Computer Scientists From The United States

"we can harness collective intelligence while maintaining rigorous security and ethical standards. The university champions the values and principles of the Western academic tradition as seen in the most advanced universities, and we hold faculty and students to the highest standards of conduct, transparency, and policy compliance."

"An atmosphere of suspicion could chill important international research partnerships and unfairly target individuals based on their ethnicity, educational history or national origin."

"What we need is not paranoia, but a well-policed and secure arena for international collaboration. This means clear guidelines for research partnerships, robust safeguards against unauthorized technology transfer, and a culture of transparency and ethical conduct in AI research."

"Many of the affiliations and co-appearances with people of Chinese background during our professional activities, as cited in research papers or advisory capacities—like mine or those of scholars from Oxford and MIT—are standard among top global academics."

"I’m optimistic that AI could help fuel socioeconomic development that has been much needed in Africa for the last half-century, But I’m also concerned that this competition could limit the autonomy of African countries and perpetuate neo-colonial practices that have negatively impacted their economies.”"

"Receiving this recognition a year after earning my PhD and a year into my professional career is considerable motivation for me to continue my research and advocacy.”"

"However, enabling people with the knowledge to understand the limitations of AI may help improve the responsible adoption and usage of these tools. Improving AI and data literacy within the general public will become fundamental as AI tools rapidly become integrated into society.”"

"It might be an English-as-a-second-language thing, but “sustain” to me sounds a bit like “survive”. And that feels like a low bar to be shooting for; I optimize for thriving :)."

"So, yes it's important to understand how a neuron works and a lot of neurophysiologists might complain that models of the neurons that the AI people are cooking up aren’t accurate enough. Well, that might be, but no amount of detailed understanding of an individual neuron or even how neurons get interconnected I think will be sufficient to have a good explanation of how it is that we do what we do. We have to have some higher level things and there are people working on that. But, some of it, I think, will get developed by those very people who have one foot in artificial intelligence and one foot in neuroscience to say, "Ah, the analogy to these high level programs is such and such to the way the brain does this." And they will invent concepts that will then help us understand the brain better."

"Unless I see the need to be thoughtful about it, I try to get bureaucratic things done as quickly as possible to “get it over with”."

"I am fairly particular about my calendar. I am a big believer in “how you spend your time is how you spend your life”. I’ve written before about how I manage my time."

"I am very cautious about adding meetings to my calendar. For any recurring meetings, can they be one-off with additional instances being as-needed? For one-offs, do we need a meeting or can we connect async? If it is a meeting where most folks are going to be listening, can the presentation be pre-recorded and posted so everyone can watch async, and then answer questions or discuss in comments? If it is clear that the meeting will be valuable, I am more than happy to do it (including recurring ones). I just carefully assess that for each meeting."

"I’ve also written about how I manage email. I apply the same zero-inbox strategy to all communication -- Chat messages and notifications at work, WhatsApp messages, Messenger messages, etc. It annoys me that Twitter and Instagram DMs don’t have an “archive” option :). This plays a big role in keeping communication channels “clean” and uncluttered."

"I am a huge fan of bots that let me send delayed messages on chat or email at work. To be honest, I wish there wasn’t this need for folks who like working “odd hours” to find ways to be “quiet” and tiptoe around via these bots. It would be ideal if everyone changed their settings so they don’t get pings in certain hours of their choice. That way everyone can work (or not) freely whenever they like. Both as a matter of principle, but also practically, given that many of the organizations we work at are global. It is not uncommon to have people on the team who have 0 overlap in work hours (e.g., west coast in the US with some countries in Europe). Does that mean all communication on the team needs to be via these bots? (I understand that power dynamics complicate these things, and so "just set your settings as you like" is easier said than done. There is also a good chance I am missing other perspectives here. So I plan to continue tiptoeing when I am working outside of “normal” hours :))."

"When a lot of pings are coming my way -- I pause to think whether they all need to be addressed right away. Can some wait till tomorrow? Can some things planned for tomorrow be done later in the week? I have found this to be highly effective in not feeling overwhelmed."

"If something worrisome comes up (e.g., interpersonal conflicts, or a critical approval running into roadblocks), I pause to notice the discomfort. I explicitly assess whether there is something I can do about it in the moment, or if I need to think about it before doing anything. If I can do something about it, I do it and try not to dwell on it till there is an update in the situation. If I need to think about it, I mark my calendar for later in the day or the next day with “think about X” and move on with the rest of my day. “Moving on” doesn’t come naturally to me and is something I have to explicitly remind myself to do. But I’ve been able to build this muscle faster than I expected -- once I did it a couple of times and found that it helped quite a bit, it made it easier to do it in future instances."

