AI, Innovation, and Risk

Welcome to Cornell’s Keynotes. I’m your host, Lutz Finger. I’m a faculty member of the Johnson School and the author of the eCornell Certificate, Designing and Building AI Solutions. It’s essentially a course where I clone myself to teach about AI and AI applications.

And today, I would like to talk about AI innovation and risk, and whether the U.S. can maintain its current market dominance. And for that, I’m so pleased to welcome our guest, Anish Chopra. He is Chief Strategy Officer from Arcadia.

He has built a successful data company in healthcare. He served as the first U.S. Chief Technology Officer, and the Virginia State of Technology’s Chief Technology Officer. And he is currently a Council Member of the National AI Council for Congress.

Thank you so much, Anish, for joining us. Oh, my friend, it’s a pleasure to be with you, and we’re going to have a great discussion. Yeah, so, like, such a long sentence about introducing you. Give me a kind of a clue.

Like, so, okay, what is a Council Member of the National AI Council actually do? Well, that’s a great question. And I’m new in my role. Probably three months.

So, a little bit of context. Towards the end of the Trump administration, in its first term, Congress worked together on a National AI Act, the premise being, as with most jobs and industries of the future, the U.S. aspires to win economically. And so, Congress called on the administration to establish an expert advisory council that could report out both to the administration and to Congress.

And so, the first thing that Congress did was to set the baseline. specific advisors guiding them on how their ideology or approach can make a difference. So we’re kind of in that expert panel, take the questions, give answers perspective. We meet probably once every other month.

And we recently concluded a report on recommendations for the incoming administration on a number of key initiatives that could be done in the first hundred days to keep the momentum going on our AI economic success. This is pretty cool. Essentially, like the government takes a bunch of like experts like you who has worked in data, who has worked in AI, who knows an industry, in your case, healthcare extremely well, and ask them for statements. Is EU doing this as well?

Is China doing this as well? Is this like, do you have your counterparts? You know, I don’t know if this particular thing is the most important question of the day for how we organize these issues. Are democracies…

Democracy is unique in that we have this kind of shared view of government. So executive branch, legislative, judicial. I think in China, they’ve got a little bit more of a top down point of view, as we’ll get into in a moment. And Europe is in a unique place.

They seem to have been really enamored with the idea of regulating their way towards these new technologies. And so that’s a different perspective. And my view is it tells you something that there are topics that transcend parties. Right, correct.

He gets asked by President Macron, who early on said, I’m sure we’ll regulate us out of the market. So Macron asks him to do a quick speech. And that wasn’t planned. And he goes and he talks AI for the American people.

Very patriotic phrase. But what does it mean in practice? What’s your sense? Well, let me just say, I actually found J.D.

Vance’s speech quite refreshing and clear. To some degree, when you’ve got 100 problems to solve, as we’re going to get into AI has, you know, economic competitiveness, infrastructure investment, you know, issues around free expression, safety, multi-stakeholder input. There are a lot of issues. You almost want to have clarity about what’s your top priority.

And we heard that very clearly. First from the Trump executive order on AI. But we heard it very clearly from J.D. with put color and texture.

The idea that the AI safety summit, which is what was entitled, you know, when London held it, it really makes a statement that the main reason for gathering is AI safety. And maybe what we saw in the speech and in the aftermath, maybe we want to maximize the use of this technology for good and framing it as AI opportunity. So I think that the idea of AI safety versus AI safety probably speaks a bit more to my perspectives, which is that you want to do that responsibly. But you really want to diffuse the benefits of this technology to the greatest good.

If all we get is better social media algorithms to get us even more addicted to our phones, that is not the end game. We want it to improve our educational system, make it much more effective in our health care system. Advance. You know.

Small businesses. So as I think about, you know, going back to the Obama administration, how do we maximize the value of technology, data and innovation to advance the big priorities of the country? I heard in AI opportunity a lot more of the gas pedal moving. And I hope we’re going to get into this.

It was not a statement that we don’t need safety. It was simply a statement that we’re going to lead with opportunity. And we want to work with the industry on getting towards a. Which, by the way, isn’t that dissimilar to.

Policymaking around public private partnerships to begin with, which we will probably cover. Now, what the audience don’t know, like you actually you are part of the online certificate that I created for for canal. You came on and like we cover technical topics and then you like you and I, we have a discussion around applications and this is like probably for me. It’s one of.

The highlights in the course this discussion and you at that point you you focused a lot on saying, look, if if the government gets involved, it has actually three stakeholders. And I just repeat this from the course. You have three stakeholders. You outlined is these are the citizens.

