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AI is going to be like electricity or like the steam engine or like computers meaning the kinds of technology that
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changed the world forever that changed Humanity forever welcome to the ripple effect the podcast
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that takes you on a journey through the minds of work and faculty I'm your host
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Dan Loney and in each episode we'll be diving deep into the inspiration behind
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the groundbreaking research that Wharton professors have conducted and exploring
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how their findings resonate with the world today we'll be covering a diverse
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range of topics bringing you the latest insights and knowledge that you can apply to your life into work so get
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ready to dive into new ideas with the ripple effect well we know there's been a lot of talk
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about artificial intelligence uh especially in the immediacy kartik and this is something that you have written
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about and talked about a lot what was it that kind of got your juices flowing and
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interest you about artificial intelligence in the first place well you know my undergraduate degree
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was in electronics and and there was a masters in computer science so I'd studied computer programming but this
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was back in the 90s at a time when AI wasn't what it is today and in fact he
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had mostly failed to deliver on its early Promise by then so the interest in AI was diminishing we had very limited
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coursework in AI and so that's the context in which I was first to introduce to AI but what really
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piqued my interest were actually a couple things when I was in grad school doing my PhD at Carnegie Mellon I took a
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course from you know one of these Geniuses of modern times his name is Herb Simon
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he is I think probably the only person I know who's won the highest award in
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economics the Nobel Prize and the highest award in computer science the Turing award and
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the highest award in psychology so he won all of these three and he was on campus and he was teaching a course
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and you just try and register for the course if you can and I did without having any interest in
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the subject and I remember when I was in that class and he would talk about these things
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which are like a mix of you know psychology how the human mind works computer science how can we take
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those ideas into uh the world of AI and computers and then economics as well in terms of what this means for for the
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world you know that was the first time my interest in this started to um get picked nonetheless my work still
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wasn't yet AI for the next few years I was working on e-commerce Internet advertising and so on and my first
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genuine interest in this topic came in when you know you started to see like personalized recommendations on Amazon
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and Netflix um in all these places and a student of mine uh brought up this question of you know
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what is it doing to the kinds of products we consume and kinds of media we consume and how is it changing it and
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then I got really interested in this idea that algorithms are influencing decisions we make
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and that was my first entry into this subject of algorithms broadly but then within that AI as well so I find it
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interesting because um there's so much conversation going on right now about Ai and how it's going to
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impact business and realistically Ai and business are are not new to each other they've been connected for some time but
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it feels like the conversation has taken a different level how do you view that combination of business and Ai and how
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those two will work in the future yeah so you know I think it's really interesting if you look at Ai and
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business of course AI is the big buzzword in business and so I find it often in the business world gets
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divisive and a bit polarized in the sense that there are the Believers who talk about look AI is going to be a
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game changer and then there are people who feel like oh okay this is the next nft or the next uh I don't know wearable
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computers or Google Glasses or whatever pick your example where there's a technology with a lot of hype that goes
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nowhere so I'm going to make a big board plane here which is that I think AI is
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going to be like electricity or like the steam engine or like computers meaning the kinds of technology that changed the
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world forever that changed Humanity forever there's the you know human lives before electricity
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and there's human lives after electricity it's going to be like that where they are
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and this is not just a statement I'm making based on my gut feel which by the
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way there is gut feel in that statement but it's based on real evidence so people economists and other researchers
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have studied these kinds of technologies that we refer to as general purpose Technologies these are Technologies like
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electricity computers that are different than other Technologies in a few ways one is that
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at a macro level they stimulate a lot of innovation and a huge amount of economic
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growth at a micro level meaning individual firms they end up changing winners and losers of individual markets
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because of how companies adopt the technology like take Internet for example well the largest retailer is in Walmart
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it's Amazon are Kmart one of the largest retailers before the internet doesn't exist today
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things like that right it changes competitive Dynamics fundamentally and researchers have looked at what are the
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properties of technologies that go on to become general purpose Technologies and
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all the early data suggests that AI looks like a general purpose Technologies if you look at
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hiring patterns related related to AI if you look at patent filings related to AI
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you look at a number of other things on in fact there was a recent study by my colleague Dan rock where he looked at
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specifically large language models like chat GPD and even his study finds even those models have some of the properties
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of general purpose technology so if you you started by asking what is the connection to business and I think my
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answer is it is going to be fundamentally transformative for business then you're talking about basically kind
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of like a pivot moment uh you know we use the term pivot a lot over the last three or four years because of the
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pandemic and how businesses had to make pivots in order to be able to survive this is a pivot but on a much larger
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scale of where we are going uh as a society absolutely I mean you've just brought up
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the pandemic imagine with the pandemic without the internet what that pandemic would be like you know we were able to
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navigate the pandemic because of the internet we were able to continue to work because of zoom and other things so
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the internet was really a general purpose technology that has changed our lives and it had a huge impact over the
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last 20 years and certainly the last two three years AI will be similar as well I
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mean we're just starting to see the early you know things like chat GPD but this
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is just a start I mean it's going to change everything and companies that don't wake up to that reality that want
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to follow rather than lead that want to say look you know this could be just a next