"I often end up rewriting. Sometimes I do that without ever finding the bug. I get to the point where I can just feel that it’s in this part here. I’m just not very comfortable about this part. It’s a mess. It really shouldn’t be that way. Rather than tweak it a little bit at a time, I’ll just throw away a couple hundred lines of code, rewrite it from scratch, and often then the bug is gone. Sometimes I feel guilty about that. Is that a failure on my part? I didn’t understand what the bug was. I didn’t find the bug. I just dropped a bomb on the house and blew up all the bugs and built a new house. In some sense, the bug eluded me. But if it becomes the right solution, maybe it’s OK. You’ve done it faster than you would have by finding it.”"

"One of the interesting things we found, when trying to predict how well somebody we’ve hired is going to perform when we evaluate them a year or two later, is one of the best indicators of success within the company was getting the worst possible score on one of your interviews. We rank people from one to four, and if you got a one on one of your interviews, that was a really good indicator of success."

"It will be a problem in the end, I think, for society what happens, what do we do with all the people that computers replace? And eventually, I mean, right now you need more and more skills in order to have jobs. But, there's this guy Robin Hansen, you know about Robin Hansen? Robin Hansen is an economist and he has got this interesting metaphor of sea level rising. Sea level is what computers can do. And land and the land that's inhabited, the jobs that require humans to do. And sea level's been rising. And on the shore a lot of people are displaced. Well, they've had to move to higher levels. But, to move to higher levels they have to have more training. Now, the fact that sea level's rising itself makes some higher levels. It's a funny thing. At sea level build some mountains so people can climb those mountains, but sea level will keep rising. And the question is will it rise above even those mountains? And so, what do we end up having people do?"

"Well, large corpuses of data are going to be useful in lots of them. I don't know that it'll solve all the problems in AI. I mean, right now we can't do all the things that humans can do. Look around you and you can see. I mean, we have office buildings full of people. And many of them aren't using their hand eye coordination. It isn't mechanical engineering which is a problem. You might ask, why are they there? What are they doing? Well, they're having meetings, they're filling out paperwork, they're doing studies, they're communicating with other humans, they're making plans. And those are things, why can't computers do all that? Why is there anybody in those buildings except the janitors and maybe a few top bosses? Well, and computers would be cheap if we could do it, cheaper than those people. And so, why are they there? Well, because computers can't do it yet. And will lots and lots of data solve that problem? I don't think so. Might help, might be part of the solution, but the reason we don't have what you might call human level intelligence yet is that we just don't have the ideas needed in order to write the programs that would allow us to achieve human level AI. But, we have a lot of smart people and I think we're making some progress."

"Well, there's certain jobs that only people can do. You can't have a machine make sweaters made by hand. And there's kinds of things which involve social interaction which only people can do. Some of the social interaction maybe machines can do. But, if you really want a human you got to have a human. And so, I'm not saying that all jobs will be replaced, but we're already seeing a trend of many and I think that trend will continue and you read people who talk about the current slow recovery, the economic situation, and many people say "Well, we've laid off a lot of people because of the recession, but in the meantime we've found out we could do some of those jobs that those people did with machines and by the way, we're not going to hire those people back." And so, I think that's going to be a continuing difficulty."

"I recorded all of that and I looked at it. I've forgotten some of the questions that were asked. Well, for example, on this Toronto thing. Remember the example in which it was asked, well the clue was World War II aviators or naval battles for which airports were named. And the answer would be Midway and Chicago and O'Hare. And it mentioned something in Toronto, I think, even though it was supposed to be a US city. And I think the people who designed it explained that well, oftentimes the category US city doesn't really mean exactly US city, it's sort of general. And so, Watson didn't count that as heavily as it should have. But, maybe it had some inaccurate common sense that allowed it to answer Toronto. But, anyway it was a failure of some sort of common sense reasoning."

"Well, if you had asked me that a few years ago I might have said "No," because I think that whatever the power of computing was at the time it was fully able to handle any of the ideas that we had at the time. I mean, we were idea short, we weren't hardware short mainly. Now, I'm not so sure because the new idea that's come up, the use of lots and lots of data, well, lots and lots of data requires lots and lots of computing. And so, the more computing, the faster it can go the better. I don't know that that's the bottleneck at the moment. After all if you talk to the Watson people which I haven't, but if you did talk to them and you asked them, "Gee, how could Watson have been better? If you had a computer, this IBM 7000 series or whatever it was, if it were 10 times as fast, 100 times as fast, 100 times as much memory would you have done better?" I think they'd still answer "Well, not necessarily. We would need more ideas about how to program all that.""