These are the the companies with a P rights or innovation. And these are the nation states with the. Next. And then you have the national security.

In if you talked if you put J. Vance’s. Speech in that context and compared, for example, to Europe or China. How do you see this differently?

Well, I think here’s how I would characterize it. The speech for J. Vance was very economic and industry focused the supply side to some degree. How do we make sure that the model developers, the labs.

Are racing faster and stronger towards. Well, let’s not call it a G. I but some future state where we reach a position where we’ve got a flywheel where our models are the models and anybody that wishes to use these models will rent those models from the U. S.

I think it was a heavy economic stakeholder pitch. Uh China clearly has a bit more of a thumb on the scale on the security. Uh nation state. Use cases.

So as it builds its AI capacity, it’s got a big customer, you know, already, which is to advance their national capacity, advancing the state. And Alex Karp would say the same thing, probably for the U. S. Right.

Alex Karp is the CEO from volunteer technology. Yeah, to some degree. Let me set this at the outset. President Obama quipped.

I think in one media story that Washington is a battle within the 40 yard lines in U. S. Football terms, meaning we’re largely going in kind of a similar direction, but we’re going to see a slight tilt. So my commentary is not that we’re having 100% economic focus, zero on security and zero on citizenry and then vice versa.

You know, it may be, you know, 35 30. Yeah. You know, 32 or whatever. So it may be maybe a slightly nuanced twist.

For sure. The U. S. Government itself wishes to be a consumer of AI.

And within that the D. O. D. Has obviously a very big voice.

You see this in drones and all of the activity happening with even in how the war in Ukraine Ukraine is playing out. But you’re also acknowledging that that is a very large voice. That that is just one component for us, for us creating an industrial base that can solve, you know, every sector, bankings, health care, real estate, you name it. Europe confuses me and it has confused me for a little while.

If you were to sort of map out where have all the unicorns come from over the last 20 plus years, they don’t really concentrate much in Europe. We see that heavy concentration in the US. We see some, obviously, success stories in Asia. Which, by the way, just to put down, it’s sad because Europe actually publishes quite a lot.

So content wise, Europe creates good knowledge. But unicorn wise, Europe struggles. To some degree, the American story is the story of the dynamism of a model that takes talent and knowledge. And grinds it through a competitive process to generate productive goods and services.

And that, for lack of a better term, innovation pipeline management, we’re really good at it in the US. And that’s why the best talent comes here if they wish to commercialize their ideas. As opposed to an academic focus where you can certainly rank the best universities and thought leaders and find a high concentration of talent in Europe. And I’m not trying to put down the European Union.

I’m not trying to put down the Europeans. I have a lot of respect for the Europeans. But this idea that you’re going to be the greatest place to start a business by having the strongest regulatory regime doesn’t strike me as the winning message. And so we sort of struck a balance in the US.

I thought the Biden approach was actually reasonable. But I appreciated the JD Vance commentary that like, well, I’m going to tilt it this way so everybody knows the flag is on opportunity. While we still encourage industry. Yeah.

And we’ll make some efforts to do so responsibly. And we’ll get into responsibility in a minute. It’s actually two comments to this. This is interesting because like the…

If you have those three entities, you’re saying it needs a balance. And very well said. My understanding from the JD Vance discussion was not so much I put the flag on opportunity more than the balance is decided by us, the US, and not by Europe. Well, the implication, let me parse that a little bit because even I’m frustrated about this issue.

So if our tech firms are building global platforms and they are subject to rules in a given jurisdiction, at some point, those rules become the foundation for what those platforms have to adhere to. And effectively do become the standard. So to some degree, Europe has positioned itself to say, we may not be the homes of the companies, but we’re going to be the ones to set the rules for how those products are going to make it into our market. So if they end up hurting American companies, or in my view, misallocate the problem to solve with the intervention.

So if I were to think in cost benefit terms, it may be that we have similar objectives. We want to reduce disinformation and we want to promote competition. I mean, these are basic rules like mom and apple pie. But if the how to get there is like a very complex regulation where you have to always ask the courts, did I get it right?

How far do I have to go? You could find yourself spending a lot more resources to get an incremental improvement on a baseline service. So was the juice worth the squeeze would be the question. And I think, J.D., was sort of speaking to Europeans by saying, look, we’ve tolerated your taxing the American entrepreneurial spirit, the innovation ecosystem.

But for so long, I’m going to say at this point, get out of the way. Let us do what we’re going to do. So you don’t harm the West against the shared concerns around China’s leadership. And with Deep Seek and all the activity that happened in the last few weeks, there’s, there’s clearly a sense that the two countries may be a lot closer in terms of their advances.

