“Everyone loves change, if it doesn’t affect them.”

– this insightful quote from Vikram Somaya, former Chief Data & Analytics Officer at PepsiC, sets the stage for our fascinating conversation hitting the Are You Human podcast now.

AI is transforming our world at an incredible pace, reshaping everything from consumer behaviour to business operations. That’s why I believe, Vikram’s hard-won wisdom on driving transformation through data analytics has never been more relevant.

Having led data strategies across media giants like ESPN and Nielsen, as well as an iconic CPG brand like PepsiCo, Vikram offers a rare cross-industry perspective, that I’m so grateful he shares with my dear audience – you.

More importantly, Vikram doesn’t hold back on the existential challenges AI poses for businesses and society. We candidly discuss the risks of bias in automated decision-making and the ethical guardrails companies must implement.

Perhaps most eye-opening are his views on AI’s potential to disrupt consumer preferences, brand loyalty. Don’t miss out.

Transcript:

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how do we take advantage of the amazing

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things that are happening in in

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Enterprise data technology in all the

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amazing things that we’re now hearing

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about with AI to actually make business

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better to make people have better

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experiences and sometimes that thread

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gets lost a little bit we get so caught

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up in the technology we forget why are

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we actually doing this but sometimes

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they’re they’re afraid to say I don’t

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know right and and and some some cases I

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don’t blame them it’s hard right you

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have to get up and say look there’s this

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completely new way of doing something

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that I’ve been doing for 10 20 in some

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cases at pepsic Disney 40 years right

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and it’s different and everything I

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thought I knew about how to do my job

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and how many people it would require and

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how much investment I have to put in is

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changing and everyone loves change if it

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doesn’t affect them right right I mean

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and that’s that that’s the nature of

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that process so it’s it can be difficult

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and it can be hard and it can be um uh

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it can be humbling right and I think if

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you go in there with the attitude that

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this is about learning this is about

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experience and we have to be part of how

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these things change and that means your

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path might eventually lead somewhere

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else and that’s that’s what happened

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with me and others um we are part of a

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story we are part of a chapter in a book

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right and that book you have one that is

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your own life your own book Your Own

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Story your own experience and the other

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is the life of these companies and

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sometimes you’ll be part of them

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sometimes you won’t but I think if you

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can find again going back to the things

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that matter find culture find Innovation

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find curiosity and use those as your not

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stars for change um and and be confident

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in the fact that learning is the most

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powerful tool you can possess I think

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those are all powerful qualities and and

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at well-run companies like the ones I

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worked for I think you know we’ve seen

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Success With

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It are you

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[Music]

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human hi VI CR and our friend s rashidi

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told me so so many great things about

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you I’m really really curious to hear

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all the things you’ve been um doing

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since you left epito right yeah thanks

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cam I first of all thank you for having

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me it’s always it’s always nice to talk

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to people who have something interesting

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to say and interesting questions to ask

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yeah I um uh pepsic IOD it wears in late

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January and since then you know there

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are very few times in life when you

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really get an opportunity to explore

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what’s going on outside the world that

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you’re very used to um and you know

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large corporate companies you know they

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that becomes your Universe to some

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degree especially when there is loud

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weico you know 185 markets we had a lot

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of work to do I was running a team of

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about 1100 people all in it’s a that’s a

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full-time very consuming job um and so

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I’ve had the opportunity now to spend a

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lot of time with everyone from Young

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startups we’re working in all forms of

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AI and what’s happening in analytics in

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the world today and and then also medium

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to large corporations so companies that

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are really thinking through some of the

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same problems that PepsiCo was or ESPN

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was or or neelsen was some of the

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companies I’ve worked at in the past um

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and that freedom has been very enjoyable

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I’ve uh I’ve really really had a good

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time was it deliberate that you chose

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those um Industries media and then uh

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retail or you just yeah it’s a good

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question I I don’t think anything in my

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life has been widely deliberate i u you

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know I’ve had my whole life um it is

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part of how I function and you know as

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with all things neuro there are pros and

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cons to how my brain works I like a lot

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of stimulus I really enjoy people I need

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a lot of data to process things um but

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then when I’m ready to I move on and

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that has informed my career in a lot of

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ways when I came out of college and I

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you know I originally went to to Yale

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for molecular biology and biochemistry

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and graduated with a degree in the

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history of architecture that’s not so

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wildly different because my mother and

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my sister are both Architects and it’s

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something I grew up with but when I

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graduated I went to work initially for a

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creative advertising agency called Cliff

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Freeman and partners and you know the

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notion of what Cliff did because he

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focused on using people to create

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emotional messaging and that story then

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sted with me in a variety of different

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ways over time because the next phase I

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went to was into the startup world and I

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spent uh you know things 12 years at

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four different startups all in the early

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consumer data space you know the early

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days of web Analytics companies like

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omniture that originated really some of

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how analytics was used uh using sort of

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internet technology and then companies

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like blue Kai which became the heart of

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the Oracle data cloud and was one of the

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first creators of the DMP the data

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management platforms used by large

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corporations that have now sort of

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morphed into consumer data platforms and

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various other ways to understand people

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but I think the thread that linked all

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those things was I was interested in how

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people behaved and I was interested in

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people period and that then translated

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into the next half of my career which

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became media so I spent time at Reuters

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I spent time at The Weather Channel

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which is going through an amazing

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transformation um and then finally uh uh

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originated the role of global data

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officer at ESPN and Disney media and

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then uh finally spent some time at

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neelsen before I spent the last just

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over four years at PepsiCo as its first

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Chief data analytics

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officer yeah because I I can I I I

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understand that this type of role and

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together with Chief digital officers

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it’s quite new it is y was it was it

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when you

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joined was it part of your job to Define

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what you are going to do

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absolutely um and I you know I know you

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know so rash introduced me and she and I

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share a lot of common thoughts around

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sort of the changing nature of this job

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and I don’t think it’s just the cdao job

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that’s changing I think it’s all the

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jobs around technology and consumer um

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that are sort of some of them have been

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Legacy jobs for a long time the CTO the

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CIO the CMO and some of them are much

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newer the chief analytics officer the

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chief data officer in my case Chief data

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analytics officer you know the

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origination now of what they’re calling

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Chief AI officer which is is nonsensical

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because AI has been around for a long

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time and has been very much part and the

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Heart In some cases of what analytics

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has been for a lot of these companies

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those jobs are all beginning to merge

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right and depending on which company you

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look at what stage of their data and

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Analytics Journey they’re on what size

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they are what companies they operate in

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those roles can be widely different

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right depending on how they have chosen

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to operate and who they have chosen in

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many cases to lead those functions so if

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we go back to sort of the heart of the

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chief data analytics officer role it

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really has been how do we use data and

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information better at the company how do

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we take advantage of the amazing things

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that are happening in in Enterprise data

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technology in all the amazing things

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that we’re now hearing about with AI to

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actually make business better to make

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people have better experiences and

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sometimes that thread gets lost a little

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bit we get so caught up in the

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technology we forget why we actually

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doing this and I think the human

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connection is what links those two

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things together both the employees the

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consumers and guests and associates they

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serve I love all the words that people

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use to describe the people that they

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Service uh and then finally obviously

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what we as Leaders find interesting and

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useful and how we create culture around

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it h and you’ve been going through

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through like you you were in it when

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pandemic happened and the whole consumer

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Behavior shifted right like I guess now

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it’s in some aspects it’s coming back to

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what it was and in some aspects it

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stayed but how how did you see it from

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from the inside you know I had a

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fascinating experience so I joined

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PepsiCo in I think it was fall of

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2019 um and I had a wonderful boss uh

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Hugh Johnston who was the CFO of the

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company at the time he’s then

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subsequently moved on to Disney and

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oddly and and what Hugh gave me time to

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do was to go and listen to the

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company um and there were obviously some

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specific needs that were required but it

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was really about understanding what the

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company required and so I had the time I

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spent time between then and oddly March

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of 2020 um to really go out and visit

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the company and again this is a

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far-flung company many countries many

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continents many offices many people um

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and it was an amazing experience because

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I presented the first time to the

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executive committee in March of 2020 the

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first week one week after that the

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company shut down as did the rest of the

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world and I had then that the

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opportunity to build a team but within

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the confines of Co um and it was an

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astonishing experience when I got there

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it was a team of one me um and when I

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left in January of 2024 this January we

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were at 1100 people um and one of the

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things that I focused on was I

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recognized that there was a lot of

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things that needed to be done but in

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order to preserve the culture and Legacy

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of what the company had built and also

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to bring in new blood we ensured that

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our teams were always 50/50 right my

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team had to be 50% New Blood new

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technologists data scientists AI experts

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folks who were thinking about the

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ethical nature of of what we were doing

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with analytics and also people who truly

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understood how these large Enterprises

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worked right and PepsiCo has no shortage

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of amazing talent

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there were amazing people to go out and

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pick from and some jobs required that

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I’ll give you an example data governance

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which is this you know band lead about

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word it’s a hard word right because it

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sounds very bureaucratic it sounds like

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you’re slowing down Enterprise progress

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but it’s really understanding how to

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organize the information you have and

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those folks we had to find from within

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the company you know and that was that

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was during covid that was difficult

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right because how how these companies

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are built on relationships and when you

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can’t go out and meet them it was uh it

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was it was tough so what did you offer

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them how did you make it how did you

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make it attractive yeah I think this is

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where culture plays really important

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role um I we wanted to build a team that

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felt like they had a purpose and to be

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to be clear we also had an incredible

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amount of support one of the advantages

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one of the very few advantages that Co

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gave us was some of our Executives had

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more time in fact our CEO Ramon laguarta

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who is a wonderful CEO had more time and

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so I was able to spend some time

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directly with him uh on at one point a

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weekly basis to try and understand what

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the ideas he had for the future of the

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company and it is astonishing when you

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have a CEO who is willing to learn

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willing to listen and then makes the

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decisions that he or she needs to make

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to make sure that the company is

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thinking about the future and Ramon is

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very much one of those CEOs um and and

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he gave us Direction and purpose and

295
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guidance and really allowed us to build

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a team that would use the best what was

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in the company but allow us to bring in

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what we needed to bring in to transform

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not just all the shiny metal objects of

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AI and analytics and all the cool

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applications we could build but actually

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fixing the infrastructure right

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fundamentally understanding that any

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large Enterprise organization today has

305
00:11:16,120 –> 00:11:20,399
too much data right they have more data

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than they need typically and yeah the

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problem is how to get that organized

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especially when you’ve been used to

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operating in a in a variety of different

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ways and that problem by the way I saw

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it ESPN we saw it

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and in any you see today everybody is on

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a journey right and what makes it tricky

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is technology is Shifting so quickly now

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the question is when you’re making these

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big Investments and you know tens of

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millions they already

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outdated it get outdated yeah I think

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that’s that’s that’s part of the magic

320
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is trying to understand where are we

321
00:11:51,040 –> 00:11:55,800
today where do we need to go and then

322
00:11:53,839 –> 00:11:57,360
it’s not a straight line it’s kind of a

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you know it’s like navigating by boat

324
00:11:57,360 –> 00:12:02,079
you have to pick a path going to go here

325
00:12:00,320 –> 00:12:03,519
and maybe the Seas will be rough today

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and maybe the winds will take us that

327
00:12:03,519 –> 00:12:06,200
way but you kind of you finally make it

328
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there and then you make it to the next

329
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one and you make it to the next one but

330
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culture I think is what keeps the boat

331
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sort of afloat right and so I focused

332
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very hard on creating a sense of

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belonging for this company and for these

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people because they needed to believe

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that they could actually impact

336
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transformation at a company like PepsiCo

337
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or a company like neelson or a company

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like ESPN and without that sort of

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guiding nordstar I think it’s very

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difficult to succeed and we had a lot of

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support in doing

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that yeah so this is I guess the most

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important um Factor right like having

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people um supporting each other

345
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communicating and

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brainstorming um because what other

347
00:12:46,839 –> 00:12:51,639
factors do you think are setting apart

348
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those companies which are winning the

349
00:12:51,639 –> 00:12:56,160
race and and and being competitive and

350
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being I think the human differentiator

351
00:12:56,160 –> 00:12:59,839
is the greatest right and after you had

352
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a

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00:12:59,839 –> 00:13:04,560
a manager named Athena canura and Athena

354
00:13:02,399 –> 00:13:07,440
is a Dr atina canura she’s a remarkable

355
00:13:04,560 –> 00:13:09,480
woman she actually ran a huge portion of

356
00:13:07,440 –> 00:13:11,399
the accenta analytics world and when she

357
00:13:09,480 –> 00:13:13,040
came in she had a PhD in sort of the

358
00:13:11,399 –> 00:13:15,480
early days of statistics and data

359
00:13:13,040 –> 00:13:17,079
science so uh she ran all of strategy

360
00:13:15,480 –> 00:13:19,120
and transformation at the time that I

361
00:13:17,079 –> 00:13:20,760
was there and to have somebody who

362
00:13:19,120 –> 00:13:23,440
fundamentally understands the language

363
00:13:20,760 –> 00:13:25,079
in which you speak has strong ideas um

364
00:13:23,440 –> 00:13:26,959
and and can really speak to everyone on

365
00:13:25,079 –> 00:13:29,519
your team from a data scientist up to a

366
00:13:26,959 –> 00:13:31,560
chief strategist it makes it much easier

367
00:13:29,519 –> 00:13:34,320
right and and and you have then the

368
00:13:31,560 –> 00:13:37,079
joint creating joint goals for the

369
00:13:34,320 –> 00:13:38,440
leadership team of the company becomes

370
00:13:37,079 –> 00:13:40,320
easier because you have somebody who

371
00:13:38,440 –> 00:13:41,880
supports you who is thinking about what

372
00:13:40,320 –> 00:13:43,240
you’re thinking about obviously has a

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00:13:41,880 –> 00:13:44,839
broader remit and other things that she