"Right now, I don't know, I think I'd try to get involved in the bridge between AI and neurophysiology. Let's take neuroscience in particular because I think there's still a lot of secrets about how the brain works that we don't understand that'll be helpful in engineering. The reason we don't understand them, I think, is we haven't invented the concepts needed to understand them. I have this analogy with computers. If you had a Martian coming down looking at computers, measuring all the currents flowing back and forth from the transistors, no amount of all that measuring, no amount of understanding how a transistor works is going to tell you how say an online banking system works or how an airline reservation system works. You have to have concepts that got invented in computer science to even understand them. You have to have concepts like lists, programs, data structures, compilers and there are probably a whole set of analogous concepts in helping us understand the brain."

"Knowledge gives us a compass, But kindness is what gets us down the road. And to quote an African proverb that one of my mentors was fond of sharing, ‘If you want to go fast, go alone; if you want to go far, go together."

"The thing that stands out in my mind is the professor showing us pictures of various shapes such as triangles and squares, pointing out how easy it was for us to distinguish them, but then asserting that nobody knew how to write a computer program to do so (to date myself, this must have been the mid ’80s). I had already started programming computers, but this got me interested in the concept of modeling intelligence with computers."

"Right, so that’s the thing. Ninety-nine percent of the people who got a one in one of their interviews we didn’t hire. But the rest of them, in order for us to hire them somebody else had to be so passionate that they pounded on the table and said, “I have to hire this person because I see something in him that’s so great, and this guy who thought he was no good is wrong, and I’ve got to stand up for him and put my reputation on the line.”"

"A machine is not a genie, it does not work by magic, it does not possess a will, and … nothing comes out which has not been put in, barring of course, an infrequent case of malfunctioning. … The “intentions” which the machine seems to manifest are the intentions of the human programmer, as specified in advance, or they are subsidiary intentions derived from these, following rules specified by the programmer. … The machine will not and cannot do any of these things until it has been instructed as to how to proceed. ... To believe otherwise is either to believe in magic or to believe that the existence of man’s will is an illusion and that man’s actions are as mechanical as the machine’s."

"For me, minimizing drag often involves saying no to things that I think would be good for external validation, but I know I am not going to enjoy doing. A recent example: I was invited to be on a panel at a high-visibility event, but I knew I wouldn’t particularly enjoy it, so I said “no”."

"I noticed that they were talking about these cases the same way I talked about some examples."

"On the flip side, I’ll often say yes to things that are somewhat “random” and won’t bring external validation, but I think would be fun to do (e.g., I agreed to do a brief interview with an effort organized by a small Indian publication for Engineer’s Day (I didn’t know that was a thing :)) or where I think I bring value (e.g., I often agree to chat with folks I don’t know who reach out to me looking for advice or perspectives on something). A lot of community-building activities pass this “minimize drag” threshold (with flying colors!) -- because I get joy from bringing value."

"Reinforcement learning has been a relatively “niche” area of AI since I became interested in it my first year of graduate school. But with recent advances, I became convinced that now was the time to move to the next level and work on problems that are only possible to attack in a commercial setting."

"I think there are more algorithms down that road — very interesting ones — but it will probably be difficult to come up with them."

"The thing is that people have tried a lot with few successes, but I don’t think that too many people have tried enough"

"If computers were human, they’d present themselves as autistic, schizophrenic, or otherwise brittle. It would be unwise or dangerous for that person to take care of children and cook meals, but it’s on the horizon for home robots. That’s like saying, ‘We have an important job to do, but we’re going to hire dogs and cats to do it.'"

"Sometimes the veneer of intelligence is not enough."

""What we needed, is nothing less than an “AI Manhattan Project”, a full frontal assault on common sense: the challenge is to create an Encyclopédia of Common sense", Michio Kaku citing Lenat."

"The time may come when a greatly expanded Cyc will underlie countless software applications. But reaching that goal could easily take another two decades."

"Intelligence is ten million rules. This refers to the prior and tacit knowledge that authors presume their readers all possess (such as "if person x knows person y, then x's date of death can't be earlier than y's date of birth") not counting the vastly larger number of "facts" such as one might find in Wikipedia or by Googling."

"Once you have a truly massive amount of information integrated as knowledge, then the human-software system will be superhuman, in the same sense that mankind with writing is superhuman compared to mankind before writing."

"Today’s quantum ecosystem is extremely vibrant, and there is a lot of energy and focus on particular questions"

"After the industry experiences, I could see startling differences between the academic and business worlds. I was most comfortable in universities, where I was able to freely learn, grow, and openly share whatever I know with people around me. In industry, information is protected, which leads to complicated games and strategies for gaining power based on who knows what. It is a difficult place to be if you enjoy sharing your knowledge and understanding, and generally helping people with their projects. I also found the Dunning-Kruger effect to cause serious problems in industry, especially when people don't know what they don't know, but have massive power over others and company directions. Both worlds clearly play important roles, but I learned that a university research environment makes me the happiest. I feel very lucky to have been able to try both at fairly high levels."

