W. I should say im actually trained as a lawyer originally. Ive been at m. I. T. For more than 20 years. And ive alwaysorked with an Extraordinary Group of computer scientists. My research in all that time has always been in the Computer Science literature. But what im really most interested in is number one, how do help policymakers to make good decisions about Technology Policy and so that involves understanding the details of how cputer systems and Network Systems work. And probably more importantly, im really interested in how to evolve our Computing Technology so its more responsive to Public Policy needs. And ive been able to do that because ive worked with and continue to work with an Extraordinary Group of computer scientists and other researchers at m. I. T. And around the world. Can you give one example of how youve influenced policy . Well, people are probably well aware as an example that theres a big debate about the use of encryption technology. We need encryption to protect our email exchanges, our financial transactions, political speech that goes on, we hope privately online when it needs t governments for decades have been concerned that the use stng eryption technology would thwart the ability of Law Enforcement to conduct electronic surveillance. So from a technical perspective, we looked at that question and while acknowledging that encryption can pose some barriers for the police, we have shown throuough Technical Research that if you try to force all encryption systems to be tappable or to have back doors as theyre sometimes called, then youll end up harming the security of all the billions of people around the world who use the internet and Computing Technology. And so while this is an ongoing debate, even the governments that are trying to contntrol encryption have acknowledged that they shouldnt do so in a way that introduces systemic weaknesses. Soso thats one area where i think weve had a real effect. Well, to help us explore some of those other areas and some of the policy initiatives that are involved with technology today, kyle burley, the Technology Editor with axios, is joining us. Thank you, peter, and thank you, professor. I want to stick on encryption for a moment. You alluded to, there is an appetite in washington and weve seen it from bill barr andome on the hill to impose back doors on companies. Are you concerned about that . Im certainly concerned that governments make decisns that really get the balance right. That look at all the interests on all sides of this debate and make sure to make the right decisions. I certainly understand the frustration that Law Enforcement has. Hey are in many ways digitally thats a problem that goes beyond encryption technology. They certainly need help and need better training and need better equipment to do investigations in the digital world. And i think we should be providing Law Enforcement the help to be able to function in this environment. The problem is that trying to regulate encryption is kind of a quick fix. It might feel good. But its not really going to help. Becaususe the concerted crimina activity is always going to find ways to hide their communicatioion one way or the other. And it will just leave all the rest of us in a more vulnerable state. O im concerned that policymakers really should look at the whole picture whe theyre making this choice. Kyle you mentioned policymakers are always playing catchup and always a little behind, do you see any remedies for that . Well, hopeful, the program i teach at m. I. T. Is part of the remedy for that. Were constantly trying to understand how to educate our computer scien students so theyre more aware of Public Policy needs. And we also spend a lot of time working with policymakers all around the world to try to understand the challenges they face, to help them to be smart about how to approach them. And to help where possible to make sure that the systems were building meet the needs that society has. So yes, i think i think weve treated a lot of technology as a kind of fixed quantity, that theres some sort of absolute wall between the Public Policy world and the technical world. And we very much want to bring that wall down. Both because wthink we can do a better job of designing systems and because we think that policymakers can do a better job of making policy if theyre wellinformed. Ky what does that look like from washingtons side . You guys can sort of better educate Computer Science students on policy, but, you know, how do you educate policymakers on computer sciee . Ill give you an example. Were doing a lot of research right now on election security. A group of my students have looked very carefully at some of the mobile voting apps that are out there and some of the internet, online voting apps that are out there. And what we learned that in some cases the apps that some election jurisdictions arere choosing have very significant flaws. Nd weve been glad to see that d. H. S. As an exale has worked very hard to try to bring information about those vulnerabilities to election jurisdictions all around the country. In looking at some of the Internet Voting Services where there are different choices about how those systems are designed, whether theyre used to actually enable people to submit ballots electronically or perhaps just get copies of ballots that they can then mail in on paper, weve been able to show that one is a pretty safe approach. That is the electronic ballot delivery with mailin return and one is a really dangerous approach where there could be hundreds of