374
00:13:43,240 –> 00:13:46,600
was thinking about for the broader

375
00:13:44,839 –> 00:13:48,360
digital and and corporate transformation

376
00:13:46,600 –> 00:13:49,959
of the company but you don’t have to

377
00:13:48,360 –> 00:13:52,639
explain everything to her because she

378
00:13:49,959 –> 00:13:55,360
knows right and so to have that support

379
00:13:52,639 –> 00:13:58,120
to have remone to have H when in my the

380
00:13:55,360 –> 00:14:01,120
initial phase of my job um that was an

381
00:13:58,120 –> 00:14:02,680
amazing thing right and and then as we

382
00:14:01,120 –> 00:14:05,079
built out the company as we built out

383
00:14:02,680 –> 00:14:07,199
the the function I’m afraid uh I’m sorry

384
00:14:05,079 –> 00:14:08,800
um we found people that really had the

385
00:14:07,199 –> 00:14:10,959
same passion and energy for what it is

386
00:14:08,800 –> 00:14:12,880
we did and the cool thing was there were

387
00:14:10,959 –> 00:14:14,600
plenty of them to be found and during

388
00:14:12,880 –> 00:14:17,560
covid you know it was an interesting

389
00:14:14,600 –> 00:14:19,160
reaction that everybody had right we we

390
00:14:17,560 –> 00:14:21,720
there was some guilt about not being in

391
00:14:19,160 –> 00:14:24,279
the office and so we worked extremely

392
00:14:21,720 –> 00:14:27,160
hard I mean I remember long phases I

393
00:14:24,279 –> 00:14:29,720
mean quarters of you know 15 18 hour

394
00:14:27,160 –> 00:14:31,560
days where and you remember everybody

395
00:14:29,720 –> 00:14:34,279
remembers right we were on Zoom meeting

396
00:14:31,560 –> 00:14:38,160
after Zoom meeting or teams or yeah that

397
00:14:34,279 –> 00:14:40,040
wasn’t necessarily healthy oh no it was

398
00:14:38,160 –> 00:14:42,920
as you mentioned that pendulum has swung

399
00:14:40,040 –> 00:14:44,320
a little bit right so we have we had a

400
00:14:42,920 –> 00:14:47,120
lot of people who got used to working

401
00:14:44,320 –> 00:14:48,600
from home or moved to other places my

402
00:14:47,120 –> 00:14:50,440
best friend got up from New York City

403
00:14:48,600 –> 00:14:52,079
and moved to the mountains in Montana

404
00:14:50,440 –> 00:14:54,199
and you know loves it there and has

405
00:14:52,079 –> 00:14:55,519
never come back and I think as you

406
00:14:54,199 –> 00:14:57,320
pointed out some of that pendulum has

407
00:14:55,519 –> 00:14:58,600
swung back you know companies are

408
00:14:57,320 –> 00:14:59,800
requiring people to be back in the

409
00:14:58,600 –> 00:15:01,839
office

410
00:14:59,800 –> 00:15:03,399
before I left Epico you know i’ said we

411
00:15:01,839 –> 00:15:04,880
need you to be in the office for 3 days

412
00:15:03,399 –> 00:15:06,839
but there was some flexibility around

413
00:15:04,880 –> 00:15:08,320
how you do that I spoke to a lot of my

414
00:15:06,839 –> 00:15:09,720
peers around what they were doing and

415
00:15:08,320 –> 00:15:11,519
similar things you know two three days

416
00:15:09,720 –> 00:15:13,600
in the office and some flexibility

417
00:15:11,519 –> 00:15:15,160
around that for large corporations other

418
00:15:13,600 –> 00:15:16,360
companies have gone completely remote

419
00:15:15,160 –> 00:15:18,399
you know especially a lot of smaller

420
00:15:16,360 –> 00:15:20,759
companies and I now have a business

421
00:15:18,399 –> 00:15:23,240
where I advise young startups in the AI

422
00:15:20,759 –> 00:15:25,360
space um and a lot of them went remote

423
00:15:23,240 –> 00:15:27,199
forever right because they realized that

424
00:15:25,360 –> 00:15:29,199
if they wanted to as I talked about

425
00:15:27,199 –> 00:15:31,639
earlier the the if the defining Factor

426
00:15:29,199 –> 00:15:33,639
is your human talent to allow technology

427
00:15:31,639 –> 00:15:36,199
to really Thrive you have to go where

428
00:15:33,639 –> 00:15:38,040
the fish are and that means as the world

429
00:15:36,199 –> 00:15:40,000
has changed you find people where you

430
00:15:38,040 –> 00:15:41,600
can right and I think with a lot of them

431
00:15:40,000 –> 00:15:43,079
they had a tremendous amount of success

432
00:15:41,600 –> 00:15:45,880
I do think it can be harder with large

433
00:15:43,079 –> 00:15:47,519
corporations because in order to create

434
00:15:45,880 –> 00:15:49,759
a sense of solidarity you do need to

435
00:15:47,519 –> 00:15:51,680
spend time with the business and one of

436
00:15:49,759 –> 00:15:53,720
the things that became very clear to us

437
00:15:51,680 –> 00:15:55,920
was in order for our analytics products

438
00:15:53,720 –> 00:15:58,000
to succeed we needed the business to

439
00:15:55,920 –> 00:16:00,160
fundamentally understand what we did and

440
00:15:58,000 –> 00:16:02,199
so we spent a lot of time on education

441
00:16:00,160 –> 00:16:04,720
and a lot of time on visiting right as

442
00:16:02,199 –> 00:16:06,319
soon as it became possible to do that we

443
00:16:04,720 –> 00:16:08,240
we you know we we did a huge program

444
00:16:06,319 –> 00:16:09,600
which we’ve talked about uh before this

445
00:16:08,240 –> 00:16:11,639
I can I can I can spend some time

446
00:16:09,600 –> 00:16:13,240
talking about it where um we had the

447
00:16:11,639 –> 00:16:16,240
first education program was for the top

448
00:16:13,240 –> 00:16:17,639
250 people at the company right because

449
00:16:16,240 –> 00:16:19,160
in a conversation with Ramon and me he

450
00:16:17,639 –> 00:16:20,800
said listen we’ve got to educate the

451
00:16:19,160 –> 00:16:22,079
people making the investment decisions

452
00:16:20,800 –> 00:16:24,040
not just the folks who are using the

453
00:16:22,079 –> 00:16:26,680
tools and again you know that kind of

454
00:16:24,040 –> 00:16:29,000
foresight from a CEO is is so helpful

455
00:16:26,680 –> 00:16:30,680
right because it allows you to then

456
00:16:29,000 –> 00:16:32,079
Focus your activities on the things that

457
00:16:30,680 –> 00:16:34,240
matter and I will tell you that

458
00:16:32,079 –> 00:16:35,199
education program served us for the next

459
00:16:34,240 –> 00:16:38,319
four

460
00:16:35,199 –> 00:16:40,759
years how did it work so what what what

461
00:16:38,319 –> 00:16:45,399
was the main yeah what was the main uh

462
00:16:40,759 –> 00:16:49,079
objective and how like what struggle and

463
00:16:45,399 –> 00:16:51,279
and what was the um stimula what was the

464
00:16:49,079 –> 00:16:54,680
reason why you decided

465
00:16:51,279 –> 00:16:56,920
to I mean I think in order to at a

466
00:16:54,680 –> 00:17:00,519
company like PepsiCo or a company like

467
00:16:56,920 –> 00:17:02,519
Disney in order to actually take out

468
00:17:00,519 –> 00:17:05,000
powerful new technology products that

469
00:17:02,519 –> 00:17:07,079
will change jobs change organizational

470
00:17:05,000 –> 00:17:08,919
structures change the way people are

471
00:17:07,079 –> 00:17:10,640
used to operating sometimes very

472
00:17:08,919 –> 00:17:12,120
successfully right these are these are

473
00:17:10,640 –> 00:17:13,319
not companies that were not having a

474
00:17:12,120 –> 00:17:15,559
problem these were companies that have

475
00:17:13,319 –> 00:17:17,000
done very well and sometimes it’s harder

476
00:17:15,559 –> 00:17:18,319
to change a company that’s done very

477
00:17:17,000 –> 00:17:20,720
well than to change a company that

478
00:17:18,319 –> 00:17:22,520
hasn’t because the impetus for change as

479
00:17:20,720 –> 00:17:24,319
you’ve pointed out might be less that’s

480
00:17:22,520 –> 00:17:26,480
where you need leadership right where

481
00:17:24,319 –> 00:17:30,240
you need people like a bob Iger at

482
00:17:26,480 –> 00:17:32,720
Disney or Ramon at at at at PepsiCo um

483
00:17:30,240 –> 00:17:35,919
to say we are setting a nor star because

484
00:17:32,720 –> 00:17:37,240
we are anticipating change down the road

485
00:17:35,919 –> 00:17:39,280
and we want to make sure no matter

486
00:17:37,240 –> 00:17:41,559
what’s going on now we want to create an

487
00:17:39,280 –> 00:17:43,400
environment where we are encouraging

488
00:17:41,559 –> 00:17:45,120
change not just for the sake of change

489
00:17:43,400 –> 00:17:47,120
but because we know the company will

490
00:17:45,120 –> 00:17:49,280
require it right and that’s why

491
00:17:47,120 –> 00:17:51,919
education is not just the first step

492
00:17:49,280 –> 00:17:54,080
education is an evergreen process and

493
00:17:51,919 –> 00:17:56,480
you know I do wish every company would

494
00:17:54,080 –> 00:17:58,200
do education more often because we get

495
00:17:56,480 –> 00:18:00,919
very used to the idea that we have these

496
00:17:58,200 –> 00:18:02,640
very smart capable people and you know

497
00:18:00,919 –> 00:18:04,080
they we often we brought them in or we

498
00:18:02,640 –> 00:18:06,240
we’ve educated them based on what we

499
00:18:04,080 –> 00:18:09,039
knew they knew but sometimes they’re

500
00:18:06,240 –> 00:18:11,200
they’re afraid to say I don’t know right

501
00:18:09,039 –> 00:18:12,720
and and and I some some cases I don’t

502
00:18:11,200 –> 00:18:14,640
blame them it’s hard right you have to

503
00:18:12,720 –> 00:18:16,080
get up and say look there’s this

504
00:18:14,640 –> 00:18:18,320
completely new way of doing something

505
00:18:16,080 –> 00:18:21,120
that I’ve been doing for 10 20 in some

506
00:18:18,320 –> 00:18:23,280
cases at PepsiCo Disney 40 years right

507
00:18:21,120 –> 00:18:25,320
and it’s different and everything I

508
00:18:23,280 –> 00:18:26,840
thought I knew about how to do my job

509
00:18:25,320 –> 00:18:28,760
and how many people it would require and

510
00:18:26,840 –> 00:18:32,360
how much investment I have to put in is

511
00:18:28,760 –> 00:18:35,120
is changing and everyone loves change if

512
00:18:32,360 –> 00:18:37,039
it doesn’t affect them right right I

513
00:18:35,120 –> 00:18:39,640
mean that’s that’s the nature of that

514
00:18:37,039 –> 00:18:43,840
process so it’s it can be difficult and

515
00:18:39,640 –> 00:18:46,159
it can be hard and it can be um uh it

516
00:18:43,840 –> 00:18:47,919
can be humbling right and I think if you

517
00:18:46,159 –> 00:18:49,600
go in there with the attitude that this

518
00:18:47,919 –> 00:18:51,919
is about learning this is about

519
00:18:49,600 –> 00:18:53,919
experience and we have to be part of how

520
00:18:51,919 –> 00:18:55,280
these things change and that means your

521
00:18:53,919 –> 00:18:56,720
path might eventually lead somewhere

522
00:18:55,280 –> 00:18:59,559
else and that’s that’s what happened

523
00:18:56,720 –> 00:19:01,600
with me and others um we are part of a

524
00:18:59,559 –> 00:19:03,280
story we are part of a chapter in a book

525
00:19:01,600 –> 00:19:04,919
right and that book you have one that is

526
00:19:03,280 –> 00:19:06,600
your own life your own book Your Own

527
00:19:04,919 –> 00:19:08,400
Story your own experience and the other

528
00:19:06,600 –> 00:19:09,559
that is the life of these companies and

529
00:19:08,400 –> 00:19:11,400
sometimes you’ll be part of them

530
00:19:09,559 –> 00:19:13,240
sometimes you won’t but I think if you

531
00:19:11,400 –> 00:19:16,200
can find again going back to the things

532
00:19:13,240 –> 00:19:19,159
that matter find culture find Innovation

533
00:19:16,200 –> 00:19:22,400
find curiosity and use those as your not

534
00:19:19,159 –> 00:19:24,480
stars for change um and and be confident

535
00:19:22,400 –> 00:19:26,120
in the fact that learning is the most

536
00:19:24,480 –> 00:19:28,000
powerful tool you can possess I think

537
00:19:26,120 –> 00:19:29,720
those are all powerful qualities and and

538
00:19:28,000 –> 00:19:31,280
at well-run companies like the ones I

539
00:19:29,720 –> 00:19:34,400
worked for I think you know we’ve seen

540
00:19:31,280 –> 00:19:37,799
success with it this is what will save

541
00:19:34,400 –> 00:19:41,000
people in in this whole um

542
00:19:37,799 –> 00:19:46,240
transformational exponential exponential

543
00:19:41,000 –> 00:19:50,520
uh time of where you know using tools uh

544
00:19:46,240 –> 00:19:53,000
embedded with like with AI um it’s it’s

545
00:19:50,520 –> 00:19:55,280
becoming like the normal type of work

546
00:19:53,000 –> 00:19:58,919
you are doing it’s a commodity so you

547
00:19:55,280 –> 00:20:01,679
have to put focus into

548
00:19:58,919 –> 00:20:04,400
like self-learning and and being more

549
00:20:01,679 –> 00:20:06,960
creative than what another person can

550
00:20:04,400 –> 00:20:09,480
can do with no look it’s absolutely true

551
00:20:06,960 –> 00:20:12,000
you know was interesting I was at a

552
00:20:09,480 –> 00:20:14,640
um when I think about that notion of how

553
00:20:12,000 –> 00:20:16,120
you res skill yourself and and read on

554
00:20:14,640 –> 00:20:17,280
people always ask me how do I get you

555
00:20:16,120 –> 00:20:18,679
know especially Business Leaders are

556
00:20:17,280 –> 00:20:20,880
like how do I get you know how do I get

557
00:20:18,679 –> 00:20:22,799
smarter about what’s possible yeah what

558
00:20:20,880 –> 00:20:25,440
I always tell them is with AI especially

559
00:20:22,799 –> 00:20:28,120
now technology is changing so fast if

560
00:20:25,440 –> 00:20:31,120
you spend just the extra time necessary

561
00:20:28,120 –> 00:20:33,400
to understand for your particular space

562
00:20:31,120 –> 00:20:35,440
whether it’s vertical or horizontal what

563
00:20:33,400 –> 00:20:37,039
is most interesting in AI there are so

564
00:20:35,440 –> 00:20:38,799
many opportunities to do it there’s

565
00:20:37,039 –> 00:20:40,760
stuff online there’s people there’s

566
00:20:38,799 –> 00:20:42,240
social media with people who genuinely

567
00:20:40,760 –> 00:20:44,760
know what they’re talking about there’s

568
00:20:42,240 –> 00:20:46,400
educational stuff on YouTube there are

569
00:20:44,760 –> 00:20:48,360
professional programs there are graduate

570
00:20:46,400 –> 00:20:50,360
degrees there’s a million ways you can

571
00:20:48,360 –> 00:20:51,440
become an expert and you can be the

572
00:20:50,360 –> 00:20:53,080
greatest expert in the world if you

573
00:20:51,440 –> 00:20:54,400
focus on it for the next six months

574
00:20:53,080 –> 00:20:56,640
right because there’s just so much

575
00:20:54,400 –> 00:20:59,760
specialization happening that nobody can

576
00:20:56,640 –> 00:21:02,000
be everything right um but it takes

577
00:20:59,760 –> 00:21:03,880
