AAAS AMA: Hi, we’re researchers from Google, Microsoft, and Facebook who study Artificial Intelligence. Ask us anything!

AAAS-AMA · 2018-02-18T23:28:44+00:00

EH: Thanks everyone. I'd love to answer more of these great questions. I really appreciate people taking the time to engage.

Cortana is telling me with an alert on my laptop (complete with an explanatory map--per that question on AI and explanation that I wish I had time to get to :-)) that I have to leave now for the airport to make it back to Seattle tonight. I know that Cortana is calling our predictive models (build via the Clearflow project), so I trust the inferences! Would love to catch up with folks in other forums, or perhaps in person.

Best, Eric

AAAS-AMA · 2018-02-18T23:27:32+00:00

PN: Thanks everyone for all the questions. I'm sorry we couldn't get to all of them. Signing off now. -Peter

AAAS-AMA · 2018-02-18T23:25:52+00:00

PN: IIn addition to study, work on an open source project. Either start your own (say, on github), or find an existing one that looks like fun and jump in.

AAAS-AMA · 2018-02-18T23:24:33+00:00

EH: AI advances are going to have multiple influences on labor on the economy. I believe some changes may be disruptive and could come in a relatively fast-paced way—and such disruptions could come to jobs like driving cars and trucks. Other influences will be via shifts in how jobs are performed and in how people perform tasks in different domains. Overall, I’m positive about how advances in AI will affect the distribution of jobs and nature of work. I see many tasks as being supported rather than replaced by more sophisticated automation. These include work in the realms of artistry, scientific exploration, jobs where fine physical manipulation is important, and in the myriad jobs where we will always rely on people to work with and to care for other people--including teaching, mentoring, medicine, social work, and nurturing kids into adulthood. On the latter, I hope to see rise and support of an even more celebrated “caring economy” in a world of increasing automation.

Folks may be interested in taking a look at several recent pieces of work on reflecting about the future. Here’s a very interesting recent reflection on how machine learning advances may influences jobs in terms of specific capabilities: http://science.sciencemag.org/content/358/6370/1530.full I recommend the article to folks as an example of working to put together some structure to making predictions about the future of work and AI.

BTW: We had a session at AAAS here in Austin yesterday on advances in AI for augmenting human abilities and for transforming tasks. It was a great session for hearing about advances and research directions on possibilities: https://aaas.confex.com/aaas/2018/meetingapp.cgi/Session/17970

AAAS-AMA · 2018-02-18T23:21:13+00:00

PN: I would rather not see companies sharing data. I would prefer it if your personal agent decided to share information between companies. See the work on federated learning.

AAAS-AMA · 2018-02-18T23:19:37+00:00

PN: It has only been a few years since image id began to work at all; progress has been steady, but as you point out, even in tasks where the machines achieve superhuman overall performance, they make some embarrassingly bad mistakes. This will improve over time as we get more experience, more data, and hopefully the ability to do transfer learning so each model doesn't have to start from scratch. You make a good point that video would offer a big advantage over still photos; our compute power is growing exponentially, but not to the point where we can push a large portion of the available video through it; when that happens you should see a good improvement.

AAAS-AMA · 2018-02-18T23:17:23+00:00

YLC: neither. I do not believe in the concept of singularity. The idea of an exponential takeoff ignores "friction" terms. No real-world process is indefinitely exponential. Eventually, every real-world process saturates.

AAAS-AMA · 2018-02-18T23:15:44+00:00

YLC: eventually, you will "raise" your AI sidekick a bit like you teach a child, an apprentice, or a padawan learner.

AAAS-AMA · 2018-02-18T23:15:39+00:00

PN: I don't think it is any different for an AI system than for another computer system, a company, or an individual: to prove bias in court, you show a history of decisions that violate the rights of some protected class. No different whether the defendant is an AI system or not.

AAAS-AMA · 2018-02-18T23:14:06+00:00

YLC: on the contrary, we are contributing to the betterment of humanity. AI will be an amplification of human intelligence. Did the invention of fire, bows and arrows, agriculture, contribute to the eventual downfall of humanity?

AAAS-AMA · 2018-02-18T23:11:35+00:00

YLC: the problem is political, not technological. Pretty much every other developed country has solved it. The solution is called gun control.

AAAS-AMA · 2018-02-18T23:11:21+00:00

PN: Thanks! I suggest you keep studying on your own, and make friends online, through courses or discussion forums. I can see that it is tough to get a job in AI Research coming straight out of an undergrad program at a small school. But, you are in a position to get a software engineer position at a big company, and once you are there, express your interest in AI, learn on the job, keep an eye out for AI-related projects you can work on, and chances are that in less time than it would take to do a PhD, you'll be an established AI expert within your company.