And so, look, again, actually asked me, I’m a Democrat. I care deeply about societal good. And I appreciated J.D. Vance’s commentary around, you know, we’re going to run plant the flag on opportunity and we’re going to I hope the corollary to that is, you know, by the way, the industry should self-regulate, we’ll collaborate, create standards.

So there’s a there’s a second. And third sentence that is after this speech that I think will kind of fill in the blanks to keep this within the 40 yard line. You asked me about because let’s pivot for a moment to China and then we can look actually from Trump over Biden to like from Obama, Trump, Biden, Trump now to how the China policy is looking like. And you asked me in the prep for this call.

I think we have. Sorry. Yeah. How much of a head start does the U.S.

Have on the on the models? And my answer is not a lot anymore. We are at an equal playing field in models. Yes, they are incremental lead better.

But, you know, this is like this like this is difference between PlayStation and a computer. Right. It’s like it’s an arm’s length race. And at the moment, OK, Grok came out today.

Amazing. But two weeks ago, it was actually. Deep seek. So I don’t think we have.

On the math level, on the computational, we are the best a big head start anymore. Well, here’s the. Pushback. My view is if I were in seat, OK, so back to my time, let’s say cloud computing just to go backwards, let’s I would say one could argue, you know, circa 2005 to 2010 cloud computing growing up a lot of it was a jump ball.

You could have in theory, you could have seen leaders around the world step up and build platforms that could sell global SaaS services globally. But the U.S. really kind of spread its wings and became the flywheel for SaaS. I mean, I think I don’t know what the share of our revenues are from some.

But it’s a. It’s a dominant. Platform. You know, one of the areas that we tried to help build that strength was to say, look, we.

Commercial companies can buy cloud services and there isn’t as much regulatory risk or other operational risks, and so they could thrive, but maybe in a smaller TAM. But these rest of these markets for them to go to the cloud would be complicated. So we worked on FedRAMP to create industry. Standards towards a more secure cloud and in some degree banking and others piggybacked off of that.

So we kind of continued the growth engine by bringing it into the public and regulated markets. So this China model race, a question to some degree is there may be a specific computational task on a benchmark that shows parity. But if you lift it up and said, no, no, are the guts of the systems and the processes and the. The whole package and the application developer ecosystem, are they that piece feels like America has got a little bit more of its act together.

And so the probability that the industry vertical solutions are going to be U.S. born and scaled feels still right to me, even if on a specific benchmark mathematically and in the context of whatever. I mean, what is the value of these benchmarks? Let’s I don’t even know.

Like, does winning the benchmark get you like a prize? Totally, totally nothing. I mean, on the game, you got to have products and services that can be scaled. I’m so much with you.

This is and we should probably we have a we have a question from Vera about technology singularity. We should touch this in one second. However, I know that you and I and that’s also the general sense of the general idea of the. correct way of thinking is that there’s a there’s a there’s a there’s a there’s a there’s a there’s a there in the US enterprise value and the top 10 companies enterprise value all summed up in Europe.

And let’s make this easy. The US is my height 6.4. How tall do you believe are the top 10 companies together in Europe? Six inches.

Six inches, you are so good. It is this. It is four inches. This is really the size of the European market.

And you held up a soldier of a knight from the European border, like back when it was like it had a military muscle to do all this great work. Anyway. Well, I don’t want to make an advertisement for your favorite online retailer. But I, you know, I tried to buy something which is four inches tall.

And they offered me obviously, an Iron Man. I was like, I cannot buy an Iron Man. So I paid $2 extra to get this knight. I love it.

Now, let’s stop. But this is the idea here is AI will help with applications. What’s your like, what one of the questions from the audience and audience, if you’re listening to this, this is your moment to get prime time with Anish. So type in your questions and send them off.

But Elvira, thanks Elvira for your question asked, what are the conversations around technology singularity and how this will affect jobs? Let’s come to the jobs part a little bit later. But like, let’s, let’s touch on what is your view on the technology singularity idea? Well, the beautiful thing as a policymaker is it’s not my place to have a view on the current state of the technological evolution and the opportunity to see machine human.

There’s a there’s a set of experts that will decide when and if we’re going to see such a thing. I believe there’s a certain point of view that’s correct, by this date or that date. The question I come back to is what is the role of government in an environment where this technological progress is taking place? And I believe the Obama framework for this holds even in the Trump administration world.