effort and it takes leaning and it takes

578
00:21:02,000 –> 00:21:06,240
again that humility of saying I don’t

579
00:21:03,880 –> 00:21:08,880
know what the future holds for what it

580
00:21:06,240 –> 00:21:11,279
is that I do I can learn about it I can

581
00:21:08,880 –> 00:21:13,240
become an expert on it I can I have I

582
00:21:11,279 –> 00:21:15,200
have the aptitude and the skill but if I

583
00:21:13,240 –> 00:21:18,240
sit back and just hope that the storm

584
00:21:15,200 –> 00:21:20,240
blows me by then I think that you are

585
00:21:18,240 –> 00:21:22,039
putting a lot of things at risk right

586
00:21:20,240 –> 00:21:24,520
and especially if you are a manager if

587
00:21:22,039 –> 00:21:25,400
you’re a you know a significant manager

588
00:21:24,520 –> 00:21:27,159
and some of the you know some of these

589
00:21:25,400 –> 00:21:29,520
people these last corporations run

590
00:21:27,159 –> 00:21:31,000
thousands 10 thousands of people people

591
00:21:29,520 –> 00:21:32,720
um you’re doing a disservice to all of

592
00:21:31,000 –> 00:21:34,960
the people who work for you as well

593
00:21:32,720 –> 00:21:36,640
because change will impact them right

594
00:21:34,960 –> 00:21:38,679
whether they like it or not and it might

595
00:21:36,640 –> 00:21:40,120
come slowly it might come in a measured

596
00:21:38,679 –> 00:21:42,240
way where you are actually sort of

597
00:21:40,120 –> 00:21:43,720
controlling that change or it will come

598
00:21:42,240 –> 00:21:46,919
with a way that you don’t like and you

599
00:21:43,720 –> 00:21:48,720
don’t expect right and um so pick pick

600
00:21:46,919 –> 00:21:51,120
pick a poison a little bit right take

601
00:21:48,720 –> 00:21:53,799
the extra time make the effort lean in

602
00:21:51,120 –> 00:21:55,320
educate upskill talk to people Network

603
00:21:53,799 –> 00:21:56,640
connect with some of the thinking around

604
00:21:55,320 –> 00:21:57,760
there I mean there are so many great

605
00:21:56,640 –> 00:22:00,480
opportunities like listening to

606
00:21:57,760 –> 00:22:01,600
something like this going to conferences

607
00:22:00,480 –> 00:22:03,320
uh I’m part of a couple of different

608
00:22:01,600 –> 00:22:04,760
organizations like World 50 where you

609
00:22:03,320 –> 00:22:06,679
can connect with some of your peers

610
00:22:04,760 –> 00:22:08,679
which for me has been incredibly

611
00:22:06,679 –> 00:22:10,320
educational and I owe a lot to some of

612
00:22:08,679 –> 00:22:12,799
the conversations I’ve had with with

613
00:22:10,320 –> 00:22:14,559
with my peers who are you know again

614
00:22:12,799 –> 00:22:16,400
Chief data analytics officers are kind

615
00:22:14,559 –> 00:22:18,320
of a a right brain left brain

616
00:22:16,400 –> 00:22:19,799
combination of yeah smart interesting

617
00:22:18,320 –> 00:22:21,880
people who understand the business who

618
00:22:19,799 –> 00:22:24,200
also understand technology uh and

619
00:22:21,880 –> 00:22:26,039
they’re usually very generous right um

620
00:22:24,200 –> 00:22:27,240
and I’ve always said to young people

621
00:22:26,039 –> 00:22:28,799
reach out to the people in your

622
00:22:27,240 –> 00:22:31,080
organization no matter how senior they

623
00:22:28,799 –> 00:22:33,919
are and ask for time the worst they can

624
00:22:31,080 –> 00:22:36,000
say is no right and at that point even

625
00:22:33,919 –> 00:22:38,840
the acknowledgement that you try is

626
00:22:36,000 –> 00:22:40,960
something um and I think that that that

627
00:22:38,840 –> 00:22:43,480
Spirit of curiosity and exploration and

628
00:22:40,960 –> 00:22:44,880
Innovation will now become a keystone to

629
00:22:43,480 –> 00:22:46,679
how we operate in the world today

630
00:22:44,880 –> 00:22:48,440
because it won’t just be about what you

631
00:22:46,679 –> 00:22:50,679
know or what knowledge is resid in your

632
00:22:48,440 –> 00:22:52,679
head all knowledge is now available the

633
00:22:50,679 –> 00:22:55,679
question is how do you utilize that how

634
00:22:52,679 –> 00:22:58,679
do you make it real um and for that you

635
00:22:55,679 –> 00:23:01,640
have to go out into the world yeah which

636
00:22:58,679 –> 00:23:04,400
brings me to another um aspect of you

637
00:23:01,640 –> 00:23:07,200
have a lot of knowledge but some of it

638
00:23:04,400 –> 00:23:09,760
is not real some of it is fake some some

639
00:23:07,200 –> 00:23:14,400
of the of the things you you’re reading

640
00:23:09,760 –> 00:23:19,880
you are like people just um share spread

641
00:23:14,400 –> 00:23:22,000
um are not good for you um so how in

642
00:23:19,880 –> 00:23:25,679
your opinion how do

643
00:23:22,000 –> 00:23:27,679
you how can you verify what’s what’s the

644
00:23:25,679 –> 00:23:29,640
right how you build your mental filters

645
00:23:27,679 –> 00:23:31,200
on this stuff is everything right as as

646
00:23:29,640 –> 00:23:33,480
you pointed out there is infinite

647
00:23:31,200 –> 00:23:35,400
knowledge available now we have more

648
00:23:33,480 –> 00:23:39,000
power in our phones than they did going

649
00:23:35,400 –> 00:23:41,760
to the Moon 50 years ago 60 years ago um

650
00:23:39,000 –> 00:23:43,480
got more than that now um and so

651
00:23:41,760 –> 00:23:45,440
beginning to understand how you

652
00:23:43,480 –> 00:23:48,440
differentiate between what is real and

653
00:23:45,440 –> 00:23:50,360
what is not will be a key skill right

654
00:23:48,440 –> 00:23:51,919
and I think the best way to do that is

655
00:23:50,360 –> 00:23:54,480
through the people filter not through

656
00:23:51,919 –> 00:23:56,320
the technology filter right very often

657
00:23:54,480 –> 00:23:58,120
you have to pick your sources of

658
00:23:56,320 –> 00:23:59,679
information and I’m going to stay away

659
00:23:58,120 –> 00:24:01,039
from any anything political but you know

660
00:23:59,679 –> 00:24:05,360
we live in a world today that’s highly

661
00:24:01,039 –> 00:24:07,120
polarized right and media content

662
00:24:05,360 –> 00:24:08,960
messaging even what my face looks like

663
00:24:07,120 –> 00:24:11,840
can be replicated can be changed can be

664
00:24:08,960 –> 00:24:14,520
altered can be transformed um can be

665
00:24:11,840 –> 00:24:18,200
used for purposes that are nefarious or

666
00:24:14,520 –> 00:24:22,520
or even um sort of malicious right and

667
00:24:18,200 –> 00:24:24,240
so figuring out how you trust and I I I

668
00:24:22,520 –> 00:24:27,840
I use that word casually but that word

669
00:24:24,240 –> 00:24:29,600
trust is unbelievably important right I

670
00:24:27,840 –> 00:24:30,960
think about it a lot and one of the

671
00:24:29,600 –> 00:24:32,960
things I talked to my teams about at

672
00:24:30,960 –> 00:24:35,120
PepsiCo specifically was trust is our

673
00:24:32,960 –> 00:24:37,480
most important word the fact that the

674
00:24:35,120 –> 00:24:39,320
company needs to trust us that we are

675
00:24:37,480 –> 00:24:40,960
coming in with the right intent and the

676
00:24:39,320 –> 00:24:43,120
right tools and the right technology and

677
00:24:40,960 –> 00:24:45,399
the right opportunities the fact that

678
00:24:43,120 –> 00:24:47,880
they have trust in the data itself that

679
00:24:45,399 –> 00:24:50,399
the data is correct that it is you know

680
00:24:47,880 –> 00:24:52,159
data can be very dirty in all its forms

681
00:24:50,399 –> 00:24:54,120
it depends who put it in depends how was

682
00:24:52,159 –> 00:24:56,240
created depends how it was structured or

683
00:24:54,120 –> 00:24:59,159
unstructured how it was analyzed what

684
00:24:56,240 –> 00:25:00,760
models were used to decrypt it secrets

685
00:24:59,159 –> 00:25:02,279
and then finally what were the outputs

686
00:25:00,760 –> 00:25:04,240
of these products and applications that

687
00:25:02,279 –> 00:25:05,679
we created right are they better than

688
00:25:04,240 –> 00:25:08,080
what they’ve been using before are they

689
00:25:05,679 –> 00:25:09,240
not and so both that personal trust in

690
00:25:08,080 –> 00:25:11,000
the fact that we are doing the right

691
00:25:09,240 –> 00:25:12,360
thing and that professional trust in the

692
00:25:11,000 –> 00:25:14,120
fact that the data and applications are

693
00:25:12,360 –> 00:25:15,559
right is very important and the last

694
00:25:14,120 –> 00:25:18,159
piece is what you just described which

695
00:25:15,559 –> 00:25:20,520
is we also operate in a world where we

696
00:25:18,159 –> 00:25:23,159
need external data signals right

697
00:25:20,520 –> 00:25:26,600
whatever they might be and some of those

698
00:25:23,159 –> 00:25:27,840
now are beginning to be less trusted

699
00:25:26,600 –> 00:25:29,640
than they were back when there were very

700
00:25:27,840 –> 00:25:32,200
few

701
00:25:29,640 –> 00:25:34,559
regulated or managed you know I mean now

702
00:25:32,200 –> 00:25:36,840
the world is global we are we are linked

703
00:25:34,559 –> 00:25:39,279
to everyone in in you know in one way or

704
00:25:36,840 –> 00:25:43,000
the other there are very many ways for

705
00:25:39,279 –> 00:25:44,919
people to sort of not do the right thing

706
00:25:43,000 –> 00:25:46,399
and again that’s why we need governance

707
00:25:44,919 –> 00:25:48,200
we need the world to think about this

708
00:25:46,399 –> 00:25:50,320
stuff um I know we were talking earlier

709
00:25:48,200 –> 00:25:51,600
about the fact that I’ve spent time with

710
00:25:50,320 –> 00:25:53,159
sort of the world economic forum and

711
00:25:51,600 –> 00:25:56,000
some of the work they’ve been doing with

712
00:25:53,159 –> 00:25:58,360
a lot of my peers with regulatory bodies

713
00:25:56,000 –> 00:26:01,080
with governmental and legislative bodies

714
00:25:58,360 –> 00:26:03,320
and the amount of information is widely

715
00:26:01,080 –> 00:26:05,240
variant in terms of what people know

716
00:26:03,320 –> 00:26:06,679
right I mean we have legislation

717
00:26:05,240 –> 00:26:08,399
sometimes being created by very smart

718
00:26:06,679 –> 00:26:10,200
young AIDS who are you know spending

719
00:26:08,399 –> 00:26:11,720
three six months even a year trying to

720
00:26:10,200 –> 00:26:13,760
understand all of AI it’s a difficult

721
00:26:11,720 –> 00:26:15,799
job right and and and then you’re trying

722
00:26:13,760 –> 00:26:17,120
to create legislation for the future

723
00:26:15,799 –> 00:26:18,880
when the technology is changing every

724
00:26:17,120 –> 00:26:22,159
six months every three months every

725
00:26:18,880 –> 00:26:23,440
month yeah um I was at a as I mentioned

726
00:26:22,159 –> 00:26:25,399
I was at a world economic Forum

727
00:26:23,440 –> 00:26:27,679
conference late last year where it was

728
00:26:25,399 –> 00:26:29,120
their first Forum on data governance and

729
00:26:27,679 –> 00:26:30,200
really thinking about sort of you know

730
00:26:29,120 –> 00:26:32,760
what’s going to change and they had

731
00:26:30,200 –> 00:26:35,960
legislators and technologists and and ex

732
00:26:32,760 –> 00:26:38,399
and operational leaders like myself and

733
00:26:35,960 –> 00:26:41,679
sort of one of the things that came up a

734
00:26:38,399 –> 00:26:44,080
ton was the speed at which this

735
00:26:41,679 –> 00:26:45,200
particular Revolution is taking place

736
00:26:44,080 –> 00:26:46,799
right when you think about even the

737
00:26:45,200 –> 00:26:49,080
internet Revolution or the mobile

738
00:26:46,799 –> 00:26:50,480
Revolution um the technology Revolution

739
00:26:49,080 –> 00:26:53,360
even the Industrial Revolution they you

740
00:26:50,480 –> 00:26:56,360
had some time to figure some stuff out

741
00:26:53,360 –> 00:26:58,240
with AI what we do today in six months

742
00:26:56,360 –> 00:26:59,320
could be completely redundant and I know

743
00:26:58,240 –> 00:27:00,640
don’t mean a little bit redundant I

744
00:26:59,320 –> 00:27:02,320
don’t mean you can keep using that old

745
00:27:00,640 –> 00:27:04,919
one for three years and it’ll kind of be

746
00:27:02,320 –> 00:27:08,559
all right it’s not going to work right

747
00:27:04,919 –> 00:27:12,880
not the same way so I think that that

748
00:27:08,559 –> 00:27:15,760
pace of change is new um and the amount

749
00:27:12,880 –> 00:27:17,640
of impact it’s having mainly because now

750
00:27:15,760 –> 00:27:19,919
consumers have become very aware of it

751
00:27:17,640 –> 00:27:22,320
since the end of 2022 when Chad GPT

752
00:27:19,919 –> 00:27:23,919
became real um and suddenly they saw in

753
00:27:22,320 –> 00:27:25,159
all of the consumer applications that

754
00:27:23,919 –> 00:27:27,360
they were used to dealing with that

755
00:27:25,159 –> 00:27:29,480
there was this revolutionary new way to

756
00:27:27,360 –> 00:27:32,039
think about how content is generated and

757
00:27:29,480 –> 00:27:33,679
how of you can speak to a computer if

758
00:27:32,039 –> 00:27:35,159
you will and how it can create things

759
00:27:33,679 –> 00:27:37,360
for you that were just not possible

760
00:27:35,159 –> 00:27:39,840
before this suddenly AI which had been

761
00:27:37,360 –> 00:27:42,279
around for decades became all in the

762
00:27:39,840 –> 00:27:43,760
Forefront and we see again the same hype

763
00:27:42,279 –> 00:27:45,480
cycle you know some of the stuff that

764
00:27:43,760 –> 00:27:49,399
people were expecting to work is not

765
00:27:45,480 –> 00:27:52,200
working um they I also I always laugh

766
00:27:49,399 –> 00:27:54,760
about this when I presented I used the

767
00:27:52,200 –> 00:27:56,600
analogy of an iceberg right it actually

768
00:27:54,760 –> 00:27:58,679
became the logo of our team subsequent

769
00:27:56,600 –> 00:28:00,120
to that because the top of the iceberg

770
00:27:58,679 –> 00:28:01,600
is you know the 10% that you see and

771
00:28:00,120 –> 00:28:03,679
it’s the AI and the analytics and the

772
00:28:01,600 –> 00:28:07,120
cool stuff but the bottom of the iceberg

773
00:28:03,679 –> 00:28:09,000
is the data right and and data goes from

774
00:28:07,120 –> 00:28:10,720
sexy to non-sexy to sexy to non-sexy and

775
00:28:09,000 –> 00:28:12,200
it’s kind of in between right now but

776
00:28:10,720 –> 00:28:13,960
and it’s painful right nobody wants to

777
00:28:12,200 –> 00:28:16,080
hear about how complicated it is to get

778
00:28:13,960 –> 00:28:18,840
your data organized but I think what’s

779
00:28:16,080 –> 00:28:21,760
changing is historically when analytics

780
00:28:18,840 –> 00:28:23,799
