Aug 29, 2018
I spent the past week in Prague (natively called Praha, but known widely as Prague via the usual mechanisms others decide your own names) at the Human Level AI multi-conference held between the AGI, BICA, the NeSY conferences. It also featured the Future of AI track, which was my proximate reason for attending to speak on the Solving the AI Race panel thanks to the selection of my submission to GoodAI's Solving the AI Race challenge as one of the finalists. I enjoyed the conference tremendously and the people I met there even more, and throughout the four days I found myself noticing things I felt were worth sharing more widely, hence this field report.
I arrived on Tuesday and stayed at the home of a fellow EA (they can out themselves in the comments if they like, but I won't do it here since I couldn't get in touch with them in time to get their permission to disclose their personage). If you didn't already know, Prague is rapidly becoming a hub for effective altruists in Europe, and having visited it's easy to see why: the city is beautiful, most people speak enough English that communication is easy for everyone, the food is delicious (there's lots of vegan food even though traditional Czech cuisine is literally meat and potatoes), and it's easily accessible to everyone on the continent. Some of the recent events held in Prague include the Human-aligned AI Summer School and the upcoming Prague AI safety camp.
Wednesday was the first day of the conference, and I honestly wasn't quite sure what to expect, but Ben Goertzel did a great job of setting the tone with his introductory keynote that made clear the focus was on exploring ideas related to building AGI. We then dove in to talk after talk for the next 4 days, each one considering an idea that might lie on the path to enabling general intelligence for machines, and we doubled-up on the third day with a Future of AI program that considered AI policy and ethics issues. I took a lot of notes, but being a safety researcher I'm hesitant to share them because that feels like a hazard that might accelerate AGI development, so instead I'll share a few high-level insights that I think summarize what I learned without saying anything with more than a very small (let's say < 5%) chance of giving someone a dangerous inspiration they wouldn't have had anyway or as soon.
To summarize, I think the main takeaway is that we, being the sorts of persons who read LessWrong, live in a bubble where we know AGI is dangerous, and outside that bubble people still don't know or have confused ideas about how it's dangerous, even among the group of people weird enough to work on AGI instead of more academically respectable, narrow AI. That's really scary, because the people outside the bubble also include those affecting public policy and making business decisions, and they lack the perspective we share about the dangers of both narrow and general AI. Luckily, this points towards two opportunities we can work on now to mitigate the risks of AGI:
These interventions are more than I can take on myself, and I don't believe I have a comparative advantage to execute on them, so I need your help if you're interested, i.e. if you've been thinking about doing more with AI safety, know that there is concrete work you can do now other than technical work on alignment. For myself I've set an intention that when I attend HLAI 2020 we'll have moved at least half-way towards achieving these goals, so I'll be working on them as best I can, but we're not going to get there if I have to do it alone. If you'd like to coordinate on these objectives feel free to start in the comments below or reach out to me personally and we can talk more.
I feel like I've only just scratched the surface of my time at HLAI 2018 in this report, and I think it will take a while to process everything I learned and follow-up with everyone I talked to there. But if I had to give my impression of the conference in a tweet it would be this: we've come a long way since 2014, and I'm very pleased with the progress (Superintelligence ⇒ Puerto Rico ⇒ Asilomar), but we have even further to go, so let's get to work!