Interview with Joanna Bryson

Joanna J. Bryson is a transdisciplinary researcher on the structure and dynamics of human- and animal-like intelligence. Her research covers topics ranging from artificial intelligence, through autonomy and robot ethics, and on to human cooperation.  She holds degrees in Psychology from Chicago (AB) and Edinburgh (MPhil), and Artificial Intelligence from Edinburgh (MSc) and MIT (ScD). She has additional professional research experience from Oxford, Harvard, and LEGO, and technical experience in Chicago’s financial industry, and international organization management consultancy. Bryson is presently a Reader (associate professor) at the University of Bath, and an affiliate of Princeton’s Center for Information Technology Policy.

Business Today: To begin with, what do you think is the biggest misconception about the future of Artificial Intelligence? 

Dr. Joanna Bryson: The false idea that artificial intelligence is in the future. We’ve had it for decades now and it’s fundamentally changing who and what we are. Many people associate the future of Artificial Intelligence with Arnold Schwarzenegger and the Terminator and robot apes bent on seeking world domination, but I don’t think we’re ever going to see something like that, and in the meantime, AI is already here and causing radical change. For example, think of our relationship with large tech companies. Facebook and Google give us entertainment and information, not in return for a monetary transaction but in return for our information. They are paying us for our information with their services, basically – it’s a barter transaction. I think that’s one of the many reasons that there is an increase in wealth inequality; all kinds of transactions are happening that are not denominated conventionally, and so they can’t be taxed. The only reason we know how important these tech companies are is because the market is valuing them with high market caps in recognition of these hidden transactions. I don’t think that is only true for super AI companies. We now do labor ourselves that we used to hire people for like booking travel or checking out at supermarkets, and we don’t get paid for that except that it presumably gets back to us in the form of low costs. Effectively, we are bartering labor. I think that people just haven’t recognized the extent to which we are changing the world already as a result of automation. Many people aren’t seeing this yet because politics is blaming the symptoms on other forces like globalization. 

BT: What are the implications of thinking that way for the next 5-10 years?

Bryson: I think in the next five years it’s possible we’ll see radical shifts in democracy and how the state is organized. The last time we had this much wealth inequality and this much political polarization was around WWI, which caused us to fall through a bunch of floors and brought a lot of instability but which led to the welfare state and the enshrining of universal human rights. That was a really big shift, a completely new invention. 

I think we are going to need another revolution of governance on the order of the welfare state. Well, first of all we need to return to the welfare state as that is being dismantled. The threat of communism meant Western governments implemented policies to keep the proletariat happy. When it became clear that communism wasn’t going to work, once the Soviet economy plateaued in the late 70s, and I think that’s when the elite stopped worrying about keeping the proletariat happy, so that was when whatever policy had been keeping wages growing steadily ended. When you look at the inequality numbers, there’s a weird trait where the wealth inequality and political polarization are just weirdly low and declining from WWII until 1978. The graph you often see is that between 1945 and 1978 wages rose with productivity and then after 1978 they plateaued. I think that government policy was keeping wages growing with productivity and I don’t know what exactly it was but it was in living memory so hopefully someone knows. 

BT: I’ve heard the argument that the reason wages began plateauing in 1978 is because that’s when automation began picking up steam.

Bryson: That doesn’t make sense at all. Automation has been going on for centuries. There is nothing special that happened in AI in 1978. The cause was the change in government policy in 1978 as the Soviet economy plateaued and the resulting rise in wealth inequality.

To be clear, I don’t think it’s actually the inequality itself that’s the problem, I think it’s the curve. If you look at what’s happened with the Gini Coefficient, the curve now has an incredibly steep part and a whole lot of flat. If you’re right along the flat it’s not clear how you can get up. You can’t just say if I go to college I get to the steep part. I have academics who have asked me if inequality is really that big of a deal because we are getting these amazing gifts due to the incentives inequality provides. The twenties, when inequality was high, were a very creative time, after all; but the two world wars also completely sucked. I think it’s better to sacrifice a little bit of creativity for a slightly more stable economy. 

BT: How does technology play into that equation, and what can we do about it?