were presented primarily a report not us

781
00:28:21,760 –> 00:28:25,320
be numbers and often there was a fair

782
00:28:23,799 –> 00:28:27,080
amount of hey skepticism you know these

783
00:28:25,320 –> 00:28:29,279
are not my reports these are not my

784
00:28:27,080 –> 00:28:30,279
numbers where do you get them from yeah

785
00:28:29,279 –> 00:28:32,360
with some of the stuff that’s being

786
00:28:30,279 –> 00:28:34,360
generated now it could read like a

787
00:28:32,360 –> 00:28:36,960
report written by human analyst who took

788
00:28:34,360 –> 00:28:40,480
a week to report it except it took one

789
00:28:36,960 –> 00:28:42,120
second to generate by an AI and you are

790
00:28:40,480 –> 00:28:43,960
more likely to believe something when

791
00:28:42,120 –> 00:28:45,919
you believe that it came from what felt

792
00:28:43,960 –> 00:28:47,640
like a human right and that could be a

793
00:28:45,919 –> 00:28:49,559
written report and there there’s lots of

794
00:28:47,640 –> 00:28:51,880
talk now about a lot of startups now are

795
00:28:49,559 –> 00:28:54,440
working with the creation of human face

796
00:28:51,880 –> 00:28:56,080
and voice and emotion um you know there

797
00:28:54,440 –> 00:28:57,760
are owning SS happening with some of

798
00:28:56,080 –> 00:28:59,760
these things happening on them now not

799
00:28:57,760 –> 00:29:03,279
just analysis of those from real people

800
00:28:59,760 –> 00:29:04,960
but the creation of you know fake people

801
00:29:03,279 –> 00:29:06,480
essentially talking about things in an

802
00:29:04,960 –> 00:29:08,000
expressive way that you and I would

803
00:29:06,480 –> 00:29:09,840
consider the domain of a human before

804
00:29:08,000 –> 00:29:11,159
that you’re more likely to believe that

805
00:29:09,840 –> 00:29:13,600
that’s just how we’re biologically

806
00:29:11,159 –> 00:29:17,240
hardwired do you because there is this

807
00:29:13,600 –> 00:29:20,679
concept of um uncanny valley right the

808
00:29:17,240 –> 00:29:23,600
there we humans can feel that something

809
00:29:20,679 –> 00:29:26,279
is off and it’s makes us uncomfortable

810
00:29:23,600 –> 00:29:28,320
yes look with Graphics we we we we

811
00:29:26,279 –> 00:29:29,840
crossed that barrier a long time ago

812
00:29:28,320 –> 00:29:32,440
right I mean if you remember the early

813
00:29:29,840 –> 00:29:33,840
days of of 3D effects in movies you

814
00:29:32,440 –> 00:29:35,840
would have you know that sort of

815
00:29:33,840 –> 00:29:37,960
weirdness and as you mentioned that

816
00:29:35,840 –> 00:29:40,480
uncanny valley notion that you can tell

817
00:29:37,960 –> 00:29:42,960
that they’re not quite there deep fakes

818
00:29:40,480 –> 00:29:44,640
now are unbelievably good right I mean

819
00:29:42,960 –> 00:29:46,399
quite frankly in most cases you will not

820
00:29:44,640 –> 00:29:48,360
be able to tell the difference often

821
00:29:46,399 –> 00:29:50,600
some of these AIS are beating cheering

822
00:29:48,360 –> 00:29:52,559
tests which is the proof that you are in

823
00:29:50,600 –> 00:29:54,840
fact human right maybe these tests need

824
00:29:52,559 –> 00:29:56,640
to be changed and re reevaluated and I

825
00:29:54,840 –> 00:29:58,679
think the line between what is created

826
00:29:56,640 –> 00:30:01,440
and what is real as you pointed out out

827
00:29:58,679 –> 00:30:03,360
is a lot more gray and and quite frankly

828
00:30:01,440 –> 00:30:05,360
most of us are not equipped anymore to

829
00:30:03,360 –> 00:30:07,720
tell the difference of truly advanced

830
00:30:05,360 –> 00:30:08,640
technology um and was it Arthur C Clark

831
00:30:07,720 –> 00:30:11,039
who said you know the difference between

832
00:30:08,640 –> 00:30:13,159
Magic and sort of magic is just science

833
00:30:11,039 –> 00:30:14,720
that we haven’t understood yet yeah

834
00:30:13,159 –> 00:30:16,600
right and so a lot of the things that

835
00:30:14,720 –> 00:30:18,240
we’re seeing now feel magical because

836
00:30:16,600 –> 00:30:19,840
for a lot of us we’re not fully

837
00:30:18,240 –> 00:30:21,559
conversent with how and why they were

838
00:30:19,840 –> 00:30:23,240
created and you think about you know

839
00:30:21,559 –> 00:30:26,279
some of the darker side of this stuff

840
00:30:23,240 –> 00:30:28,440
fraud and uh you know earlier it used to

841
00:30:26,279 –> 00:30:29,559
be fishing emails or a text and thing

842
00:30:28,440 –> 00:30:32,320
from somebody you thought now it could

843
00:30:29,559 –> 00:30:34,080
be a voicemail from your video voicemail

844
00:30:32,320 –> 00:30:36,279
from your mother saying I’m in trouble

845
00:30:34,080 –> 00:30:38,519
and I need money and so and so and you

846
00:30:36,279 –> 00:30:41,279
know lots of people have fallen prey to

847
00:30:38,519 –> 00:30:43,000
scamming already lots of companies have

848
00:30:41,279 –> 00:30:44,600
been hacked ransomware all sorts of

849
00:30:43,000 –> 00:30:46,159
things are happening in cyber and

850
00:30:44,600 –> 00:30:47,720
there’s no shortage of scary things that

851
00:30:46,159 –> 00:30:50,120
can be done with these Technologies but

852
00:30:47,720 –> 00:30:52,960
again you know when when jny I first

853
00:30:50,120 –> 00:30:54,480
came out every board every CEO every

854
00:30:52,960 –> 00:30:56,840
every senior leader wanted to know how

855
00:30:54,480 –> 00:30:58,200
they could be more relevant in this and

856
00:30:56,840 –> 00:31:01,240
one of the first things we did was to

857
00:30:58,200 –> 00:31:02,960
say hold on right large language models

858
00:31:01,240 –> 00:31:04,360
are processing data for in some cases

859
00:31:02,960 –> 00:31:07,000
from as much of the internet as they can

860
00:31:04,360 –> 00:31:09,399
see some of this data is not copyrighted

861
00:31:07,000 –> 00:31:11,880
some of this data we cannot use if you

862
00:31:09,399 –> 00:31:14,360
actually ask a question of a large

863
00:31:11,880 –> 00:31:15,880
language model you are educating it are

864
00:31:14,360 –> 00:31:17,480
you educating them on things that you

865
00:31:15,880 –> 00:31:18,919
should not be educating them on and

866
00:31:17,480 –> 00:31:20,440
obviously we worked with our large

867
00:31:18,919 –> 00:31:22,399
technology Partners to figure out how to

868
00:31:20,440 –> 00:31:23,559
privatize those Notions and you know

869
00:31:22,399 –> 00:31:26,200
every cdao will tell you they’re

870
00:31:23,559 –> 00:31:28,039
figuring out how to essentially create a

871
00:31:26,200 –> 00:31:29,639
a shared but private space right with

872
00:31:28,039 –> 00:31:30,639
they can converse with the AI without

873
00:31:29,639 –> 00:31:32,720
losing all of their corporate

874
00:31:30,639 –> 00:31:35,279
information but that warning was

875
00:31:32,720 –> 00:31:37,799
important you know we’re at the stage

876
00:31:35,279 –> 00:31:39,720
with AI a little like Prometheus with

877
00:31:37,799 –> 00:31:41,240
fire right we know that it’s this

878
00:31:39,720 –> 00:31:42,880
unbelievably power in fact I used a

879
00:31:41,240 –> 00:31:44,320
stronger analogy when I was talking to

880
00:31:42,880 –> 00:31:47,279
some of my leaders of PepsiCo I said

881
00:31:44,320 –> 00:31:48,960
this is like nuclear technology right it

882
00:31:47,279 –> 00:31:51,600
can be used for good it can be used for

883
00:31:48,960 –> 00:31:53,279
evil the technology itself doesn’t care

884
00:31:51,600 –> 00:31:55,919
it’s our application of them as human

885
00:31:53,279 –> 00:31:58,080
beings that is going to matter and so we

886
00:31:55,919 –> 00:31:59,440
have to be cautious as we think through

887
00:31:58,080 –> 00:32:01,919
this because again like I said yeah is

888
00:31:59,440 –> 00:32:05,000
not new but some of these things can

889
00:32:01,919 –> 00:32:06,600
change how people live and sort of work

890
00:32:05,000 –> 00:32:08,480
in the world today and we have to be

891
00:32:06,600 –> 00:32:10,639
cautious about that especially for a

892
00:32:08,480 –> 00:32:13,039
large corporation there there’s in

893
00:32:10,639 –> 00:32:16,600
efficient effort to think about

894
00:32:13,039 –> 00:32:21,799
potential risks such as you know uh the

895
00:32:16,600 –> 00:32:25,559
AGI concept and and how it can

896
00:32:21,799 –> 00:32:29,399
transform like the way we collaborate

897
00:32:25,559 –> 00:32:32,880
the way we live and whom we fall in love

898
00:32:29,399 –> 00:32:35,720
into like love who whom we decid to love

899
00:32:32,880 –> 00:32:39,639
like that kind of strange Concepts which

900
00:32:35,720 –> 00:32:40,799
we previously seen in um Sci-Fi movies

901
00:32:39,639 –> 00:32:44,559
yeah and look look I’ve been a huge

902
00:32:40,799 –> 00:32:46,600
sci-fi buff since I was a kid um um um I

903
00:32:44,559 –> 00:32:48,080
I firmly believe that most of our ideas

904
00:32:46,600 –> 00:32:50,120
are not new they’ve been written about

905
00:32:48,080 –> 00:32:52,120
by somebody right it’s a question of

906
00:32:50,120 –> 00:32:55,519
again how we manifest the magic into

907
00:32:52,120 –> 00:32:56,720
reality through science um and as you’ve

908
00:32:55,519 –> 00:32:58,360
pointed out the technology is

909
00:32:56,720 –> 00:32:59,960
progressing so far

910
00:32:58,360 –> 00:33:02,360
that sometimes the mechanisms that

911
00:32:59,960 –> 00:33:03,840
manage them are struggling to keep up

912
00:33:02,360 –> 00:33:06,159
right whether that’s legislation or

913
00:33:03,840 –> 00:33:08,679
regulation or even industry

914
00:33:06,159 –> 00:33:09,960
conversation um there are fundamentally

915
00:33:08,679 –> 00:33:11,279
different ways that governments are

916
00:33:09,960 –> 00:33:12,919
approaching it you know when you think

917
00:33:11,279 –> 00:33:15,080
about how Singapore or China is

918
00:33:12,919 –> 00:33:16,919
approaching it versus the us there are

919
00:33:15,080 –> 00:33:18,320
fundamental differences with sort of how

920
00:33:16,919 –> 00:33:21,320
that’s being done how that’s being

921
00:33:18,320 –> 00:33:22,760
regulated um and I don’t you know we

922
00:33:21,320 –> 00:33:24,320
don’t know what right now which one is

923
00:33:22,760 –> 00:33:25,159
going to win or which one is the best we

924
00:33:24,320 –> 00:33:27,279
just know that there are different

925
00:33:25,159 –> 00:33:29,679
approaches to this thing and because we

926
00:33:27,279 –> 00:33:31,840
live in a Village it means that

927
00:33:29,679 –> 00:33:33,240
companies like the ones I’ve worked at

928
00:33:31,840 –> 00:33:35,360
and that a lot of your viewers are

929
00:33:33,240 –> 00:33:36,880
working at we are operating in a variety

930
00:33:35,360 –> 00:33:39,399
of different spaces right whether that’s

931
00:33:36,880 –> 00:33:42,039
geographical spaces or techn technology

932
00:33:39,399 –> 00:33:43,320
spaces or even how much technical debt

933
00:33:42,039 –> 00:33:45,559
they have so can they go and quickly

934
00:33:43,320 –> 00:33:47,480
build something fast right now without

935
00:33:45,559 –> 00:33:49,480
having to worry about fixing all their

936
00:33:47,480 –> 00:33:51,799
you know some cases billions of dollars

937
00:33:49,480 –> 00:33:53,000
systems that they’ve already built or do

938
00:33:51,799 –> 00:33:56,360
they have to really think about what

939
00:33:53,000 –> 00:33:58,240
that technical debt is and so each um

940
00:33:56,360 –> 00:34:00,480
engagement as I SP more time in

941
00:33:58,240 –> 00:34:02,760
Consulting is particularly

942
00:34:00,480 –> 00:34:05,360
different right there is no Silver

943
00:34:02,760 –> 00:34:07,240
Bullet for everyone there is no common

944
00:34:05,360 –> 00:34:09,440
answer for have we have we sorted out

945
00:34:07,240 –> 00:34:11,679
bias have we thought about a regulatory

946
00:34:09,440 –> 00:34:13,520
framework have we thought about an

947
00:34:11,679 –> 00:34:15,760
ethical framework for how we think about

948
00:34:13,520 –> 00:34:17,240
the utility of this analytics and simple

949
00:34:15,760 –> 00:34:19,440
examples like when we think about

950
00:34:17,240 –> 00:34:21,240
marketing if the the AI can go off and

951
00:34:19,440 –> 00:34:24,960
learn in a way that is fundamentally

952
00:34:21,240 –> 00:34:27,040
unhuman because it’s not human right and

953
00:34:24,960 –> 00:34:28,280
even the word ethics is so interesting

954
00:34:27,040 –> 00:34:32,320
right who ethics

955
00:34:28,280 –> 00:34:35,599
mine yours are in this company in this

956
00:34:32,320 –> 00:34:37,520
country in this part of the world ethics

957
00:34:35,599 –> 00:34:39,879
are a fungible thing and we are quick to

958
00:34:37,520 –> 00:34:42,440
forgive humans for having diff different

959
00:34:39,879 –> 00:34:44,240
ethical values we will not forgive

960
00:34:42,440 –> 00:34:47,159
technology for having different ethical

961
00:34:44,240 –> 00:34:49,639
values and so that is that’s a

962
00:34:47,159 –> 00:34:51,159
philosophical question right we’re now

963
00:34:49,639 –> 00:34:52,520
approach because we’re we’re getting so

964
00:34:51,159 –> 00:34:55,000
close to the domain of what was

965
00:34:52,520 –> 00:34:57,160
previously only human business to

966
00:34:55,000 –> 00:34:59,400
determine we are now beginning to give

967
00:34:57,160 –> 00:35:01,000
some of those things to the technology

968
00:34:59,400 –> 00:35:02,680
right whether that’s predicting

969
00:35:01,000 –> 00:35:05,960
financial analysis all the way to

970
00:35:02,680 –> 00:35:07,960
deciding who do we Market to right this

971
00:35:05,960 –> 00:35:09,599
notion of human in the loop is not going

972
00:35:07,960 –> 00:35:13,160
to become less important it’s going to

973
00:35:09,599 –> 00:35:16,560
become more important it definitely will

974
00:35:13,160 –> 00:35:20,160
because maybe it’s it does not have

975
00:35:16,560 –> 00:35:22,440
ethics but the the repercussions the the

976
00:35:20,160 –> 00:35:25,520
consequences of of

977
00:35:22,440 –> 00:35:29,280
the algorithm doing I don’t know giving

978
00:35:25,520 –> 00:35:32,599
that kind of score um instead of other

979
00:35:29,280 –> 00:35:35,200
may have fundamental um you know

980
00:35:32,599 –> 00:35:36,800
consequences for for a person of course

981
00:35:35,200 –> 00:35:39,040
and you know I mean like you know the

982
00:35:36,800 –> 00:35:40,640
the the standard use case is you’re

983
00:35:39,040 –> 00:35:43,800
you’re teaching an autonomous car what

984
00:35:40,640 –> 00:35:45,640
to do in in every scenario and it’s