thousands, millions of ballots sitting on unprotected servers. So, you know, sometimes the policy world misses the nuance in a certain way, wants internet voting good, bad. And our researchers have shown there are techniques that can be used that can be productive and that can expand access to the blot for people who need it and want it and may face barriers. But that there are some things that just shouldnt be done. So i think as long as we get Pay Attention to the details, the Technical Details and the policy details, we can make progress on these things. Kyle theres been a lot of talk abo, you know, a number of policy issues whether its election security, privacy, a. I. , facial l recognition and, you know, were not seeing a lot of firm action. Do you think that theres a lack of learship in washington on some of thesese . Well, faal recognitions a great example. A lot of concern about face recognition actually arose from research that was done by another student of ours at the , who found that widedely used face Recognition Systems from some of our leading Technology Companies are dramatically less accurate if youre a person of color or a w woman. And the results of this has been a really deep investigigation into just what takes to build more accure Face Recognition Technology. I think there are parts of the government that have worked really hard to try to support that. And the National Institute of standards and technology is doing morere and more testing i this a area trying to establish benchmarks about how to tell whenen you have a good face recognition in the system and when you have one thats not good. So but i think there is more need for policy leadership in this area. Were going to be relying on all kind of Artificial Intelligencebased technologies for really critical decisions, for everything fro whether youre going to get arresteted not to whether you are gog to get a loan or not or hired for a job or not and the fact is right now as we saw with face recognition, we often lack the ability to make solid Technical Assessments of whether those systems are actually Accurate Enough for the purpose that theyre using. And there are always going to be companies that put out different technologies and say here, try ts, try that. And thats fine when theyre for low stakes u usage. But for these higher stakes usage, when peoples libty or lives, economic livelihood is on the line, i think the government really does have to step in and set some standards and make it clear that if technology if companies are deploying technologygy which is substandard, at minimum, they shouldnt be able to sell it. And beyond that, they should probably be a financially responsible for the harm. Peter can you explain in layman terms how facial recognition is developed and how how it recognizes faces and how its being used today . Sure. So face recognition uses a branch of Artificial Intelligence called Machine Learning. And the way that Machine Learning works generally, so its a technique to try to get machines to learn things. For example, to try to match names to faces. And in a nutshell, what the way that you teach a machine to learn how faces is u give it lots and lots of images of faces and associated names. And then when and the computer looks for patterns in all of those images. It may looat millions of images to try to figure outut h to recognize one from the other. In some cases face recognition is about matching one face to another. So, for example, if you want to use your face as the key to enter a building, for example, that kind of Face Recognition Technology will try to figure out whether the video image, for example, that it sees of peter is like the one thats on file. If its a question of putting names to faces, then it uld do a different kind of technique. But either way, its about Teaching Computers to find patterns in very large amounts of data and then recognizing that pattern again in some new data. But the key to face recognition or any other kind of Machine Learning technology is that the pattern recognition is only as good as the data whats called e Training Data that is initially presented to the computer. So, forxample, if you try to train a computer to do face recognition, and all the images of the people with darker skin are poorly lit and dont have adequate contrast, then that system is not going to learn how to recognize people with darker skin as well as people with lighter skin. Andness a problem that this is really an engineering problem which is a solvable problem if enough effort is put into it. But because these technologies are developed very often in a commercial context, companies are going to are going t to expend amuch effort as they feel they need to expend to sell their product but no more. So part of what we have to do is make sure that we have the right kind of standards in place and the right kind of responsibility in place in case this system doesnt work properly. Peter to go back to what kyle said earlier, theres a real question about privacy, isnt there, and a potential abuse . Absolutely. So theres no question that in order to make Machine Learning techniques work well, work accurately, they need a lot of data. And in a lot of cases thats personal data. Now, there are dferent approaches that you can take to that problem. You can try to secure the data to make sure that even though one company perhaps gets together lots of personal data for training purposes, you protect it and make sure that no one c can get into the data. Thats always somewhat risky because as we know, its pretty