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buzzword we will play it safe or the companies that say you know the moment they see an early
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failure that backtrack and say there's no Roi on this like the companies that
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did do that when the.com bust happened companies that play these kinds of moves will pay a big price and I think it's
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the companies that truly Embrace its potential and play the long game they're
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going to be the big winners from from this trend so then what do you say about some of the recent calls to maybe slow
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down the development process and maybe take a little bit more time and and really think this out because it seems
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like there are obviously with some of the people that have talked about this they have some concerns about how fast
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things are moving I think first of all the concerns are legitimate it is moving very fast this is a
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technology that is unlike other Technologies we've seen in terms of the rate of change and the rate of progress
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and especially given its implications for simple things like employment employability all the way to
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you know things like use of AI in Warfare or AI going out of control there's a
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range of concerns here so I think the concerns are real now what is the right solution to those
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I'm not yet sold on whether a six-month pause in AI work is going to change anything
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if first of all I don't even think it's feasible but let's say it's feasible and
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you're able to stop all people working on these kinds of AI models and say stop
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for six months what's going to happen in six months nothing um because it's not like you'll find the
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magic uh solution in fact what needs to happen is you know investments in education
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at school levels where people are trained to understand AI they're trained to understand things like deep fakes
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they're trained to understand issues around ethics when Building Technology this is not something you
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solved in six months this is something you solve over 10 years and and change curriculum you need to
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retrain Engineers you need to retrain managers you need to also retrain your congressmen and senators and all of the
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politicians and lawmakers you can none of that so what what are you going to change in six months
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nothing and so I think what it requires is like really a focused effort where you're changing things over a
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20-year period and you are fast to react to problems that you've noticed with AI
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I was gonna say because I I think there's also another issue to bring up here as well and and I'll use chat GPT
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as the example because seemingly that is the one that everybody is talking about
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right now and everybody wants to incorporate in their operations whether it's Microsoft Google companies
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Etc uh how are companies going to be able to use this technology and say be better than their competition if they're
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all using the same type of product yeah great question by the way I actually think that
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a lot of the companies that will use off-the-shelf tools like say chat GPD and others
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will create amazing efficiencies that will be copied by a lot of their competitors which will bring costs down
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and all of the value I think will accrue to the eventual customers and users because it'll bring prices down the
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second thing that's going to happen is because they bring prices down it will
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help expand markets because it'll bring in new customers into various markets
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and the expansion of markets will mean there's value created for all of those
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companies equally meaning all of them gain some the companies that actually will be able
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to use things like this to get a real advantage over their competitors are going to be companies that are able
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to pair off-the-shelf AI tools and capabilities with something proprietary and what is that proprietary
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complementary asset they can bring to the table is going to be the name of the game for companies that are aggressively
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investing so I'll give you a couple examples of what is a proprietary thing they can bring in
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you could use an off-the-shelf large language model like gpd4 which is basically the underlying
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model for uh you know the chat GPD which was like GPD 3.5 but you can use an off-the-shelf model like that but if
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you've got a large proprietary data set of say Healthcare information Healthcare
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data set you can train or retrain those models on your massive Healthcare data set and now you've created a new AI that
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is the best in class at answering Healthcare questions and you were able to do that because you
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had the largest proprietary Healthcare data set you could do the same thing in finance in
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other areas so that's one you bring in something proprietary usually a very large proprietary data set or
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you change something in terms of user experience a good example of charge GPT itself open
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AI the company be behind chat GPD has had GPD one gpd2 gpd3 for a while and developers have been using it the
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capability in chat GPT is not fundamentally new it was already there and we've seen it I've used gpd3 for
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over a year now the difference is charge GPD provided that in a very seamless easy to use sort
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of UI and that shows you the value of user experience so somebody can take off the
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shelf AI but integrate it into a great user experience that creates a winning combination
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or somebody combines like for example there are companies that are trying to build image editing AI where you're
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taking an image and you want to edit it you want some things to be changed you don't want to go to photoshop and do it
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and you just want to give an instruction to Ai and it does it for you great there's lots of startups doing that
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many will use the same kinds of AI they look very similar now but if an apple does it and
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integrates it into an iPhone they can give a seamless experience to the user because you don't have to download an
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app you can take a photo right there you can make edits if Google does it and integrates it into Android that again
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gives a seamless experience on the phone that gives them a leg up over anyone else that's using the same kind of AI as
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them so that so it's all about pairing it with something called proprietary that is also complementary
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let me have you discuss the uh the legal side of the advancements that we're
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seeing around Ai and obviously there's lots of discussion right now uh around
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big Tech uh on the regulatory side at the moment how then does AI factor into the discussions on on legal
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and IP issues yeah I mean there's there's tons of legal issues around AI I think I'll
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mention a couple one couple ones one is is what happens when you use AI to make decisions in socially consequential
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settings and you do it at Large Scale so for example there have been concerns about using AI
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in courtrooms for example to predict the likelihood that a defense a defendant will reopen
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or what happens if you use AI to do resume screening or you use AI to do loan approvals and