985
00:35:43,800 –> 00:35:48,400
about to have an accident and it’s about

986
00:35:45,640 –> 00:35:49,720
to there’s one group of of of of of

987
00:35:48,400 –> 00:35:52,760
people and there’s a young child and

988
00:35:49,720 –> 00:35:54,640
there’s one group people older and how

989
00:35:52,760 –> 00:35:57,040
does it pick right and and this goes to

990
00:35:54,640 –> 00:35:58,680
the heart of what is an ethical a human

991
00:35:57,040 –> 00:36:01,880
determination

992
00:35:58,680 –> 00:36:04,599
is at some point you have to the systems

993
00:36:01,880 –> 00:36:08,079
and the models to do something that only

994
00:36:04,599 –> 00:36:09,640
a human historically has decided um and

995
00:36:08,079 –> 00:36:11,839
I think that will be very hard for us

996
00:36:09,640 –> 00:36:12,800
all to deal with right especially when

997
00:36:11,839 –> 00:36:14,599
when you think about the history of

998
00:36:12,800 –> 00:36:16,160
analytics it was primarily sort of

999
00:36:14,599 –> 00:36:17,359
descriptive and diagnostic right

1000
00:36:16,160 –> 00:36:19,920
essentially was looking in a rearview

1001
00:36:17,359 –> 00:36:21,800
mirror showing us what has happened so

1002
00:36:19,920 –> 00:36:23,760
we as humans can make a determination as

1003
00:36:21,800 –> 00:36:25,240
to what to do in the future now it’s

1004
00:36:23,760 –> 00:36:26,560
becoming predictive right so it’s

1005
00:36:25,240 –> 00:36:28,160
beginning to tell us hey here’s what I

1006
00:36:26,560 –> 00:36:30,319
think will happen in the future

1007
00:36:28,160 –> 00:36:33,119
or it’s even prescriptive which is here

1008
00:36:30,319 –> 00:36:35,240
is what you should do I as a Systems

1009
00:36:33,119 –> 00:36:38,119
Technology I’m going to tell you as a

1010
00:36:35,240 –> 00:36:40,640
human being what to do and that is a

1011
00:36:38,119 –> 00:36:43,359
very very different relationship right

1012
00:36:40,640 –> 00:36:44,760
um so this notion of what is technology

1013
00:36:43,359 –> 00:36:45,839
and what is human and what is human

1014
00:36:44,760 –> 00:36:48,359
determinant what is technology

1015
00:36:45,839 –> 00:36:50,280
determinant is becoming you know all

1016
00:36:48,359 –> 00:36:51,560
interesed and I think it’s going to make

1017
00:36:50,280 –> 00:36:53,640
a lot of people it has made a lot of

1018
00:36:51,560 –> 00:36:55,599
people very uncomfortable right and you

1019
00:36:53,640 –> 00:36:58,440
know their questions ranging from oh

1020
00:36:55,599 –> 00:37:01,800
will my job be gone will my industry be

1021
00:36:58,440 –> 00:37:04,200
gone you know am I am I teaching my

1022
00:37:01,800 –> 00:37:05,440
children what the next what this what

1023
00:37:04,200 –> 00:37:06,839
their world is going to be like because

1024
00:37:05,440 –> 00:37:09,079
it’s going to be so fundamentally

1025
00:37:06,839 –> 00:37:11,839
different from ours in terms of how they

1026
00:37:09,079 –> 00:37:13,760
learn what they learn why they learn you

1027
00:37:11,839 –> 00:37:16,359
how you will you are teaching them or

1028
00:37:13,760 –> 00:37:18,720
they are teaching you and ideally it

1029
00:37:16,359 –> 00:37:20,760
should be both right because I I have a

1030
00:37:18,720 –> 00:37:22,560
12-y old and a 15y old and I’m learning

1031
00:37:20,760 –> 00:37:24,880
from them constantly right because they

1032
00:37:22,560 –> 00:37:26,560
fundamentally operate differently um

1033
00:37:24,880 –> 00:37:27,720
because they are so used to having this

1034
00:37:26,560 –> 00:37:29,119
infinite amount of knowledge remember

1035
00:37:27,720 –> 00:37:31,040
when I was growing up maybe this dates

1036
00:37:29,119 –> 00:37:33,240
me but we had to go to an encyclopedia

1037
00:37:31,040 –> 00:37:35,000
or a library to gain knowledge right it

1038
00:37:33,240 –> 00:37:36,240
was the early days of the internet and

1039
00:37:35,000 –> 00:37:38,440
it was so exciting when you could

1040
00:37:36,240 –> 00:37:41,440
actually access something um through the

1041
00:37:38,440 –> 00:37:43,040
web our this next Generation even the

1042
00:37:41,440 –> 00:37:45,000
one that’s sort of you know in the

1043
00:37:43,040 –> 00:37:48,520
youngest AG of their career they are

1044
00:37:45,000 –> 00:37:51,760
used to having Limitless access right

1045
00:37:48,520 –> 00:37:54,160
and so they’re instant instant instant

1046
00:37:51,760 –> 00:37:55,560
instant Limitless so it’s the analytics

1047
00:37:54,160 –> 00:37:57,640
that is becoming everything right

1048
00:37:55,560 –> 00:38:00,000
because Gathering the data itself when

1049
00:37:57,640 –> 00:38:01,119
you think about jobs from 25 years ago

1050
00:38:00,000 –> 00:38:03,760
and you were coming out of college you

1051
00:38:01,119 –> 00:38:06,160
would do analyst jobs right you know at

1052
00:38:03,760 –> 00:38:07,560
especially if you you know a smart white

1053
00:38:06,160 –> 00:38:10,440
color worker was interested in doing

1054
00:38:07,560 –> 00:38:12,200
things in technology or Finance or cpg

1055
00:38:10,440 –> 00:38:13,480
you would go and be an analyst and the

1056
00:38:12,200 –> 00:38:14,720
cool thing about being an analyst was

1057
00:38:13,480 –> 00:38:15,560
not only did you learn how to put

1058
00:38:14,720 –> 00:38:16,720
together this information but you

1059
00:38:15,560 –> 00:38:19,079
learned about the companies and the

1060
00:38:16,720 –> 00:38:21,040
industries while you were doing it now

1061
00:38:19,079 –> 00:38:23,520
we don’t need people necessarily to do a

1062
00:38:21,040 –> 00:38:25,560
lot of that right I mean that data can

1063
00:38:23,520 –> 00:38:27,920
be gathered and analyzed by a well

1064
00:38:25,560 –> 00:38:29,280
constructed system but how it is

1065
00:38:27,920 –> 00:38:30,800
utilized at a company how those

1066
00:38:29,280 –> 00:38:33,000
decisions are made have to be human

1067
00:38:30,800 –> 00:38:35,800
determinant and again if a human is not

1068
00:38:33,000 –> 00:38:38,119
in the loop during the creation of that

1069
00:38:35,800 –> 00:38:40,160
data during the management of that data

1070
00:38:38,119 –> 00:38:42,040
during the creation of the analytics and

1071
00:38:40,160 –> 00:38:44,440
applications and tools that are deciding

1072
00:38:42,040 –> 00:38:46,079
then the outputs something very strange

1073
00:38:44,440 –> 00:38:47,359
is going to start to happen right which

1074
00:38:46,079 –> 00:38:50,000
the system is going to make determinants

1075
00:38:47,359 –> 00:38:53,040
of its own and we don’t want

1076
00:38:50,000 –> 00:38:56,640
that yeah yet so many people start

1077
00:38:53,040 –> 00:38:59,520
relying on those systems uh for advice

1078
00:38:56,640 –> 00:39:02,160
sometimes um you know quite uh which can

1079
00:38:59,520 –> 00:39:03,960
have dear consequences yeah no I mean

1080
00:39:02,160 –> 00:39:06,040
look that that’s not new right I mean

1081
00:39:03,960 –> 00:39:07,680
when you’re in a plane today and a pilot

1082
00:39:06,040 –> 00:39:10,160
is relying on systems that are highly

1083
00:39:07,680 –> 00:39:11,720
electronic to keep you alive and safe

1084
00:39:10,160 –> 00:39:15,280
and on your way to you know what would

1085
00:39:11,720 –> 00:39:16,520
be miraculous 50 years ago we we have

1086
00:39:15,280 –> 00:39:19,640
gotten pretty used to doing that right

1087
00:39:16,520 –> 00:39:21,400
we do that in every day of how often do

1088
00:39:19,640 –> 00:39:24,079
we touch our phones right every few

1089
00:39:21,400 –> 00:39:26,440
seconds um we’re constantly relying on

1090
00:39:24,079 –> 00:39:27,960
technology derived information to

1091
00:39:26,440 –> 00:39:29,800
determine where we’re going how we’re

1092
00:39:27,960 –> 00:39:31,599
going what to tell the car what music to

1093
00:39:29,800 –> 00:39:33,040
play what to tell our children how to

1094
00:39:31,599 –> 00:39:34,720
order food like we’re doing it

1095
00:39:33,040 –> 00:39:37,119
constantly and it’s only going to get

1096
00:39:34,720 –> 00:39:38,720
more and more intense right and granted

1097
00:39:37,119 –> 00:39:40,440
that’s not for everyone I grew up in

1098
00:39:38,720 –> 00:39:41,880
India and you know we still have a lot

1099
00:39:40,440 –> 00:39:44,440
of people sitting under the poverty line

1100
00:39:41,880 –> 00:39:46,480
but most of them have a cell phone

1101
00:39:44,440 –> 00:39:48,920
because that is access to knowledge

1102
00:39:46,480 –> 00:39:51,240
right fundamental access to knowledge so

1103
00:39:48,920 –> 00:39:53,000
it it spans the gamut of of human

1104
00:39:51,240 –> 00:39:55,160
population at this point in terms of how

1105
00:39:53,000 –> 00:39:56,599
they access information is beginning to

1106
00:39:55,160 –> 00:39:58,800
become uniform in the sense that they

1107
00:39:56,599 –> 00:40:00,480
all it’s not limited to the rich or the

1108
00:39:58,800 –> 00:40:02,839
powerful or people in a particular

1109
00:40:00,480 –> 00:40:04,240
country a lot of people have access to a

1110
00:40:02,839 –> 00:40:06,359
lot of information as you pointed out

1111
00:40:04,240 –> 00:40:08,280
nearly Limitless right the question now

1112
00:40:06,359 –> 00:40:10,560
becomes is how do we still give them

1113
00:40:08,280 –> 00:40:13,359
things to do that matter right and what

1114
00:40:10,560 –> 00:40:16,359
are those things that are truly human

1115
00:40:13,359 –> 00:40:17,960
only versus what are the things and even

1116
00:40:16,359 –> 00:40:20,280
when I say human only it’s always

1117
00:40:17,960 –> 00:40:22,040
enabled by technology right but what are

1118
00:40:20,280 –> 00:40:24,680
the decisions that specifically should

1119
00:40:22,040 –> 00:40:26,280
not be made by machines and that again

1120
00:40:24,680 –> 00:40:28,520
begins to become there are some that are

1121
00:40:26,280 –> 00:40:29,680
very clear very black white very easy to

1122
00:40:28,520 –> 00:40:31,640
understand some that are much more

1123
00:40:29,680 –> 00:40:33,480
amorphous much more gray much more

1124
00:40:31,640 –> 00:40:35,720
philosophical and that’s where as you

1125
00:40:33,480 –> 00:40:38,359
pointed out governments are talking you

1126
00:40:35,720 –> 00:40:39,599
know NOS are talking uh private

1127
00:40:38,359 –> 00:40:42,680
corporations are talking public

1128
00:40:39,599 –> 00:40:45,200
corporations are talking um um Watchdog

1129
00:40:42,680 –> 00:40:46,880
organizations are keeping an eye out to

1130
00:40:45,200 –> 00:40:48,480
make sure they’re thinking about how

1131
00:40:46,880 –> 00:40:51,400
legislation is created how we’re

1132
00:40:48,480 –> 00:40:54,720
enforcing it but it it’s a whole new

1133
00:40:51,400 –> 00:40:57,079
world of of uh of governance and again I

1134
00:40:54,720 –> 00:40:59,319
think we have to be very careful to use

1135
00:40:57,079 –> 00:41:02,240
that word in a positive sense right

1136
00:40:59,319 –> 00:41:04,720
because it requires good people to work

1137
00:41:02,240 –> 00:41:06,319
hard on things that matter uh for us to

1138
00:41:04,720 –> 00:41:08,160
be a better society and but I

1139
00:41:06,319 –> 00:41:10,200
fundamentally believe technology can do

1140
00:41:08,160 –> 00:41:13,040
that if we all sort of do the right

1141
00:41:10,200 –> 00:41:16,359
thing yeah it’s it’s just the tool we’ve

1142
00:41:13,040 –> 00:41:18,800
created and supposed to serve us but I

1143
00:41:16,359 –> 00:41:22,839
what I’m what worries me is

1144
00:41:18,800 –> 00:41:26,400
that in a way those technologists those

1145
00:41:22,839 –> 00:41:29,920
creators um are trying to Design Systems

1146
00:41:26,400 –> 00:41:34,640
which will do the thinking for us to to

1147
00:41:29,920 –> 00:41:37,640
to like to two wide extent meaning we

1148
00:41:34,640 –> 00:41:40,839
will become lazy we will become we can

1149
00:41:37,640 –> 00:41:43,280
become less creative because yeah all

1150
00:41:40,839 –> 00:41:46,960
the choice will be limited and just

1151
00:41:43,280 –> 00:41:49,040
giving giving to us uh to confume

1152
00:41:46,960 –> 00:41:50,520
um you know there are these two great

1153
00:41:49,040 –> 00:41:52,359
movies that illustrate this point there

1154
00:41:50,520 –> 00:41:53,880
was one made this 15 years ago now

1155
00:41:52,359 –> 00:41:55,240
called idiocracy where someone comes

1156
00:41:53,880 –> 00:41:56,680
from the past into the future and

1157
00:41:55,240 –> 00:41:59,560
everyone’s kind of idiot because they’re

1158
00:41:56,680 –> 00:42:01,040
now relying on the world and Technology

1159
00:41:59,560 –> 00:42:02,520
giving them what they need the other

1160
00:42:01,040 –> 00:42:05,359
movie which I think is fascinating for

1161
00:42:02,520 –> 00:42:06,880
this is w-e the story about the robot

1162
00:42:05,359 –> 00:42:09,359
all the humans are sitting on like

1163
00:42:06,880 –> 00:42:11,200
floating couches and just watching sort

1164
00:42:09,359 –> 00:42:13,480
of media and and and have no real

1165
00:42:11,200 –> 00:42:15,240
curiosity anymore and look that’s a very

1166
00:42:13,480 –> 00:42:17,440
there’s lots of dystopian Futures

1167
00:42:15,240 –> 00:42:18,720
possible Right Where technology takes

1168
00:42:17,440 –> 00:42:21,079
over and does all sorts of strange

1169
00:42:18,720 –> 00:42:22,440
things I mean look in the 50s and 60s we

1170
00:42:21,079 –> 00:42:25,240
were wored that nuclear technology would

1171
00:42:22,440 –> 00:42:27,240
destroy the world right um I so I think

1172
00:42:25,240 –> 00:42:28,480
all revolutions are difficult right we

1173
00:42:27,240 –> 00:42:29,920
have to go through a significant period

1174
00:42:28,480 –> 00:42:31,960
of change and understand what this

1175
00:42:29,920 –> 00:42:33,720
change means and that’s why I don’t

1176
00:42:31,960 –> 00:42:35,640
think it’s enough for us to sit back and

1177
00:42:33,720 –> 00:42:38,000
say oh it’ll figure itself out right

1178
00:42:35,640 –> 00:42:39,760
this is where people um who have

1179
00:42:38,000 –> 00:42:41,720
curiosity and Innovation and care about

1180
00:42:39,760 –> 00:42:43,280
the world have to be sort of aggressive

1181
00:42:41,720 –> 00:42:45,040
about saying we are interested in

1182
00:42:43,280 –> 00:42:47,319
determining what our future will look

1183
00:42:45,040 –> 00:42:48,880
like and I will tell you again you know

1184
00:42:47,319 –> 00:42:50,480
my parents generation Our Generation

1185
00:42:48,880 –> 00:42:53,359
we’ve had it pretty good right since the

1186
00:42:50,480 –> 00:42:55,240