hard to build perfectly secure systems. There are also techniques that are being developed in my lab at m. I. T. And by people all around the world for what are called private learning techniques. So that you can actually do the same kind of Machine Learning training that we talked about. But do it in a way that the data aually stays with the owner of the data and that the computation remains private. So the computer can learn the patterns that it needs to learn in order to recognize whatever it is, the face or a credit risk or the incidence of cancer perhaps in an xray or anything else whi at the same time preserving the privacy of that information by allowing it to stay in control of the person who has it originally. Kyle academia has been out front of lot of these issues that youre alluding to, the way that facial Recognition Systems are formed more poorly on people of color and, you know, were starting to kind of see the industry catch up. A number of major tech compans have imposed moritoria on t use of their facial Recognition Technology by Police Departments at the very least. Do you see sort of a reckoning going on . Do you see more sincere awareness in Silicon Valley of how products may be exacerbatingxisting inequality . Well, i think society generally is takina more critical look at a lot of technology thats being put in front of us thats being offered for use. You know, if you look at the way the internet developed in erblely initially, commercially, in the 1990s, it had a lot of excitement about it. Some people called it the wild west. It was very enticing new chnology. And there was a real spirit of experimentation then which was great. It led to a lot of innovation and a lot of advances. And i think im very happy with the expanded access to information that it created for all of us in society. But i think theres a recognition also that maybe some of f the concerns about privacy werent attended to as carefully as they ought to have been. In what almost feels like a second wave of data iense he have technology, Artificial IntelligenceMachine Learning and everyone is looking more critically and more carefully, partly is because the companies that are developing a lot of these technologies went from the proverbial, you know, couple of inventors in a garage to enormouous Global Entities that have strong in some casese dominant positions in markets. So i think were appropriately looking at these things more carefully. We also recognize that our lives depend on them a lot more urgently where in viewing this technology with the power to drive us arod or with the power to make very important decisions about our lives. So yes. And i think were right, though, in the middle of that process of trying to figure out what it means to hold Companies Accountable for protecting peoples privacy, for buding their products and Services According to a certain set of standards. You know, its a kind of a legal detail. But for a lg time, and to this day, software anand really all were talking about software here exclusively etty much software isnt subject to t normal Product Liability rules that we think about for things like automobiles or consumer appliances or whatever else. So if your car, you know, has an accident when it shount or explodes or catches fire, the Car Companies responsible for a lot of money. Thats not that is not the case for software and Internet Service providers. So were in the process of trying t to figure out what kin of responsibility should we put on these companies when were really going to depend on their products and services for our lives. Kyle you mentioned our lives obviously do depend on technology more thanan ever rig now were in the middle of a global pandemic. What are maybe some areas where you see, you know, whats something that youre hopeful about that technology could solve as we try to fight covid . So im spending a lot of time myself working in a area called digital Contact Tracing. Your viewers will many of them probably know that apple and google in april announced a global offering of a number of technologies which make it possible for people to determine if theyve been in close proximity with someone whos been identified as infected with the covid19 virus. The design for those systems came out of some work that we did in my lab with ron robest at. T. And labs around the world in switzerland and germany and elsewhere, and this all happened very, very quickly in response to the pandemic. We were all looking for what we could do to help. And came to this view that we could actually use the cell phones that are in our pockets, in our hands, for many, many people around the world, to help with the epidemiological process withublic health sure t people who have been exposed to this Infectious Disease take appropriate measures. So its its very interesting because the Technology Developed super quickly. We put out a design about three weeks. And a week later, apple and google said ok, were goingo do that. And a month later, it was already deployed in both of their mobile operating systems. Were now in a more complicated process where Public Health authorities all around the world are trying to figure out how to use that. Were working very closely with a number of them to try to make this work. Anand weve moved from what is nair narrow technical ququestion. How do you get phones to recognize when theyre in proxim with each other so how to integrate a system like this into a very complicated Public Health process known as Contact Tracing that people are e talki about a lot. So im hopef