Bryson: One of the things they talk about a lot in the EU is whether or not we should declare robots to be people and then tax them. I think that there is economic interest in that because it’s about taking a part of the business process, fully automating it, and then breaking it off. The robot performs labor but they don’t get tax liability or legal liability for it because it’s not a real person. I can see why the European Union would want to say this might be a way to solve that problem. But I think it’s a really bad way. it doesn’t break the chain, it’s not coherent to treat a robot like person. First of all they are not accountable as people are. Second of all it’s hard to count them; you can replicate a software program without cost, and the boundaries between different entities aren’t clear. It should be very clear that the legal and financial responsibility for automated parts are the original business’s.

The alternative is coming up with a better revenue model. Europe has more people and a larger economy than America, yet Google is paying no tax and getting more benefits from Europe than they are getting from America. I don’t think a tax would make sense anymore because companies figure out all types of ways to barter and cheat the system. 

In fact, now that we have information, we should look into a wealth tax. Wealth taxes are in fact already known to be better than income tax in theory but the main problem is that it’s hard to track, there’s so many ways to hide wealth. However, now that wealth can be better tracked and accounted for with information technology, a wealth tax may be possible.

BT: What keeps you up at night?

Bryson: Data and privacy. The more we know about people, the easier it is to manipulate them. My biggest fear is that people are too easily manipulated now that we know so much information about them. I think data should be treated under personal law; if people seem to be manipulating us, we should be able to do class action, and I think that is what the European Union is thinking about, creating an AI regulatory body that would be watching for things like that and get on and intervene. It would be a major shift from the way business today is done. Data wouldn’t be owned by the people who hold it, but by the people it’s about, and the people who own it would have some kind of asset, but not one they can do whatever they want with. 

BT: Going off of some of the policies you mentioned, is the main barrier to the realization just politics? They sound fairly feasible.

Bryson: A lot of the things I have been talking about are feasible because I have been looking for things that are feasible. What we need to do is first of all convince ourselves that we are ready and then convince other people that we are ready. Sometimes you just have to move in politics, you just have to try and guess, and then we need to convince people with power that this is worth doing. I try to do that, I talk about this kind of stuff when I’m at AI meetings. From talking to governments and companies, I’ve noticed a lot of the things people worry about, we don’t need to worry about, it’s like fire-fighting. They think if we put out this fire, it’s going to fix it, but no, that’s a fire that’s been caused by something more fundamental - the political polarization, the wealth inequality, that system. 

BT: What would be your advice for undergraduates who are deciding what to do in light of the changes wrought by new technologies and the problems that come with it?

Bryson: First of all pick a problem, don’t keep bouncing around. Try to pick a problem you can really contribute to. Bounce around for a couple of years, try to see different things but pick something and really work on it. Do realize though that that’s sort of a five year threshold and it’s important to be generalist, it’s important to keep learning. I always tell people to get into the best university because it does keep you cognitively challenged and learning to learn is a big deal. Also, in order to learn new things, it helps to be intelligent. It used to be that people thought intelligence peaked when they were 18. This was because 18 was when you would stop being educated. It’s now known there are ways to maintain your intelligence into your old age, and the two best predictors are having a cognitively challenging job and picking a partner that is at least as smart as you are. That would be my advice to everyone. Finding a challenging job and a partner that is as smart as you are. 

BT: In terms of career path: given someone’s strengths, how should they be thinking about how to move forward?

Bryson: It’s not only about strengths, although that is important. It’s also about interest. I just picked something that was I really interested in and stuck with it, and didn’t chase grants like some people do, so in some ways I’m successful in that I’ve learned what I wanted to learn and am actually having a tangible influence in the world right now, but on the other hand, I’m 52 and don’t have tenure. 

A big part of it is also creating opportunity. One of my favorite quotes is “luck is when opportunity meets preparation.” The best way to prepare is to differentiate yourself. There’s no reason to keep doing the same thing. There’s a whole bunch of people doing the same thing and the wages for that are going to down. I think this is one of the big mistakes we are making right now in general education, teaching to the test, so everyone gets the same education, which is kind of weak. We should try to seek unique individual opportunities and try to combine different things.

When evaluating opportunities, I would always look for things where they need something that I could do but I would get to learn something that I thought I needed to know. That’s how when I was in industry I landed some great opportunities, by hopping a couple of times and making those kinds of assessments, where I had a strength that the company needed enough that they would let me address the weakness that I wanted to address. You can’t always go exactly where you want to go, but you can build up your portfolio as you take advantage of different opportunities. Then again, every time you change, you do lose a little ground, so there are different strategies. ﹥