second world war through till now while

1187
00:42:53,359 –> 00:42:57,480
the world has gone through a lot of pain

1188
00:42:55,240 –> 00:43:00,319
less pain less less Global pain the

1189
00:42:57,480 –> 00:43:01,960
generations that preceded it and now we

1190
00:43:00,319 –> 00:43:04,160
have scenarios where you know climate’s

1191
00:43:01,960 –> 00:43:05,839
a very real concern and should be a

1192
00:43:04,160 –> 00:43:07,440
highly real concern for us I do some

1193
00:43:05,839 –> 00:43:10,440
work in that space too which I think is

1194
00:43:07,440 –> 00:43:12,400
very very important um and and and then

1195
00:43:10,440 –> 00:43:14,559
there’s this technology Revolution that

1196
00:43:12,400 –> 00:43:17,160
is changing everything about how the

1197
00:43:14,559 –> 00:43:18,760
Haves and the Have Nots live right and

1198
00:43:17,160 –> 00:43:19,880
again there’s lots of social you could

1199
00:43:18,760 –> 00:43:21,280
you know you could spend an hour just

1200
00:43:19,880 –> 00:43:24,000
talking about the social sort of

1201
00:43:21,280 –> 00:43:25,920
consequences of what this does in terms

1202
00:43:24,000 –> 00:43:28,640
of the creation of wealth and certain

1203
00:43:25,920 –> 00:43:30,680
sort of certain demographics versus not

1204
00:43:28,640 –> 00:43:31,880
in others sort of the geopolitical

1205
00:43:30,680 –> 00:43:33,680
implications of what it is that we’re

1206
00:43:31,880 –> 00:43:34,800
going through but I think in the end we

1207
00:43:33,680 –> 00:43:37,440
have to think about what we can do

1208
00:43:34,800 –> 00:43:39,599
personally right and how we can create

1209
00:43:37,440 –> 00:43:42,000
culture in our professional lives in our

1210
00:43:39,599 –> 00:43:44,040
personal lives how we can educate those

1211
00:43:42,000 –> 00:43:46,400
that need education how we can uplift

1212
00:43:44,040 –> 00:43:49,040
people and I fundamentally believe we

1213
00:43:46,400 –> 00:43:51,119
can uplift everyone right I mean we have

1214
00:43:49,040 –> 00:43:52,640
to believe that and it’s not what

1215
00:43:51,119 –> 00:43:55,040
everyone thinks and some people are very

1216
00:43:52,640 –> 00:43:56,839
direct about that you know that they are

1217
00:43:55,040 –> 00:43:58,079
more mercenary about saying you know

1218
00:43:56,839 –> 00:44:00,119
these people can be educated these

1219
00:43:58,079 –> 00:44:01,599
people cannot I don’t I don’t believe

1220
00:44:00,119 –> 00:44:02,960
that I think everyone can be educated in

1221
00:44:01,599 –> 00:44:04,440
certain ways now that doesn’t mean I

1222
00:44:02,960 –> 00:44:06,480
don’t think teams have to be changed or

1223
00:44:04,440 –> 00:44:07,760
reorganized I think they do but I think

1224
00:44:06,480 –> 00:44:09,480
we can do it in a way that is

1225
00:44:07,760 –> 00:44:11,240
fundamentally human especially when we

1226
00:44:09,480 –> 00:44:12,839
are dealing with situations that are

1227
00:44:11,240 –> 00:44:16,200
very very technology driven to your

1228
00:44:12,839 –> 00:44:18,119
point we have to create a safe space for

1229
00:44:16,200 –> 00:44:20,160
that sort of the human permeating the

1230
00:44:18,119 –> 00:44:22,000
technology to allow the technology to be

1231
00:44:20,160 –> 00:44:23,640
utilized to its full potential in a way

1232
00:44:22,000 –> 00:44:26,599
that is safe for us as a

1233
00:44:23,640 –> 00:44:29,599
people and we can do it finally at scale

1234
00:44:26,599 –> 00:44:31,599
because it can be personalized of course

1235
00:44:29,599 –> 00:44:34,559
this whole yeah I mean the notion of of

1236
00:44:31,599 –> 00:44:36,920
of this one this many to many interface

1237
00:44:34,559 –> 00:44:39,319
in the world today is it exists right I

1238
00:44:36,920 –> 00:44:40,920
mean the internet exists and um it’s not

1239
00:44:39,319 –> 00:44:42,760
just when I say the internet I’m I’m

1240
00:44:40,920 –> 00:44:45,400
using a broad term for it it’s all the

1241
00:44:42,760 –> 00:44:48,319
ways that we sort of sort of relate to

1242
00:44:45,400 –> 00:44:50,160
technology right I remember you know

1243
00:44:48,319 –> 00:44:51,960
reading early books or watching early

1244
00:44:50,160 –> 00:44:54,119
movies about the notion of the AI in

1245
00:44:51,960 –> 00:44:56,040
your year right that one day that’s all

1246
00:44:54,119 –> 00:44:57,880
you will need you you you’ll be talking

1247
00:44:56,040 –> 00:44:58,680
to something and

1248
00:44:57,880 –> 00:45:02,319
um

1249
00:44:58,680 –> 00:45:04,440
and the the system the the the many

1250
00:45:02,319 –> 00:45:05,720
words for it Avatar Etc is going to tell

1251
00:45:04,440 –> 00:45:07,040
you what you need to know right you

1252
00:45:05,720 –> 00:45:08,559
don’t have to access anything you don’t

1253
00:45:07,040 –> 00:45:10,680
have to type anything you will just have

1254
00:45:08,559 –> 00:45:13,200
to ask or think here’s what I need to

1255
00:45:10,680 –> 00:45:14,839
know and it’s available to me so then

1256
00:45:13,200 –> 00:45:17,640
what are we doing sort of what are we

1257
00:45:14,839 –> 00:45:19,920
responsible for what are we and and and

1258
00:45:17,640 –> 00:45:21,599
again again philosophical and social

1259
00:45:19,920 –> 00:45:23,319
questions aside about who controls the

1260
00:45:21,599 –> 00:45:25,000
machines right I mean those are very

1261
00:45:23,319 –> 00:45:27,160
real questions is it going to be the

1262
00:45:25,000 –> 00:45:30,480
technologists who become sort of you

1263
00:45:27,160 –> 00:45:33,079
know not to use a a poorly poorly used

1264
00:45:30,480 –> 00:45:34,960
word in in in Indian history but sort of

1265
00:45:33,079 –> 00:45:37,160
a cast of technologists who will control

1266
00:45:34,960 –> 00:45:38,800
the future to some degree that’s

1267
00:45:37,160 –> 00:45:40,520
happened right I mean when you think

1268
00:45:38,800 –> 00:45:41,920
about companies that are changing the

1269
00:45:40,520 –> 00:45:43,200
world today primarily there are

1270
00:45:41,920 –> 00:45:46,079
technology companies that are creating

1271
00:45:43,200 –> 00:45:48,000
the most impact right yes um and and are

1272
00:45:46,079 –> 00:45:49,400
impacting every industry and you know

1273
00:45:48,000 –> 00:45:51,480
when I remember when I first came into

1274
00:45:49,400 –> 00:45:54,440
my first set of CDA rols you know it

1275
00:45:51,480 –> 00:45:57,800
used to be digital media and advertising

1276
00:45:54,440 –> 00:46:00,640
and marketing and um uh technology and

1277
00:45:57,800 –> 00:46:02,359
uh and even cpg retail to some degree

1278
00:46:00,640 –> 00:46:04,040
that were kind of you know doing this

1279
00:46:02,359 –> 00:46:05,119
now it’s everyone right it doesn’t

1280
00:46:04,040 –> 00:46:07,440
matter whether you’re manufacturing

1281
00:46:05,119 –> 00:46:09,440
something or mining ion ore you are

1282
00:46:07,440 –> 00:46:10,800
using technology in a fundamentally

1283
00:46:09,440 –> 00:46:13,760
different way than you used five years

1284
00:46:10,800 –> 00:46:15,119
ago or 10 years ago it is becoming I

1285
00:46:13,760 –> 00:46:16,359
hesitate to say that every company is a

1286
00:46:15,119 –> 00:46:18,559
technology company every company is not

1287
00:46:16,359 –> 00:46:20,680
a technology company but every company

1288
00:46:18,559 –> 00:46:22,720
utilizes technology and digital

1289
00:46:20,680 –> 00:46:24,079
technology or they should be otherwise

1290
00:46:22,720 –> 00:46:26,400
they’re going to fall behind their their

1291
00:46:24,079 –> 00:46:27,880
competitors in the space so um and

1292
00:46:26,400 –> 00:46:29,119
governments doing the same thing

1293
00:46:27,880 –> 00:46:32,720
educational institutions are doing the

1294
00:46:29,119 –> 00:46:34,559
same thing and and they have to right I

1295
00:46:32,720 –> 00:46:35,960
I think a lot about obviously as any

1296
00:46:34,559 –> 00:46:37,440
parent does about how you how do you

1297
00:46:35,960 –> 00:46:41,720
educate your children what do you tell

1298
00:46:37,440 –> 00:46:43,480
them to do and and for me it’s it’s I

1299
00:46:41,720 –> 00:46:46,200
have strongly focused with my children

1300
00:46:43,480 –> 00:46:48,040
on how to understand how people operate

1301
00:46:46,200 –> 00:46:49,680
right like what does that look like your

1302
00:46:48,040 –> 00:46:51,720
friends your organizations the things

1303
00:46:49,680 –> 00:46:53,440
you compete in your Athletics it’s about

1304
00:46:51,720 –> 00:46:55,319
people so think about that and the

1305
00:46:53,440 –> 00:46:57,839
second part is not just how do you

1306
00:46:55,319 –> 00:47:00,200
access knowledge anymore but how are you

1307
00:46:57,839 –> 00:47:02,640
analyzing information right for some

1308
00:47:00,200 –> 00:47:03,920
utility it because the power right now I

1309
00:47:02,640 –> 00:47:05,920
remember I grew up in India where

1310
00:47:03,920 –> 00:47:07,760
schools were we had to learn a 100,000

1311
00:47:05,920 –> 00:47:09,240
formula for physics and 100,000 formula

1312
00:47:07,760 –> 00:47:10,800
for math you’re not allowed to use a

1313
00:47:09,240 –> 00:47:12,720
calculator and I’ll tell you it gave you

1314
00:47:10,800 –> 00:47:14,319
a great basis for being a good scientist

1315
00:47:12,720 –> 00:47:16,160
or a good engineer but in a lot of ways

1316
00:47:14,319 –> 00:47:17,960
it didn’t teach you how to survive in an

1317
00:47:16,160 –> 00:47:18,960
environment where the human connectivity

1318
00:47:17,960 –> 00:47:21,079
is going to become increasingly

1319
00:47:18,960 –> 00:47:22,440
important yeah and as you grow in your

1320
00:47:21,079 –> 00:47:25,160
career you will find that you’ll be

1321
00:47:22,440 –> 00:47:26,920
spending more time with people than less

1322
00:47:25,160 –> 00:47:28,480
right maybe fewer people and maybe

1323
00:47:26,920 –> 00:47:31,119
people who make more decisions but in

1324
00:47:28,480 –> 00:47:33,440
the end that human interaction becomes

1325
00:47:31,119 –> 00:47:35,800
as much part of your job as it was

1326
00:47:33,440 –> 00:47:38,079
earlier in the day just a different

1327
00:47:35,800 –> 00:47:41,839
kind

1328
00:47:38,079 –> 00:47:44,920
H I read the other day I don’t know if

1329
00:47:41,839 –> 00:47:48,760
it was already it is already a legisl

1330
00:47:44,920 –> 00:47:50,280
legislation or it’s just a project that

1331
00:47:48,760 –> 00:47:55,599
um there is

1332
00:47:50,280 –> 00:47:58,200
a like uh there was an idea to limit um

1333
00:47:55,599 –> 00:48:03,160
consumption of of social media and and

1334
00:47:58,200 –> 00:48:06,480
protect youth um yeah cuz even I

1335
00:48:03,160 –> 00:48:09,520
remember my childhood without a phone

1336
00:48:06,480 –> 00:48:12,160
without yeah being constantly like it is

1337
00:48:09,520 –> 00:48:14,680
an addiction um and what you see now I

1338
00:48:12,160 –> 00:48:18,440
don’t know how you do it with your

1339
00:48:14,680 –> 00:48:21,040
children but um it feels like they are

1340
00:48:18,440 –> 00:48:24,520
being sucked into it and and they are

1341
00:48:21,040 –> 00:48:27,599
too young to understand um how to fight

1342
00:48:24,520 –> 00:48:29,280
with it how to use it responsibly

1343
00:48:27,599 –> 00:48:33,319
yeah look I think this is an impossible

1344
00:48:29,280 –> 00:48:35,800
problem to solve right it is um it is a

1345
00:48:33,319 –> 00:48:37,559
moment of dramatic change it is a moment

1346
00:48:35,800 –> 00:48:39,160
when you’re absolutely right I think

1347
00:48:37,559 –> 00:48:41,640
social media has overwhelmed a lot of

1348
00:48:39,160 –> 00:48:44,000
children and um I’ve certainly seen it

1349
00:48:41,640 –> 00:48:46,640
in my own children um and we’ve tried as

1350
00:48:44,000 –> 00:48:48,200
parents to to make the best trade-offs

1351
00:48:46,640 –> 00:48:50,240
possible but we’ve made mistakes along

1352
00:48:48,200 –> 00:48:52,040
the way I mean I think we all do and

1353
00:48:50,240 –> 00:48:54,799
we’ve had to optimize and I think that

1354
00:48:52,040 –> 00:48:57,079
notion of experimenting in optimization

1355
00:48:54,799 –> 00:48:59,160
is going to be the way right and there

1356
00:48:57,079 –> 00:49:02,760
will be experiments in States in

1357
00:48:59,160 –> 00:49:04,680
countries in in continents um around how

1358
00:49:02,760 –> 00:49:05,799
to manage this right I mean China does

1359
00:49:04,680 –> 00:49:07,440
it very different from Europe Europe

1360
00:49:05,799 –> 00:49:09,040
does it very different from the US even

1361
00:49:07,440 –> 00:49:10,799
in the US there are states that do very

1362
00:49:09,040 –> 00:49:12,520
fundamentally different from each other

1363
00:49:10,799 –> 00:49:14,000
because of you know political views or

1364
00:49:12,520 –> 00:49:16,880
personal views or the views of the

1365
00:49:14,000 –> 00:49:18,400
legislators of that state and we’re

1366
00:49:16,880 –> 00:49:19,799
going to figure it out one way or the

1367
00:49:18,400 –> 00:49:20,960
other and there will be some mistakes

1368
00:49:19,799 –> 00:49:22,119
along the way there’ll probably be a lot

1369
00:49:20,960 –> 00:49:24,559
of mistakes along the way but that’s

1370
00:49:22,119 –> 00:49:25,799
true with any new technology right um

1371
00:49:24,559 –> 00:49:28,079
but as you pointed out this is a

1372
00:49:25,799 –> 00:49:30,440
technology that’s fundament m l

1373
00:49:28,079 –> 00:49:33,480
reshaping sort of the human world in a

1374
00:49:30,440 –> 00:49:35,280
very very real way and uh as with

1375
00:49:33,480 –> 00:49:37,079
anything like that I think we have to be

1376
00:49:35,280 –> 00:49:39,119
cautious and we have to be careful and

1377
00:49:37,079 –> 00:49:41,200
we have to do the work we have to do the

1378
00:49:39,119 –> 00:49:42,880
problem is in this particular scenario

1379
00:49:41,200 –> 00:49:45,880
if we wait too long to do that it’s

1380
00:49:42,880 –> 00:49:47,240
already evolved to the next stage um and

1381
00:49:45,880 –> 00:49:50,480
you know our children have a lot of

1382
00:49:47,240 –> 00:49:52,920
access um um in the US there there’s a

1383
00:49:50,480 –> 00:49:54,319
ton of privilege um and there’s you

1384
00:49:52,920 –> 00:49:55,760
you’re beginning to see the differential

1385
00:49:54,319 –> 00:49:57,720
between folks who have access to more

1386
00:49:55,760 –> 00:50:00,079
knowledge earlier on and folks who do

1387
00:49:57,720 –> 00:50:01,920
not and and you know as a technologist

1388
00:50:00,079 –> 00:50:03,400