And that is, we refer to this our strategy for American innovation. And it basically asks the question, what can we be doing collectively to ensure that the jobs and industries of the future are designed, scaled, the outcomes and the benefits of which are accruing to the American people? Again, if there is a singularity, what are the implications of this? We’ll get to the jobs issue in a minute.

So we’ve historically made investments as societies on infrastructure, roadways, railways, and runways. So we’ve historically made investments as societies on infrastructure, roadways, obvious infrastructure looks a lot more digital. R&D, computing infrastructure, hence Stargate and some of the questions about what can the public-private partnerships do. Get financed.

Yeah. Human capital, talent. So if you think about this question of singularity, it speaks to what’s the infrastructure that facilitates people thinking, doing, acting, investing, and building towards this kind of future. Well, you need to have a robust foundation.

I actually like this. Let me answer the singularity part from my point of view. But I like the approach that you say, no matter whether it is there or not, we need to have the singularity also is there to serve us, the people. And because singularity is there to serve us, the people.

And because singularity is there to serve us, for that, we need regulation and we need a structure. And I like this structure. And the structure should be focused on opportunity, coming back to the earlier point. Let’s talk to the singularity.

During my time at Google, I had also the pleasure to meet Demis Hassabis, the Nobel Prize laureate, as he worked with Google on AlphaFold. And he just recently doubled down on saying, guys, the AGI, I don’t see it yet. But I’m going to ask you a question. What do you think about the AGI?

He actually said there’s a 50% chance that we might see more generalizable as a human in five years’ time, which is still some way out. Other people would give it more time. So only because a tool like ChatGPT, DeepSeek, Gemini, or whatever, sounds intelligent, does not necessarily mean it’s generalizable. Only because a car can drive by itself doesn’t mean it’s generalizable.

Only because my chess computer beats me, it doesn’t mean it’s generalizable. And you can actually tell this when you go on OpenAI, and then you have to select between five different models. The model which is for planning or the model which is for search or the model which is, that’s not generalizable. Now, we are on a path, but first we need to get AGI being like a human, and then there might be the singularity.

And that is even further out there. So that would be my technical part to it. But no matter what… But we need the supporting structure of the nation state to thrive.

Yes. And so to finish that part of it, because it needs three things. The first is this infrastructure layer. The second is, and this is where you get into the Europe versus China versus the US rules of the road to promote competition and outcomes, basically to facilitate greater results that are created.

And that’s where we need to get into the infrastructure layer. So historically, this has been antitrust rules, net neutrality rules around how do we leverage the pipes to our homes. And so what we’re hearing right now is an active debate. Should AI safety be rules and regulations by a nation state?

Should there be self-regulatory benchmark-driven industry norms? And so one can have a pretty healthy discussion about when and how do we leverage the pipes to our homes. So what’s happening with that is there’s a hole there with 건데finendo, with 건데finendo, with Cornell education at a fraction of the price. So whatever the national priorities are, even if not kind of controlled by the government, there’s a call to action by the government that fosters investment and opportunity.

If you put those three things together, the American dynamism is really clear relative to European or Chinese at the moment, is that we found a way to bring harmony to these critical components. And I think, look, I think the Trump administration can be framed in the same way. They’re going to be investing in infrastructure. The National AI Resource Computing Center, or NAR, came out of a Trump administration effort.

So there’s investments in R&D, there’s recruiting the best and the brightest, this whole debate about H-1B versus O-1 visas and all that kind of thing. So you see a lot more similarity than differences when you take that overall American strategy into consideration. America has a different approach to innovation than Europe. And I like this framing of continuity.

I mean, you have been in the White House with Obama. You do know Biden. You are now in that setup where you are looking at the council members and discuss with them. And you stress here this continuation of the American approach to innovation.

Which I think, I mean, it definitely has paid off if we look at the outcome here. But deep seek is now hitting the market, right? I could argue all this investment from Google and OpenAI and all of this money and the debt-funded Stargate announcement might depreciate very soon because we have OpenAI, we have open source models competing. This could be methodological.

This could be data. Thanks to Zuckerberg. This could be as well the Chinese deep seek. And Dr.

Barnhill, Benjamin Barnhill, had a question for this, which I think fits perfectly into this context. So first of all, thanks for saying this. And like audience, please put your questions down. We are completely reachable on all channels.

In a government perspective, what is the implication of foreign cloud AI ML-based models, specifically thinking about deep seek LMs, LLMs in terms of data sovereignty or like I would cross off the data sovereignty. And you said this is nothing new. You said there is continuation. But like, how do we see this?

How did we do it in cloud? How do we do it now? Yeah. So here is, herein lies the debate.