"One "occupational hazard" of being a professor is exposure to various countries, cultures, and people from all over the world. I was very fortunate to visit a few dozen countries, often hosted by people who have the same professional interests. This made me wonder what my life would be like if I had grown up there. I became attracted to Poland, where I have family heritage, and then Nordic countries. I was especially attached to Finland after teaching a short course at the University of Vaasa in 2007; I was invited by Pekka Isto, a Finnish motion planning expert."

"I think there are advantages and disadvantages to that. I would like to see more stamina from the community when it comes to looking into the more difficult questions that have less immediate reward — like, for example, deeply understanding quantum algorithms."

"In 2012-2013, I came with my family to Oulu for a sabbatical to write books and get to know Finland better. After living there for nine months, we came to deeply appreciate Finnish culture and lifestyle. It seemed that Finland naturally fit my personality. People are respectful of each other and generally cooperate in maintaining a safe, responsible, and fair society. Modesty and respect for cultural differences around the world are strongly emphasized. Education and educators are highly respected. I thought it would be perfect for raising my children, with safe, playful, and nurturing infrastructure, and where good health care and education are free rights of residents (private universities are even illegal). Relating to my profession, there is strong interest in developing advanced technology while also being respectful of nature, the environment, and wellbeing. These are the values that suit me well, and that I want my family to learn. In 2018, I was invited to become a professor at the University of Oulu, and I could not be happier. I am currently co-leading the Perception Engineering Group, which pursues problems in virtual reality, robotics, and telepresence. The university made a nice video about me, and a Finnish newspaper explains more about why I moved to Oulu. I am also involved in helping the industrial ecosystem in Finland, especially in virtual reality and its various flavors (VR, AR, MR, XR, ...)."

"One very, very interesting thing about quantum computation is that it touches so many different fields in mathematics"

"The reason I included the bits above is to explain why I always have strong empathy for people who have struggled because they are not part of the usual group in power. In my case, it was mostly about coming from a poorer, working-class family. Doing something smart would often lead to bullying. I could feel people having contempt for me as I succeeded and maybe even outperformed them, when based on my way of speaking, clothing, or whatever else, I should have been easily beaten. I really didn't care for competition; I just wanted to ensure I could be in a place where I could work with very smart, open-minded people. I am certain that others who struggle with additional issues based on race, gender, sexuality, disabilities, foreign nationality, and so on, face these problems and more. I had to learn how to speak and act differently to fit into the higher levels of society, but to this day I continue to have feelings of impostor syndrome. If you know what I am talking about, then please be sympathetic and support each other (and not only the ones in your own group)!"

"Near the end of high school, I still believed that engineers mostly drive locomotives, but my guidance counselor pointed out that with my interests in math, science, and computers, I should probably be an electrical or computer engineer. He then showed me a college guide to convince me that some school in Missouri was one of the "top" (it wasn't listed there), and I looked over his shoulder and saw the top 3 schools listed as "MIT", "Stanford", and "Illinois". He didn't seem to know anything about "Illinois", but I made it my mission to learn about it. I figured that MIT and Stanford were only for rich people from another planet, but Illinois happened to be the name of that state on the other side of the Mississippi River from St. Louis. I soon realized that "Illinois" was UIUC, which was actually the home of the fictional HAL 9000 Computer from 2001! It was to be completed in 1992 (movie) or 1997 (book), which meant I had a chance to help realize at least part of the glorious future of that movie. It took me a couple of years of complicated scheming to borrow money in every way possible to cover the triple out-of-state tuition rate. When I finally figured it out, I had to personally petition to UIUC Engineering Dean to even be allowed to apply as an out-of-state transfer student, and they said I was the only one they let in over the past decade. Persistence! I then fought for two more years to get all prior credits transferred, and finally graduated as one of the top students from Electrical and Computer Engineering in 1989."

"Around 2012, I started to get the sense that robotics as a field was gradually becoming less interested in fundamental research, and many researchers were insisting that all work should be experimental and practical. Based on my background described above, I have tended to be respectful and supportive to all communities, which made this trend disheartening. On the other hand, I thought that if one was to do something very practical, then why not just build a product in industry? Otherwise, I could not see the point of being in academia. So, I gave it at try..."

"I was born in 1968 and grew up in and around St. Louis, USA. My loving parents were often overwhelmed because I asked them questions continuously to the point of exhaustion. As a child I was inspired by the space age, with Kubrick and Clarke's 2001 exciting me with dreams of a future full of space exploration and intelligent machines (HAL 9000). No one in my family had gone to college, and nearly everyone around me was skeptical about higher education (why would you let them "educate the brains out of you?" or "After that, he ain't got no more common sense."). This made it seem nearly impossible to get on track for helping build that envisioned future. Also, while I was growing up, the space age was slowly disintegrating."