myself I had to really struggle early on

1389
00:50:01,920 –> 00:50:05,760
with not allowing my children to have

1390
00:50:03,400 –> 00:50:06,880
access to this technology and you know I

1391
00:50:05,760 –> 00:50:08,839
made some mistakes along the way gave

1392
00:50:06,880 –> 00:50:12,200
them access to early pulled it back

1393
00:50:08,839 –> 00:50:15,040
right and then we had Co and for two

1394
00:50:12,200 –> 00:50:17,520
years all the rules we built around not

1395
00:50:15,040 –> 00:50:19,440
giving our children access to was

1396
00:50:17,520 –> 00:50:20,440
eliminated because it was the only way

1397
00:50:19,440 –> 00:50:22,640
they could communicate with their

1398
00:50:20,440 –> 00:50:24,520
friends and their family and we had no

1399
00:50:22,640 –> 00:50:27,319
choice right and children came out of

1400
00:50:24,520 –> 00:50:28,720
that changed I saw it we all saw it yeah

1401
00:50:27,319 –> 00:50:30,440
um and and one of the nice things was

1402
00:50:28,720 –> 00:50:32,040
they came out sort of hungry for for

1403
00:50:30,440 –> 00:50:35,079
human connection and contact and that

1404
00:50:32,040 –> 00:50:36,599
was great but also more dependent on

1405
00:50:35,079 –> 00:50:38,000
digital and Technology than they

1406
00:50:36,599 –> 00:50:41,079
probably would have been if we didn’t go

1407
00:50:38,000 –> 00:50:43,040
through that terrible event right so um

1408
00:50:41,079 –> 00:50:44,359
I think that accelerated many things as

1409
00:50:43,040 –> 00:50:46,280
we talked about at the beginning of this

1410
00:50:44,359 –> 00:50:48,240
conversation and it changed the way

1411
00:50:46,280 –> 00:50:50,440
people behave some of those behaviors

1412
00:50:48,240 –> 00:50:52,040
are going back some of them will not but

1413
00:50:50,440 –> 00:50:54,000
you know this is like Pandora’s Box

1414
00:50:52,040 –> 00:50:55,760
there’s no putting this back in it’s a

1415
00:50:54,000 –> 00:50:57,920
question of how do we manage it now that

1416
00:50:55,760 –> 00:50:59,920
it’s out in a way that is best for

1417
00:50:57,920 –> 00:51:01,559
society again I I’ll go back to that

1418
00:50:59,920 –> 00:51:03,319
best for society thing because I think

1419
00:51:01,559 –> 00:51:06,200
technologists absolutely have a

1420
00:51:03,319 –> 00:51:09,079
responsibility to be thinking about

1421
00:51:06,200 –> 00:51:13,680
that yeah and and right now with the

1422
00:51:09,079 –> 00:51:17,079
whole personalization and the real time

1423
00:51:13,680 –> 00:51:20,359
um you know context and and information

1424
00:51:17,079 –> 00:51:22,559
um Gathering and insights it’s even like

1425
00:51:20,359 –> 00:51:27,160
in terms of if we are thinking about the

1426
00:51:22,559 –> 00:51:30,319
aspect of Education um it’s it’s going

1427
00:51:27,160 –> 00:51:35,160
to be more Pro like it’s going to be

1428
00:51:30,319 –> 00:51:39,280
more um present in in not only children

1429
00:51:35,160 –> 00:51:41,000
but particularly children um uh

1430
00:51:39,280 –> 00:51:43,839
environment

1431
00:51:41,000 –> 00:51:48,640
so I guess

1432
00:51:43,839 –> 00:51:52,760
yes like we need human uh human um

1433
00:51:48,640 –> 00:51:54,160
relationships and and being in within

1434
00:51:52,760 –> 00:51:58,440
within others

1435
00:51:54,160 –> 00:52:00,640
but it will just be much easier to to

1436
00:51:58,440 –> 00:52:04,040
learn H

1437
00:52:00,640 –> 00:52:06,480
and discover new things I guess through

1438
00:52:04,040 –> 00:52:09,440
asking you what I’m trying to get into

1439
00:52:06,480 –> 00:52:11,319
is assistance AI assistance right like

1440
00:52:09,440 –> 00:52:13,079
the whole new if I mean if I knew the

1441
00:52:11,319 –> 00:52:15,280
answer to that I’d probably be a lot

1442
00:52:13,079 –> 00:52:16,760
richer than I am today right I it’s it’s

1443
00:52:15,280 –> 00:52:18,000
one of those things where I don’t I

1444
00:52:16,760 –> 00:52:21,240
don’t know that it’s been figured out

1445
00:52:18,000 –> 00:52:22,760
yet there’s a lot of you know a lot of

1446
00:52:21,240 –> 00:52:24,839
but but like the Facebooks and the

1447
00:52:22,760 –> 00:52:26,760
Googles and the metas and the Instagrams

1448
00:52:24,839 –> 00:52:29,040
and the WhatsApp there will be new Vari

1449
00:52:26,760 –> 00:52:31,799
of these new tools right and maybe one

1450
00:52:29,040 –> 00:52:34,119
of them one day will be sort of the you

1451
00:52:31,799 –> 00:52:35,640
know the the information God in your

1452
00:52:34,119 –> 00:52:37,720
head that tells you everything you need

1453
00:52:35,640 –> 00:52:39,799
to know um I mean look people have been

1454
00:52:37,720 –> 00:52:42,079
trying to do this for decades sort of be

1455
00:52:39,799 –> 00:52:44,400
that that one source of information and

1456
00:52:42,079 –> 00:52:45,839
it’s a very powerful thing right and how

1457
00:52:44,400 –> 00:52:47,680
governments will actually react to that

1458
00:52:45,839 –> 00:52:49,160
is going to be interesting to watch and

1459
00:52:47,680 –> 00:52:50,760
there will be more tension I

1460
00:52:49,160 –> 00:52:53,480
fundamentally believe between private

1461
00:52:50,760 –> 00:52:54,400
corporations and governments because um

1462
00:52:53,480 –> 00:52:56,160
you know the incentives are

1463
00:52:54,400 –> 00:52:57,720
fundamentally different in some cases

1464
00:52:56,160 –> 00:52:59,240
course I mean you’re you’re you’re

1465
00:52:57,720 –> 00:53:01,319
beholden to your shareholders versus

1466
00:52:59,240 –> 00:53:02,799
you’re beholden to your citizenry and

1467
00:53:01,319 –> 00:53:04,680
then are you a citizen of the world how

1468
00:53:02,799 –> 00:53:06,559
do you think about that and and but in

1469
00:53:04,680 –> 00:53:07,920
the end I’m going to care most about my

1470
00:53:06,559 –> 00:53:09,680
family and the people I love and the

1471
00:53:07,920 –> 00:53:11,960
ones who depend on me so how do you

1472
00:53:09,680 –> 00:53:13,480
manage all those boundaries and look

1473
00:53:11,960 –> 00:53:15,240
that’s the Human Condition right we’ve

1474
00:53:13,480 –> 00:53:17,400
been doing this ever since we were sort

1475
00:53:15,240 –> 00:53:20,160
of you know using rocks to kill animals

1476
00:53:17,400 –> 00:53:22,040
tens of thousands of years ago so um how

1477
00:53:20,160 –> 00:53:23,400
we continue to evolve as Society I think

1478
00:53:22,040 –> 00:53:25,240
will be as you pointed out heavily

1479
00:53:23,400 –> 00:53:28,400
influenced by how technology enables us

1480
00:53:25,240 –> 00:53:31,359
to be but the end you know if if a child

1481
00:53:28,400 –> 00:53:32,640
behaves badly it’s partially the child

1482
00:53:31,359 –> 00:53:34,200
but it’s also the parents and the

1483
00:53:32,640 –> 00:53:36,280
community and the village in which they

1484
00:53:34,200 –> 00:53:37,720
were were raised and and so again it’s

1485
00:53:36,280 –> 00:53:40,599
about creating as we’ve talked about

1486
00:53:37,720 –> 00:53:42,720
earlier the right sort of

1487
00:53:40,599 –> 00:53:44,119
universally agreed upon ethical

1488
00:53:42,720 –> 00:53:45,640
principles as to how we use these

1489
00:53:44,119 –> 00:53:47,119
Technologies now there will always be

1490
00:53:45,640 –> 00:53:50,280
bad actors there will always be people

1491
00:53:47,119 –> 00:53:52,400
who try to you know gain profit or or or

1492
00:53:50,280 –> 00:53:53,720
or or do things in a malicious way

1493
00:53:52,400 –> 00:53:56,440
because it gives them an advantage in

1494
00:53:53,720 –> 00:53:58,559
some ways but I fundamentally am an

1495
00:53:56,440 –> 00:54:00,680
Optimist I believe in the power of The

1496
00:53:58,559 –> 00:54:02,559
Human Condition and I believe that there

1497
00:54:00,680 –> 00:54:04,960
are more people focused on doing good

1498
00:54:02,559 –> 00:54:07,040
for society than not and so it’s

1499
00:54:04,960 –> 00:54:08,240
dependent even more dependent on us now

1500
00:54:07,040 –> 00:54:10,280
especially if we live in one of these

1501
00:54:08,240 –> 00:54:12,680
worlds to be thinking about Frameworks

1502
00:54:10,280 –> 00:54:14,680
and ways and education policies to allow

1503
00:54:12,680 –> 00:54:17,720
the stuff to happen the right way and it

1504
00:54:14,680 –> 00:54:19,440
matters who you vote for it matters um

1505
00:54:17,720 –> 00:54:21,200
how you give feedback back to the people

1506
00:54:19,440 –> 00:54:24,079
that you work for it matters how you

1507
00:54:21,200 –> 00:54:25,440
treat the people who work for you um and

1508
00:54:24,079 –> 00:54:27,400
again that’s just things that you teach

1509
00:54:25,440 –> 00:54:29,839
your children every day and or should

1510
00:54:27,400 –> 00:54:32,400
right about how to behave in in in in in

1511
00:54:29,839 –> 00:54:34,680
in society it’s the same thing um I

1512
00:54:32,400 –> 00:54:36,640
don’t think the fundamental rules change

1513
00:54:34,680 –> 00:54:39,359
I think the tools we have and the access

1514
00:54:36,640 –> 00:54:41,559
we have changes but again it comes back

1515
00:54:39,359 –> 00:54:44,280
to what do you believe your values and

1516
00:54:41,559 –> 00:54:46,040
principles are right and are we are we

1517
00:54:44,280 –> 00:54:48,440
are we more ready to agree on those

1518
00:54:46,040 –> 00:54:50,359
things than disagree and then we can

1519
00:54:48,440 –> 00:54:52,799
find ways to apply them to

1520
00:54:50,359 –> 00:54:56,880
technology and you said that you are

1521
00:54:52,799 –> 00:54:58,920
Optimist like I also do feel it’s

1522
00:54:56,880 –> 00:55:01,440
like mainly mainly good what what’s

1523
00:54:58,920 –> 00:55:04,880
happening and and the things we are

1524
00:55:01,440 –> 00:55:08,280
creating um but what are is what are the

1525
00:55:04,880 –> 00:55:11,599
particular aspects of technology or and

1526
00:55:08,280 –> 00:55:17,160
areas um which you probably advise or

1527
00:55:11,599 –> 00:55:19,920
work on uh which you would love to um

1528
00:55:17,160 –> 00:55:21,680
you know for other people to to put more

1529
00:55:19,920 –> 00:55:24,319
attention

1530
00:55:21,680 –> 00:55:25,599
to luckily for me luckily or unluckily

1531
00:55:24,319 –> 00:55:26,880
the things that I operate in are getting

1532
00:55:25,599 –> 00:55:28,480
a lot of attention in fact they’re

1533
00:55:26,880 –> 00:55:31,480
getting too much attention some might

1534
00:55:28,480 –> 00:55:33,440
argue right um um I mean if you’re in

1535
00:55:31,480 –> 00:55:35,160
the AI world if you’re in the analytics

1536
00:55:33,440 –> 00:55:36,760
world if you’re in the technology world

1537
00:55:35,160 –> 00:55:38,720
it’s all anyone’s talking about today

1538
00:55:36,760 –> 00:55:40,119
right because either in fear because

1539
00:55:38,720 –> 00:55:41,280
they’re worried you know they do

1540
00:55:40,119 –> 00:55:42,720
something very manual and they’re

1541
00:55:41,280 –> 00:55:43,880
worried that that thing might go away

1542
00:55:42,720 –> 00:55:45,720
something that they learned for the last

1543
00:55:43,880 –> 00:55:48,240
30 years 20 years 10 years five years is

1544
00:55:45,720 –> 00:55:49,440
not applicable anymore um and so they’re

1545
00:55:48,240 –> 00:55:51,599
trying to understand what that looks

1546
00:55:49,440 –> 00:55:53,440
like or they are part of this milu who

1547
00:55:51,599 –> 00:55:55,920
is setting principles and standards and

1548
00:55:53,440 –> 00:55:58,520
stages for for companies or governments

1549
00:55:55,920 –> 00:55:59,880
or people or or or organizations and you

1550
00:55:58,520 –> 00:56:01,880
know we’re getting to make a lot of

1551
00:55:59,880 –> 00:56:03,880
decisions with longlasting

1552
00:56:01,880 –> 00:56:05,599
consequences but again I I think it’s

1553
00:56:03,880 –> 00:56:07,359
very hard for one person to do it

1554
00:56:05,599 –> 00:56:10,240
anymore right it has to be part of an

1555
00:56:07,359 –> 00:56:12,680
ecosystem as to how that is managed um

1556
00:56:10,240 –> 00:56:14,599
and and sort of making sure that we can

1557
00:56:12,680 –> 00:56:17,599
continue to build that in the right way

1558
00:56:14,599 –> 00:56:19,640
is important I think Technologies like

1559
00:56:17,599 –> 00:56:20,920
sort of the interface between human and

1560
00:56:19,640 –> 00:56:23,119
analytics is going to become very

1561
00:56:20,920 –> 00:56:24,400
important right uh so not just the

1562
00:56:23,119 –> 00:56:27,280
technology that builds the analytics

1563
00:56:24,400 –> 00:56:29,559
tools but the translation layer between

1564
00:56:27,280 –> 00:56:31,720
that and us right and whether that’s

1565
00:56:29,559 –> 00:56:34,079
again the bug in New Year or reports or

1566
00:56:31,720 –> 00:56:35,920
visuals or sort of new applications that

1567
00:56:34,079 –> 00:56:38,319
we’re now using to communicate with the

1568
00:56:35,920 –> 00:56:40,119
world and how do we express ourselves

1569
00:56:38,319 –> 00:56:41,640
that layer is going to become very very

1570
00:56:40,119 –> 00:56:43,319
important because to your point that

1571
00:56:41,640 –> 00:56:46,119
layer is going to become reality to some

1572
00:56:43,319 –> 00:56:47,760
degree right um one of my favorite books

1573
00:56:46,119 –> 00:56:49,680
ever is a book called snow crash written

1574
00:56:47,760 –> 00:56:50,920
by a guy named Neil Stenson and it was

1575
00:56:49,680 –> 00:56:52,520
written a long time ago it was very

1576
00:56:50,920 –> 00:56:55,359
early talked about the early days of

1577
00:56:52,520 –> 00:56:57,119
cyber and you know it it it you know

1578
00:56:55,359 –> 00:56:58,640
originated the term and cyber and it

1579
00:56:57,119 –> 00:57:00,680
talked a lot about sort of this The

1580
00:56:58,640 –> 00:57:02,920
Duality of the world that will exist

1581
00:57:00,680 –> 00:57:05,319
when a digital twin of the world in is

1582
00:57:02,920 –> 00:57:07,200
in place right yeah and what is language

1583
00:57:05,319 –> 00:57:08,480
and what is communication and suddenly

1584
00:57:07,200 –> 00:57:10,039
it becomes all these high fluing ideas

1585
00:57:08,480 –> 00:57:11,960
there almost too much to contain in one

1586
00:57:10,039 –> 00:57:14,440
brain but I think you got to you got to

1587
00:57:11,960 –> 00:57:17,160
pick a piece that you know you can have

1588
00:57:14,440 –> 00:57:18,960
impact on right and that and you know

1589
00:57:17,160 –> 00:57:20,680
and and usually you have impact on many

1590
00:57:18,960 –> 00:57:22,000
pieces your family the people who work