Will the economic value in the era of AI accrue to the applications that bring it to the last mile sectors of the economy? In which case, the more open source foundation models that can be run on an AWS cluster at low cost. I love that Satya Nadella introduced this Javon’s paradox to this dialogue. I never heard of it.

Yes. Amazing. Amazing observation. Maybe explain it quickly.

Yeah. So the basic principle is as the price of the good falls, demand for the good will far outstrip it. And then the aggregate pie grows so big that it’s, it actually is net positive to the industry. So while I can’t speak to the economic return on investment of whatever the hundred billion dollar Stargate plan looks like, and its version of, you know, how it affected Colossus or whatever that Elon did in Tennessee or wherever that was.

My, I can’t speak to, in our risk taking culture, it almost doesn’t matter. Like companies are going to have cash and they can put that cash to its highest and best value. And if they’ve come to the conclusion that it’s going to be in building out the foundation, power centers and data centers and putting a hundred thousand machines connected to each other. Well, God bless our economy allows for that to be a bet.

And it’s not going to like ruin the world. If that bet was off by an order of magnitude, deep seeks introduction and availability. The fact that this Chinese, whatever hedge fund, whatever it is, open source. I don’t know.

What is it? It’s something it was a research center and they, they essentially, they couldn’t build the models because it didn’t have US export restrictions. Right? So all the design decisions were like, make it on a cheaper model, right?

So MacGyver, you know, I’m a huge believer in India, frugal innovation. There’s a lot of debate whether India should be in this. None. The Nile Connie, who I respect deeply, is sort of the Godfather.

Of Elijah, the digital infrastructure in India. When he announced the India strategy here, it was on the all the way on the other side of the use of AI, not on the model supply. And so back to this issue of where will the economic value accrue? If it turns out that model availability is ubiquitous, open, cheap, and it works, then a whole swath of.

Our economy can become much more productive at much lower, you know, investment. So that’s great. And India is going to push on use cases that are cheap. So if the supply side is cheap, use cases are cheap.

We could actually have an unbelievable gift, which is every single person in your country can have a supercomputer that does, makes them all superhuman, right? If everyone from every neighborhood and every, you know, the poorest. Neighborhoods have the same capacity as the richest kids with all the resources. Man, what a story for economic opportunity for everyone.

So thank you, you know, to the folks who’ve been democratizing this, that it can actually result in more economic opportunity, more American dream. So I’m. Thank you. Look, and in this case, right?

Because his decision. Yeah, right. Who he set the. So here’s I will say an interesting thing that happened back to this nuance.

There was a bit of a debate I felt with the approach in the Biden administration. So maybe I’ll highlight this as an example. So when the executive orders and the initial statements around what the administration was going to do were being contemplated, one of the first actions was this idea of a frontier model commitment. And this got a little bit wrapped up in some of the complaints by JD and others.

They wrote in these documents, the Biden team did. If the size of your model is greater than X, then you are expected to communicate with our AI Safety Institute and other other government agencies. And so that that whenever you set a technical standard into a regular. Regulatory framework, it is like always going to look in hindsight like it was a ridiculous thing to do because we’ve blown past whatever that milestone was is my best understanding.

So it did also emphasize collaboration with all the proprietary models. And it took a little while to pivot to recognize and to celebrate open source. I, I do believe. It would have been nicer to have a bit more encouragement of open source from the outset because as we’re seeing now, it facilitates a lot more diversity of app developers and in America that diversity and democratization wins.

Yes. So I wish we would have more celebration of open source in the early days. There was a lot of, I mean, the defense to a lot, a lot of the politics looks on these things. Is that like the military?

The national security crowd, they kind of want a few throats to choke, if you will. So they kind of prefer, you know, a smaller number of people that they could get in a room and engage on really complex issues. So I can imagine in the room. Now, the Biden team never had a CTO.

So I don’t know exactly how like you, you were the CTO from the Obama team. Trump had it a CTO. Now, Trump is like promoted the CTO like times 10. They like four of them with all the AI officers.

And so, so there’s a, there was an acknowledgement that you want to have like the economic council with its equities around. How do we grow the economy? You want to have the security people say, here’s what our equities are to make sure that we don’t like give our enemies an undue advantage and that we can, you know, harvest some of this stuff for our own. You want to have like a technological point of view.

What’s the science and research agenda? Then you got to want to have a roadmap. Like, why do you put all these pieces together? And that debate, that debate should have resulted in more support for open source.