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it turns out these AI have biases then a company that uses them in these very important settings exposes themselves to
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uh you know litigation and those kinds of issues and so that's one type of issue and I
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think at the end of the day my view on this is look yes you can complain all day you want about potential biases in
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AI but before we do that let's talk about what's the alternative the alternative is humans fundamentally
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flawed human decision makers who have their own biases so it's not like decisions in
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courtroom today or in hiring today are unbiased and you're switching to AI That's more biased in fact the reality
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is AI biases are probably easier to detect than human biases and probably easier to correct than AI biases and so
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companies will have to make sure they are taking sufficient safeguards auditing their AI sufficiently
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uh before they release Ai and these socially consequential settings so that's one set of concerns the other
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related to generative AI and we already saw this play out last weekend when this track was released
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That was supposed to be by Drake uh it did really well took off and then it turns out somebody created it with AI
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and so I think the legal issues there are going to be both on the input side of generative Ai and the output side and
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by input side I mean what kind of data are used to train the AI so if you're
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using data to train AI to create music the question is where did the training data set come from do you have the
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consent of the musicians who's created the music before you trained your system
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on that are you giving them suitable compensation if money is made out of the resulting
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product how are you tracking what is each musician's contribution you create
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a new brand new song how do you say two percent of this song is inspired from Jay-Z and three percent from Drake and
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four percent from somebody else how do you even determine that that's on the input side and on the
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output side if you create a new track and in Drake's voice uh or an Elvis's voice is that allowed
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do you need permissions do you you know so there's all these kinds of things and
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by the way U.S copyright law doesn't even cover synthetic media so what is the copyright
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law around creation of content by AI so lots of issues that have to be tackled in in the coming years and those are the
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kinds of things where I think lawmakers and lawyers in general will be slow and not Progressive
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and they will typically just resort to lawsuits and we I think we'll see a lot
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of lawsuits in the next two three years can I have you finish up our conversation around Ai and the labor
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market because that I think is also just the potential fascinating I mean obviously there have been stories and
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themes thrown out there for quite some time about the potential impact but we haven't gotten to the point I think yet
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where we've really had the rubber meet the road to a degree yeah yeah true uh look I think
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as far as ai's impact on labor market anyone who's concerned about its potential impact on
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the labor market is I think in the you know is asking the right set of questions
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in the sense that even though technology is in the past in human history have often had labor concerns associated
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with those Technologies labor is always for Technologies and in the past it's
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almost always been the case that new technologies have created more jobs than they have destroyed
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and so all of those concerns were misplaced in the past the real question is is AI like every
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other technology in the past where it will eventually create more jobs than it destroys or is it going to ultimately
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uh be a net job you know cannibalizer as opposed to Creator and I think that's the big
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question we don't know the answer if you were to put a gun to my head and say
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give me an answer right now Karthik I would say well I think it's probably going to have a net job loss rather than
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that job creation however that is not the full answer though because AI will also augment jobs
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and not just merely replace jobs so there will be a lot of jobs where there's a lot of routine things that we
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do that we don't enjoy that we do repetitively that are you know soul-sucking in some ways we
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will be able to Outsource that to Ai and we'll free up time to do the more interesting more creative pieces of the
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job which I think will be great for all of us so I think you know there's going
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to be that as well and I also want to distinguish between High skill and low skill jobs so
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the kind of AI that's been around for the last 10 years we'll call it predictive AI these are this is AI that
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makes predictions and you plug it into different tasks like predictive credit card transaction is fraudulent or not
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predictive an email is Spam or not or things like that this kind of AI you know is one type and then there's generative
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AI which is like chat GPD or uh you know stable diffusion that's creating text
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that's creating images and so on and I want to talk about how these impact jobs at different skill levels
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but first thing I'm going to just say is historically automation has affected
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blue-collar jobs the most low skill jobs that's what it's automated and affected
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the most question is is this true for the new kinds of AI like chat GPD or image
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creation and early research actually suggests that it suggests two things one is that these new kinds of AI increase
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productivity for workers so there's a test that's being done on developers a research
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study focused on developers using Code generation AI there's a research study that was
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focused on chat gpdlex system to improve writing and all of these show like nearly two-fold
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increase in productivity with just these early forms of AI and over time much greater productivity but
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what these studies show is also that not all workers benefit equally the study with developers showed that
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developers with the lowest skill levels benefited much more than developers with
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high skill levels the study with writing showed that writers who had the lowest writing
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skills benefited more so than writers with the higher skills so one of the things it also shows is
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that the new kinds of AI will affect White Collar jobs for sure but they will also empower
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workers with lower skill levels and help create an equal playing field and by the
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way you know in in global Commerce today English just knowing English is you know the paths to a job it's a path
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to success and somebody who doesn't know English it's you could have very high
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intelligence very high skill but not knowing English could itself be the bottleneck you suddenly bring generative
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AI and you even the playing field for for them and you can apply this for developers you can apply this for many
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other workers thank you for listening to the ripple effect we hope you found this episode
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informative and engaging don't forget to subscribe and leave us a review so that
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