1591
00:57:20,680 –> 00:57:24,400
with you the people who work for you the

1592
00:57:22,000 –> 00:57:25,760
people work for the other organizations

1593
00:57:24,400 –> 00:57:27,960
you spend your time in the hobbies that

1594
00:57:25,760 –> 00:57:30,039
you spend your time in I’m a passionate

1595
00:57:27,960 –> 00:57:31,440
car guy and racing guy and we have a

1596
00:57:30,039 –> 00:57:33,920
really rich Community here in the

1597
00:57:31,440 –> 00:57:35,240
Northeast us and you know sort of how

1598
00:57:33,920 –> 00:57:36,480
you go out there and present yourself

1599
00:57:35,240 –> 00:57:38,400
and talk about the things that matter to

1600
00:57:36,480 –> 00:57:40,799
you and the evolution of that world is

1601
00:57:38,400 –> 00:57:42,520
important and so finding time finding

1602
00:57:40,799 –> 00:57:44,240
balance for all those things I think is

1603
00:57:42,520 –> 00:57:45,200
going to become very very important and

1604
00:57:44,240 –> 00:57:47,359
you know some people have different

1605
00:57:45,200 –> 00:57:49,440
ideas of what balance looks like I like

1606
00:57:47,359 –> 00:57:51,480
True Balance um you know balance between

1607
00:57:49,440 –> 00:57:53,359
family and time for yourself and and and

1608
00:57:51,480 –> 00:57:55,160
then deep professional satisfaction from

1609
00:57:53,359 –> 00:57:56,480
the things that you do and I hope most

1610
00:57:55,160 –> 00:57:59,520
people have that opportunity I think

1611
00:57:56,480 –> 00:58:01,200
it’s I’ve been very lucky was it some

1612
00:57:59,520 –> 00:58:05,240
like actually that was my next question

1613
00:58:01,200 –> 00:58:09,240
so perfectly you spped into it so was it

1614
00:58:05,240 –> 00:58:12,359
something you seen among your family or

1615
00:58:09,240 –> 00:58:15,000
you something which you had to um mature

1616
00:58:12,359 –> 00:58:19,240
and understand that you know family and

1617
00:58:15,000 –> 00:58:21,079
time off of work um matters and not

1618
00:58:19,240 –> 00:58:23,920
everything I think it’s always both I

1619
00:58:21,079 –> 00:58:26,079
mean I have an amazing family very

1620
00:58:23,920 –> 00:58:27,480
educated very they believe that

1621
00:58:26,079 –> 00:58:29,119
education is the most important thing

1622
00:58:27,480 –> 00:58:32,000
that you can do and that you can support

1623
00:58:29,119 –> 00:58:34,000
as the family um I’m very I’m very close

1624
00:58:32,000 –> 00:58:35,839
to them you know they my mother’s an

1625
00:58:34,000 –> 00:58:38,200
architect my father is a cardiothoracic

1626
00:58:35,839 –> 00:58:40,039
surgeon my grandfather was a general in

1627
00:58:38,200 –> 00:58:41,839
the Indian army and also a doctor my

1628
00:58:40,039 –> 00:58:43,200
other grandfather was um an

1629
00:58:41,839 –> 00:58:44,799
industrialist who worked for a group

1630
00:58:43,200 –> 00:58:46,520
called The tatas for many many years and

1631
00:58:44,799 –> 00:58:49,000
taught me everything I ever wanted to

1632
00:58:46,520 –> 00:58:50,720
know about integrity so I had an amazing

1633
00:58:49,000 –> 00:58:52,640
amount of support growing up I went to a

1634
00:58:50,720 –> 00:58:54,319
great school I went to a great College I

1635
00:58:52,640 –> 00:58:56,680
was very blessed in that not everybody

1636
00:58:54,319 –> 00:58:58,480
has those opportunities right and I

1637
00:58:56,680 –> 00:59:00,160
recognize that there’s that creates

1638
00:58:58,480 –> 00:59:01,680
differentials and you know I think my

1639
00:59:00,160 –> 00:59:03,480
children have a lot of those Privileges

1640
00:59:01,680 –> 00:59:06,079
and opportunities too right they go to

1641
00:59:03,480 –> 00:59:07,960
Great Schools they get a lot of support

1642
00:59:06,079 –> 00:59:10,039
um um they have a strong family to

1643
00:59:07,960 –> 00:59:11,680
support them that doesn’t always happen

1644
00:59:10,039 –> 00:59:12,559
and look it doesn’t mean that these

1645
00:59:11,680 –> 00:59:14,920
children are going to be the most

1646
00:59:12,559 –> 00:59:17,920
successful right sometimes hunger is

1647
00:59:14,920 –> 00:59:21,200
what gives you success right I on not

1648
00:59:17,920 –> 00:59:23,559
having is what gives you success but I I

1649
00:59:21,200 –> 00:59:26,599
I and so I I don’t know that there’s a

1650
00:59:23,559 –> 00:59:29,079
formula for for happiness right but I

1651
00:59:26,599 –> 00:59:30,799
think a lot of it is to your point how

1652
00:59:29,079 –> 00:59:33,119
you are raised and who raises you and

1653
00:59:30,799 –> 00:59:34,960
then the other part is sort of what does

1654
00:59:33,119 –> 00:59:37,119
that first part do to you and allow you

1655
00:59:34,960 –> 00:59:38,839
to think about what you need right and

1656
00:59:37,119 –> 00:59:41,079
so if you don’t have that do you go out

1657
00:59:38,839 –> 00:59:43,240
there and find it and some of that is

1658
00:59:41,079 –> 00:59:44,680
implicit in who you are and personality

1659
00:59:43,240 –> 00:59:46,920
and I remember I have two boys and

1660
00:59:44,680 –> 00:59:48,160
they’re very different kids and I was

1661
00:59:46,920 –> 00:59:49,599
like how can the both these children

1662
00:59:48,160 –> 00:59:51,960
have come from the same two parents but

1663
00:59:49,599 –> 00:59:53,880
they did right I mean and that’s the the

1664
00:59:51,960 –> 00:59:56,400
magic of our of the human brain is it’s

1665
00:59:53,880 –> 00:59:59,400
this unbelievably complex computer there

1666
00:59:56,400 –> 01:00:01,839
society around like the the friends they

1667
00:59:59,400 –> 01:00:03,880
choose yeah friend I mean and there’s so

1668
01:00:01,839 –> 01:00:06,000
many small factors so many variables

1669
01:00:03,880 –> 01:00:07,920
right you know what sport did you play

1670
01:00:06,000 –> 01:00:09,760
what did you were you a the I mean I was

1671
01:00:07,920 –> 01:00:11,640
a theater kid who also played sport so I

1672
01:00:09,760 –> 01:00:13,520
got you know I always loved having

1673
01:00:11,640 –> 01:00:15,039
multiple communities and again probably

1674
01:00:13,520 –> 01:00:17,400
speaks to my add that I needed the

1675
01:00:15,039 –> 01:00:19,359
theater people and the basketball people

1676
01:00:17,400 –> 01:00:20,920
and the rugby people and you know this

1677
01:00:19,359 –> 01:00:23,319
people and the technology people and for

1678
01:00:20,920 –> 01:00:24,599
me like a little bit of all of it was

1679
01:00:23,319 –> 01:00:26,240
the most interesting part rather than

1680
01:00:24,599 –> 01:00:28,599
becoming very verticalized I have

1681
01:00:26,240 –> 01:00:31,280
friends all they care about is one thing

1682
01:00:28,599 –> 01:00:32,880
right and and and again like I said

1683
01:00:31,280 –> 01:00:35,559
success is not dependent on having one

1684
01:00:32,880 –> 01:00:37,960
or the other way of operating right

1685
01:00:35,559 –> 01:00:39,720
often so many different formulas yes

1686
01:00:37,960 –> 01:00:42,119
yeah I mean and I think those variables

1687
01:00:39,720 –> 01:00:43,599
are are hard right I mean there is if we

1688
01:00:42,119 –> 01:00:46,520
if everyone knew the formula for Success

1689
01:00:43,599 –> 01:00:48,760
we’d all be using it so and and the

1690
01:00:46,520 –> 01:00:50,680
other thing I I think again success for

1691
01:00:48,760 –> 01:00:52,920
me is sometimes kind of a tough word too

1692
01:00:50,680 –> 01:00:55,480
right I believe I am constantly

1693
01:00:52,920 –> 01:00:56,559
successful because I love my life right

1694
01:00:55,480 –> 01:00:58,039
I enjoy

1695
01:00:56,559 –> 01:00:59,319
that I have and it doesn’t mean bad

1696
01:00:58,039 –> 01:01:01,200
things don’t happen of course they do

1697
01:00:59,319 –> 01:01:04,000
people get sick people die people you

1698
01:01:01,200 –> 01:01:05,839
know jobs come Jobs go bad things happen

1699
01:01:04,000 –> 01:01:08,760
to people that you care about but I

1700
01:01:05,839 –> 01:01:11,960
think it’s how you you respond to them

1701
01:01:08,760 –> 01:01:13,119
that is important right and um I’m slly

1702
01:01:11,960 –> 01:01:15,880
not stating that that’s the only way to

1703
01:01:13,119 –> 01:01:17,400
be like that that for me that everyone

1704
01:01:15,880 –> 01:01:18,559
talks about grit and resilience and all

1705
01:01:17,400 –> 01:01:20,680
these things but if there’s anything I

1706
01:01:18,559 –> 01:01:22,640
wanted my children to learn it’s not

1707
01:01:20,680 –> 01:01:24,760
just how to live in a golden cocoon

1708
01:01:22,640 –> 01:01:26,359
right it is to know that there are

1709
01:01:24,760 –> 01:01:28,319
difficult things in the world and and

1710
01:01:26,359 –> 01:01:30,799
some of them they will inevitably have

1711
01:01:28,319 –> 01:01:33,319
to face and give them the strength to

1712
01:01:30,799 –> 01:01:35,200
understand that they can right um that

1713
01:01:33,319 –> 01:01:36,400
they and and they they will and look

1714
01:01:35,200 –> 01:01:38,359
sometimes those things are chemically

1715
01:01:36,400 –> 01:01:40,000
taken away from from people you know you

1716
01:01:38,359 –> 01:01:42,400
know your brain chemistry might not

1717
01:01:40,000 –> 01:01:44,280
allow for that and so we have to be

1718
01:01:42,400 –> 01:01:47,720
empathetic to the world around us trying

1719
01:01:44,280 –> 01:01:50,079
to understand that there is no easy

1720
01:01:47,720 –> 01:01:52,079
buckets of neurobehavior there is a wide

1721
01:01:50,079 –> 01:01:53,880
spectrum how people behave and I

1722
01:01:52,079 –> 01:01:55,440
typically tend to find when you are not

1723
01:01:53,880 –> 01:01:56,839
given one thing you’re typically given

1724
01:01:55,440 –> 01:02:00,119
another you have to figure out what that

1725
01:01:56,839 –> 01:02:03,240
thing is right so for me you know add

1726
01:02:00,119 –> 01:02:05,279
comes with certain things and and and

1727
01:02:03,240 –> 01:02:07,200
corporate add which is a manifestation

1728
01:02:05,279 –> 01:02:08,920
it also comes with certain things and

1729
01:02:07,200 –> 01:02:11,279
you have to find your own path through

1730
01:02:08,920 –> 01:02:13,359
that right and and and figure out sort

1731
01:02:11,279 –> 01:02:14,680
of how you perceive the world how the

1732
01:02:13,359 –> 01:02:16,279
world perceives you and how you can

1733
01:02:14,680 –> 01:02:18,559
operate through it in a way using

1734
01:02:16,279 –> 01:02:21,599
technology using your relationships

1735
01:02:18,559 –> 01:02:24,400
using your experience um and asking for

1736
01:02:21,599 –> 01:02:27,119
guidance asking for wisdom asking for

1737
01:02:24,400 –> 01:02:28,359
experience I love talking to my grand

1738
01:02:27,119 –> 01:02:30,720
what what used to be my grandparents

1739
01:02:28,359 –> 01:02:32,880
generation because I do believe there is

1740
01:02:30,720 –> 01:02:35,640
fundamental knowledge in experience and

1741
01:02:32,880 –> 01:02:37,400
age and I think sometimes you know

1742
01:02:35,640 –> 01:02:40,039
sometimes some you know families don’t

1743
01:02:37,400 –> 01:02:42,000
allow for that and I I one of the things

1744
01:02:40,039 –> 01:02:43,640
that I love is when my children get to

1745
01:02:42,000 –> 01:02:45,160
hang out with their grandparents or

1746
01:02:43,640 –> 01:02:48,279
their grandparents friends and and just

1747
01:02:45,160 –> 01:02:50,319
hear about stories of of of doing things

1748
01:02:48,279 –> 01:02:51,920
and being through stuff and good things

1749
01:02:50,319 –> 01:02:54,039
and bad things and hard things and easy

1750
01:02:51,920 –> 01:02:55,440
things and I think technology will

1751
01:02:54,039 –> 01:02:58,000
hopefully enable some of these stories

1752
01:02:55,440 –> 01:03:00,720
to be told St better too you know um

1753
01:02:58,000 –> 01:03:04,000
we’ll see I think that’s uniquely human

1754
01:03:00,720 –> 01:03:06,599
right um learning and growing through

1755
01:03:04,000 –> 01:03:08,960
through through stories and if we can

1756
01:03:06,599 –> 01:03:12,279
teach our AI how to learn and grow the

1757
01:03:08,960 –> 01:03:15,079
same way my hope is that more will be

1758
01:03:12,279 –> 01:03:16,680
beneficial than not right and if we can

1759
01:03:15,079 –> 01:03:17,680
allow that to happen with people we can

1760
01:03:16,680 –> 01:03:20,319
allow that to happen with the

1761
01:03:17,680 –> 01:03:20,319
Technologies we

1762
01:03:20,480 –> 01:03:26,440
create I think this this is a perfect

1763
01:03:23,359 –> 01:03:29,559
ending to our our chat

1764
01:03:26,440 –> 01:03:34,160
I think you you’ve summed it up really

1765
01:03:29,559 –> 01:03:37,960
really nicely okay um so just the last

1766
01:03:34,160 –> 01:03:41,319
last last question um yeah so reflecting

1767
01:03:37,960 –> 01:03:43,799
on your career which accomplishments are

1768
01:03:41,319 –> 01:03:46,960
you most proud of it’s always the teams

1769
01:03:43,799 –> 01:03:48,839
I’ve built always the teams I’ve built

1770
01:03:46,960 –> 01:03:49,960
um you know a lot of people who worked

1771
01:03:48,839 –> 01:03:52,119
for me have now worked for me at

1772
01:03:49,960 –> 01:03:55,119
multiple companies in one case four or

1773
01:03:52,119 –> 01:03:57,319
five companies um and the cultures I

1774
01:03:55,119 –> 01:03:59,079
built the things that we did together

1775
01:03:57,319 –> 01:04:01,319
were important the value that we drove

1776
01:03:59,079 –> 01:04:03,480
for shareholders was important but I

1777
01:04:01,319 –> 01:04:05,559
think it was the communities that we

1778
01:04:03,480 –> 01:04:06,760
created and it was not limited to one

1779
01:04:05,559 –> 01:04:08,720
company it was not limited to one

1780
01:04:06,760 –> 01:04:12,079
industry it was not limited to one

1781
01:04:08,720 –> 01:04:14,160
geography um you know I think we created

1782
01:04:12,079 –> 01:04:17,039
a wonderful ecosystem and we continue to

1783
01:04:14,160 –> 01:04:18,799
rely on each other and uplift each other

1784
01:04:17,039 –> 01:04:21,319
and talk to each other and learn from

1785
01:04:18,799 –> 01:04:22,400
each other and that is what I am by far

1786
01:04:21,319 –> 01:04:25,920
the proudest

1787
01:04:22,400 –> 01:04:28,799
of sounds like you’re a great boss I

1788
01:04:25,920 –> 01:04:32,480
I’ll will do some research to see if it

1789
01:04:28,799 –> 01:04:35,440
if it um if it’s the same on the other

1790
01:04:32,480 –> 01:04:39,760
side no I’m I’m sure I’m sure okay great

1791
01:04:35,440 –> 01:04:39,760
thank you thank you