But let me push back a little bit on on the statement. We should be like discuss public-private partnership in this respect. Yeah, when am so I applaud Zuckerberg for going open source, but from his business model like Meta as a platform. He wants open source because the open source allows more creators to create content, which more people consume, which makes his platform more successful.

So in like it give the give the. Public the tools to create another metaverse so that matter can really be meta, right? This is this makes sense. Now, if you if if you think about it, and I think we discussed this in my course, and the figure program is like how many companies after the mobile revolution, if we take the last big thing, which got Silicon Valley, I’m sitting here in Silicon Valley, which got Silicon Valley excited.

That was a mobile revolution, right? I remember I was at LinkedIn at that time. And we started. Stop everything in order to catch the mobile train and change LinkedIn into a mobile solution, right?

How many companies actually entered the SMP 500 right after? Let’s say the start of the mobile revolution was Apple iPhone after the iPhone came out seven seven new company and it because the most value was from this mobile revolution was generated for the companies that had access to data and access to customer. If the same thing. Happens now with AI because AI is a very neat interface.

And then we would see that the private part like private corporations using open source will generate the most value. Now, you are a big supporter of public private partnerships, right? How does this play in and how you know, when I want to be a fly on the wall and one of your meetings discussion, how do you how do you balance between how much? Public versus how much private?

Well, this gets to where in the stack do you want public private partnerships? So, uh, R and D is inherently, you know, public private. You have research centers, computing clusters, and you want to incorporate access for researchers who don’t have the budget to cover the cost of these sort of things. So developing infrastructure is critical.

The in the world of standards. So the to me, the most powerful, highly highest leverage point for public private partnerships is in technical standards development. So I would argue, AI safety is the place for public private partnerships. I would argue the model content compute protocol.

MCP that Claude released is an ideal public private partnership. So we’d have a common protocol that the industry could rally around for how we allow a machine. To interact as a human on on websites and data portability and so forth. So if you identified market competition as a key priority to drive more economic diversity and economic success, you’ll find that if you can get standards through public private partnerships developed, you increase the possibility.

You increase the possibility. For more more market actors. Now, it easier said than done. I don’t know in the mobile computing blip when everything was hot, whatever.

It’s 2014 15. We heard that time frame was whether we got that mix, right? You know, we got the infrastructure, right? We open sourced a whole bunch of spectrum.

We released more spectrum in the in the mid to late 2010s. Then then in the prior decade. And I think that, you know, represented a bit of a public private partnership to spur, you know, the the applications in mobile, but the competition part wasn’t as great to your point. We had a few winners and maybe and I trust played a little bit more of a role where, you know, back to this debate about did better get too big and should Instagram and hindsight should have been allowed.

That’s a harder legal question, but we win when we have. Open standards more competition and applications that to your comment about special specialized models can go to market. So so there may be lots of players who build products and services on AI that are not the mag 7. Yeah, I so the NAI AC the National AI Advisory Council report.

It’s a long document. It’s. It’s worth at least summarization from chat GPT, but it’s worth a read. So and you you talk about boosting AI adoption for businesses.

You talk about training and funding. Mark Logan, one of the people who are on the stream again, like comment on it. Mark Logan asked the following question. What’s one regulatory change you would push for to help the US companies innovate with AI without drowning in red tape or losing.

What’s one regulatory change you would push for to help the US companies innovate with AI without drowning in red tape or losing against less related competitors to China? So if you take the NAI AC report and like what’s your favorite thing? Well, well, I’m a healthcare guy. So I’m a little biased in that.

I want to unleash innovation in healthcare. So I might speak to that one in particular. Look at the moment. We don’t have a lot of regulations on AI commercial.

AI is not a regulated space that in fact that that’s a little bit of the discussion. The JD Vance was having in Paris is that I don’t want to go down that road. And so I can’t say, oh, turn off something that doesn’t really exist yet. It’s more like don’t turn on the thing that would get us in trouble.

Let’s keep moving is kind of the headline. So the one action, there are several actions in the report, I think in threes. So to me, the commitment to keep funding the science and the R&D speaks to the investments in infrastructure. We have to do that.

We have to do more. So I think that part of the recommendation of like keep boosting the quality of the supply is there. The multi-stakeholder encouragement around governance and ensuring that we have more of that public private, you know, that voice. I still think is the right answer.

And in fact, I do think it you could make that work even with JD Vance’s speech in Europe because you want the industry to self-regulate. And you want it to have a set of guiding principles so that people aren’t competing on shipping unsafe products. You want them to ship a stronger products and then can iterate when they get feedback that there’s a problem so that you can you can have a flywheel where the private sector can self-organize. But in the healthcare space, I will say my in my in the report, my number one focus area in the chapter I spent the most time on was the AI models today are trained on the internet.