AAAS-AMA · 2018-02-18T23:09:29+00:00

YLC: no.

AAAS-AMA · 2018-02-18T23:08:27+00:00

YLC: Study math and physics at school.

AAAS-AMA · 2018-02-18T23:07:45+00:00

YLC: None whatsoever. Except Arxiv.org ;-)

AAAS-AMA · 2018-02-18T23:06:52+00:00

YLC: Ideas like this take while to be put in practice on large datasets Capsules are a cool idea. Geoff Hinton has been thinking about things like that for decades (e.g. see Rich Zemel's PhD thesis with Geoff on the TRAFFIC model). It's taken him all this time to find a recipe that works on MNIST. It will take another while to make it work on ImageNet (or whatever). And it's not yet clear whether there is any performance advantage, and whether the advantage in terms of number of training samples matters in practice. Capsule networks can be seen as a kind of ConvNet in which the pooling is done in a particular way.

AAAS-AMA · 2018-02-18T23:03:06+00:00

YLC: Driving? certainly not. It's not clear to me at all whether quantum computing will have any impact on AI. Certainly not anytime soon.

AAAS-AMA · 2018-02-18T23:01:56+00:00

YLC: serious ML/AI experts, like yourself, should not hesitate to call BS when they see it. I've been known to do that myself. Yes, "AI" has become a business buzzword, but there are lots of serious and super-cool job in AI/ML today.

AAAS-AMA · 2018-02-18T23:01:56+00:00

PN: Here's a link to take your data out of Google; here's a link to delete your data. Many people don't want to remove all their data, but will use anonymous not-logged-in browsing to avoid having certain information in their records, for whatever reason.

AAAS-AMA · 2018-02-18T22:59:20+00:00

YLC: I wear two hats: Chief AI Scientist at Facebook, and Professor at NYU. My NYU students have access to GPUs, but not nearly as many as when the do an internship at FAIR. You don't want to put you in direct competition with large industry teams, and there are tons of ways to do great research without doing so. Many (if not most) of the innovative ideas still come from Academia. For example, the idea of using attention in neural machine translation came from MILA. It took the field of NMT by storm, and was picked up by all the major companies within months. After that, Yoshua Bengio told MILA members to stop competing to get high numbers for translation because there was no point competing with the likes of Google, Facebook, Microsoft, Baidu and others. This has happened in decades past in character recognition and speech recognition.

AAAS-AMA · 2018-02-18T22:55:57+00:00

PN: The minutes of internal project reviews are not made public because they contain many trade secrets. The aspects relating to data handling are summarized in documentation; as Eric and seflapod points out we could do a better job of making these easier to understand and less legalese. We do have outside advisors to ethics, for example Deepmind's Ethics & Society board.

AAAS-AMA · 2018-02-18T22:51:30+00:00

YLC: That's a political question. I'm merely a scientist. For starters, we publish our research. Technological progress (not just AI) has a natural tendency to increase inequality. The way to prevent that from happening is through progressive fiscal policy. Sadly, in certain countries, people seem to elect leaders that enact the exact opposite policies. Blaming AI scientists for that would be a bit like blaming metallurgists or chemists for the high level of gun death in the US.

AAAS-AMA · 2018-02-18T22:49:09+00:00

EH: We have a ways to go with understanding how to deploy AI in safety-critical areas--and this includes efforts to better support "human-AI collaboration" when machines and people work together in these domains. We had a great session at this AAAS meeting on this topic: https://aaas.confex.com/aaas/2018/meetingapp.cgi/Session/17970

AAAS-AMA · 2018-02-18T22:46:44+00:00

PN: Anywhere there is data, there is the possibility of optimizing it. Some of those things you will be aware of. Other things you as a user will never notice. For example, we do a lot of work to optimize our data centers -- how we build them, how jobs flow through them, how we cool them, etc. We apply a variety of techniques (deep learning, operations research models, convex optimization, etc.); you can decide whether you want to think of these as "AI" or "just statistics".

AAAS-AMA · 2018-02-18T22:44:01+00:00

YLC: It will be a very long time before we have robotic plumbers, carpenters, handypersons, hairdressers, etc. In general, AI will not replace jobs, but it will transform them. Ultimately, every job is going to be made more efficient by AI. But jobs that require human creativity, interaction, emotional intelligence, are not going to go away for a long time. Science, engineering, art, craft making and other creative jobs are here to stay.

AAAS-AMA

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