Information & Ethics committee  Yes, that's a great question. I would say that the reason you have seen this technological advancement is that AI systems are getting better across the board. There have been a lot of developments in the architecture that powers these systems. These systems now run on better hardware, which means they're able to operate at much faster speeds.

Information & Ethics committee  That is one of the challenges in this kind of endeavour. I would say, broadly speaking, that it's a matter of asking the question of how we're going about collecting that data. In the absence of a regulatory framework, it is easy for different companies to operate in different kinds of capacities.

Information & Ethics committee  I'm not familiar with the financial situation that surrounds the institute, but I also want to clarify that I'm speaking here as an individual and, mostly, to present the data that the index has on facial recognition. My views are not those of Stanford.

Information & Ethics committee  Part of the reason they're becoming more biased is that, typically, these models are being fed increasingly large numbers of data. For certain models, it is advantageous to have a lot of data. The more data you give the model, the more likely it is to get some data that is not ideal.

Information & Ethics committee  One of the things I allude to—and we talk about this in the report—is the issue of filtration, whereby you can mandate that companies filter the kind of data they use to train their systems. It's been reported in different papers that there can be a filtration tax. That is, if you filter data before you apply it to a model, the model might not perform as optimally as if you gave it unfiltered data, because the more data a model has, typically, the better it can perform on certain tasks.

Information & Ethics committee  I will say that our report doesn't make any concrete recommendations for steps that should be taken. It's more trying to take stock of where the AI landscape is. I will make a couple of points, though. First, I think the report would clearly imply that there should be a greater consciousness that AI tools are going to become increasingly ubiquitous and that a lot of these tools are flawed.

Information & Ethics committee  Again, I will politely decline to answer that question. I don't think the report—

Information & Ethics committee  I would say yes. AI is obviously something that changes day by day. I mean, 2022 has been a tremendous year of AI progress; it seems like every week there's a new model that's breaking ground. I don't think we're ever going to get to a point where we'll have data to sufficiently know the answer to every question, but we're getting more data, and an absence of absolute data does not mean that we shouldn't take action.

Information & Ethics committee  I can perhaps go first and then I'll defer to Ms. Polsky. I would say again that there are definitely questions that remain unanswered, but we do have a lot of data that says things that are difficult to dispute. As mentioned, the paper that I cited earlier shows that facial recognition systems can be biased, and I think that's a generally well-accepted fact.

Information & Ethics committee  I'll say a couple of things. First, I'm not technically a doctor. Although I very much appreciate the title, I feel that I would be remiss not to correct that. Second, it is perhaps outside my area of expertise to offer recommendations for the committee. I understand that they are very valuable and very essential, but I feel that I can comment most on the data and what impact—

Information & Ethics committee  Again, I think answering that question is outside of my scope of expertise. I would defer more to the other witness on the panel, who I think has a bit more experience in this domain and can comment a bit more authoritatively.

Information & Ethics committee  Perhaps not necessarily as a best practice but a point of reality, one of the big takeaways from this “AI Index” report is that AI is becoming increasingly ubiquitous in all of our lives. Ten years ago, there were a lot of AI problems that were very difficult to solve. This meant that AI was something that was just being researched, whereas, if you move forward 10 years, AI is now one of those things that are coming out of the lab and moving into the real world.

Information & Ethics committee  Certainly. That's an excellent question. It speaks to the fact that although regulation of facial recognition technologies certainly matters, there are also other AI use cases that might merit regulatory attention. One of the takeaways from the data we have on facial recognition is that facial recognition is in the middle of the pack in terms of total private investment.

Information & Ethics committee  Again, I didn't contribute to that report directly, so I wouldn't be best suited to answer the question, but I think perhaps the issue that the report is getting at there is one of institutional shift. You might potentially have these technologies used by different individuals in different parameters.

Information & Ethics committee  My apologies for that trouble with the microphone. The AI Index doesn't comment directly on the amount of investment that exists in that space, but it alludes to the fact that this is becoming an area of increasing concern across a lot of different spaces. I'll highlight two points here.