So I think that’s the first thing I would say. I think that’s the first thing I would say. Healthcare data represents like whatever 20% some number of the global data pie every year, but like a bare fraction of it have been used in any AI training. So I am eager to bring healthcare data into the training program and even more eager to ask the question.

How do we build the equivalent of an AI supercomputing doctor? Yes. So that we can diagnose disease early as early as possible. And we can actually identify interventions that can reduce that disease from progressing further.

So people can live longer and healthier lives. Actually, let’s do a quick stop here. And let’s explain a little bit your background. So I met you.

Oh, I met you during my LinkedIn time. Yes. But then we started getting connected. I joined Google Health as one of the early members.

We’re trying to build. I remember. And you had built a data company in healthcare. I did.

And you sold it later. This was a very successful one. But explain a little bit to the audience what the premise was from care journey. Well, in the Affordable Care Act, which in hindsight is a gift for anyone who wants to make the healthcare system better, whether you’re a liberal or a conservative, there’s something in the ACA that you can say, wow, I want to do this.

I want to double down on that because that’s how I’m going to make the system better because nobody believes the current system is giving us the biggest bang for the buck. We’ve got exceptional medical device innovation and pharmaceutical innovation and top talent surgeons and everything else. But for whatever reason, we’re not able to extend the benefits of all that to as many people as we should. And so there’s a lot of room for improvement.

The thesis in the ACA that I wanted to highlight was that. Well, we’re going to make the healthcare system better. prior to the Obama administration, it was illegal for any commercial entity to access and use the claims history of government plan program beneficiaries, Medicare and Medicaid. So if I was trying to figure out which doctor has the best experience caring for people that have diabetes by helping them avoid the hospital unnecessarily or the emergency room and to get them care at the lowest cost, you could track this if you had access to the data.

You could basically build a cohort of diabetics who could track all over the country what their journeys look like in aggregate and say, who’s got the least number of those avoidable conditions and is it statistically relevant signal? So we shifted the pie. We shifted the policy to yes, not no from when it comes to this issue of opening up government data. In 2015, then Andy Slavitt, the head of the CMS Medicare Medicaid program, said, if you have a commercial idea, tell us about it and we’ll go through a privacy review board process, but we’ll authorize you to have de-identified access to the Medicare data for purposes of building information.

So with that, with that, with that, with that, with that, with that, with that, maybe a bit more scary highlighting of those that are not so high. And so Care Journey built, I think, one of the most effective physician quality rating engines in the country. U.S. News licenses it in a more public way.

But a lot of our customers are payers and providers who incorporate that into their referral programming, network development programming, and soon, I hope, extending it into consumer navigation and search. And I think the core principle here is the stunning of the good information, right? People talk about AI as something which is out there and taking over the world. And this is always like totally like a nightmare for me.

And we’re like AI is there to support us. AI is there to help us. And in order to do that, it needs data, right? As much as I go to my doctor and tell my doctor everything.

Yeah. So that. The doctor’s AI called the human brain is hopefully coming up with something to help me. We need to enable data access.

And there are so many good examples in what Care Journey has done. I, at one point in time, had the pleasure to work with Marty McCurry, who. Yes. Like he is becoming, I think, the FDA.

Yeah. And he built as well a database to show quality metrics and build out a quality metric. So he was like. So there’s a way to measure quality with like an application layer, like on top of your data.

If you make data available, then you can measure. And if you can measure, you can see something like quality and improvement. Yes. So we license Marty’s analytical package to bring it in a way he and I both built applications on the base data layer.

And we went in a direction he took it in a different direction, and we were able to bring his 건데 with it. Right. Right. structs into ours.

So you sort of have a better library of insights that we went to market to the payers and providers and some of the life sciences companies with his package. So it’s a wonderful thing that you can do. And in many ways, it’s the only job you can feel comfortable doing to bend the healthcare cost curve that doesn’t make you feel like you’ve cut people’s access or you’ve boosted costs. If I push against it.

And so we started off by JD Vance talk and we said it’s the opportunity. And we talked about that there is a balance between those different entities. Now, if you look at healthcare, that balance in general has been tilted way more towards the patient. Don’t do harm, which is not true when we do like when new medications are tested, we try to limit harm, but harm is happening individually.

The process of research, right? We try to limit it, but it’s happening. Now, what’s your point of it? Or is something and this is a question from Stephanie who says, do we need an ISO for AI and industry standard guidance?

Is there is there something needed in order to prevent us? So I launched with about 40 health systems and health plans about a year and a half ago, with a survey of over 200,000 healthcare companies with over 200,000 healthcare companies with over 200,000 healthcare companies with over And so the idea here is that if we could strengthen the governance of the use of AI locally, we can get to a better place where there’s a feedback loop about what’s considered useful and what’s not useful. I’ll give you a silly example. There was a New York Times article.

That email from your doctor may have been written by AI and not your doctor was sort of like the headline. And, you know, one of the debates in AI communities is when to watermark. And so one of the health systems UCSD quoted in the article said, you know, we, even though we have lots of templates and macros and tools in our daily lives that we don’t say, oh, I use this template to start my email or my memo to you, that AI felt different and to earn trust. Maybe it made sense to disclose that this, you know.

This feature that allows a doctor to respond in a pre-populated way could be, you know, a productivity tool and not a lazy just like send whatever the machine says. So UC San Diego describes their governance model that allows them to sort of see whether this is, you know, down the fairway. And their conclusion was we want to add a passage at the end that says this message was partially automated and reviewed by doctors. So UC San Diego’s health systems were like, you know what?

We concluded that you don’t have to say anything. So we chose not to disclose that this message was partially automated. And the New York Times kind of shone light on this, even though these two organizations came to different conclusions. But having gone through a similar process of governance.

I think it’s kind of good that we have, you know, attempting different things. And the market will provide feedback and we’ll see what’s the, but they can iterate much faster. There is a very fascinating study done by Eric Bjornjolfsson. He is a professor and a senior fellow at Stanford.

And he looked at productivity and he figured out that like the productivity gains for junior folks are not knowledgeable. Knowledgeable folks are enormous. And we have seen something. And I think that’s what we’re seeing in healthcare before.

If you show a complicated x-ray to a general, like general doctor, they don’t know. And if you send them, there was a test done. So you sent to doctors exactly the same description. One time you say it’s a human doctor who wrote this description on the x-ray.

And the other time you said it’s an AI. And then you ask the doctors how they feel about it. It was published in Nature. And the general practitioner, they say, oh, thank you.

This is so helpful. Obviously the x-ray. The x-ray doctors say, no, I don’t trust this. This is like the AI is wrong.

Now, the point is AI can scale up. And why would we need a disclaimer? We just should deliver a better service. And obviously we are responsible for the service because we humans have agency.

We just use an AI tool. That’s the essence of the course. Now nobody needs to do the certificate. But yes, that’s it.

Now, we are running into the five last minutes. Anish, outlook to the future. Nobody knows. And I will keep you responsible for what you say now and tell you forever that you got this wrong.

No, but like, where are we going? What is the future of AI look like? Well, to me, it’s probably the most exciting time if you wanted to solve big problems in our world. Because AI will make us that much more productive.

And. If the productivity gains can accrue in health, energy, education, these are the sectors where it’s been flat for the last decade or longer, despite huge capital investments. Then that’s going to waken up a lot of sectors of the economy. So I love this SAS software as a service versus service as software.

I don’t know if you tracked all this. I love it because we’re going to shift from selling, you know, IT systems through the IT department and more like labor substitute through the business units. And I think it’s going to be a real positive. I think it’s going to be great that we’re going to see nursing units incorporate AI into their planning process, etc.

So it’s to me. I feel very bullish that we’re going to see. Yeah. I realized that this is like, a nurse out of a pocket, by the way, this is an interesting limitation for AI models because people do not want to hear the theory.

They want compassion. And AI at the moment is currently not very good at compassion. So my key moment there was actually in my UX testing. One lady looked at the recommendation and says, I know that I have free diabetes.

Don’t tell me about it. I still eat my donut. I was like, okay, that lady doesn’t need content. AI is good in content.

So I’m not doing something in e-commerce, blame me, but the company is called R2Decide. We actually become the sales agent or the sales guiding principle there. So, but I’m with you. The future is full of opportunities.

And with that, thank you so much for this time. This was a very fun discussion. Now I’m looking at a long list of questions. Okay.

My suggestion would be that we both kind of like align on the questions and all the people who have asked questions and haven’t gotten them answered. What we can do is we, if you follow Anish Chopra on LinkedIn, and if you follow me on LinkedIn, and if you follow Econel on LinkedIn, we post the question and a quick answer to, because some of those are actually pretty stunning, but it didn’t follow into the flow. So thank you so much. Anish, you’re kicking off a series of amazing AI discussions.

We will do this monthly. So thank you. Thank you. All right, my friend.

Thanks everybody. Bye. All right, bye. Thank you.