AIRCS Workshop: How I failed to be recruited at MIRI.

Crossposted from LW website This blog post will touch on two related topics:

1) Why and how I applied to MIRI and failed to secure an internship. 2) My experience at the AI Risk for Computer Scientists workshop (AIRCS).

If you're only interested in the AIRCS workshop, you may skip to the second section directly. Ideally, I'd have liked to make two separate entries, as they may pertain to different points of interest. However, both topics are extremely intertwined to me, and I could not make a clear cut in this experience. I should also note that me failing to secure an internship at MIRI probably have had a drastic impact in how I write about it, if only because I'd have been more constrained in what I describe had I got the internship.

With respect to people's name, I'll adhere to the following rule: Only mention names if what they said was done so publicly. That means that for books, facebook public pages or lectures, I will assume I can use the name of the author or teacher, and I will keep the name to myself for private discussions.

Miri and me.

I discovered MIRI through Eliezer Yudkowsky, as I first began reading HPMOR and then Rationality, from A.I. to Zombie. Like almost everyone, I'm not sure what it is MIRI exactly do. I know at least that MIRI's intended goal is to save the world from unaligned AGI. But whatever it is they concretely do, it seems quite fun - I mean, it seems to involve type theory and category theory. I also read some articles they wrote, and skimmed through many other. While interesting, I've never caught enough details to actually imagine how to even start implementing anything they speak of. Reading some of their writings reminded me of several epistemology books I read years ago, but written more precisely, with clear code in mind, and to a computer-science-savy audience.

As I said, fun stuff, fun work!


In February 2019, Eliezer Yudkowsky shared on facebook a post by Buck Schlegeris stating that "I think that every EA who is a software engineer should apply to work at MIRI, if you can imagine wanting to work at MIRI." (and some more stuff). When I read that, I thought I should give it at least a try. I really didn't know how I could have helped them given my professional background - mostly logic and automata theory - but if they say that we should give it a try anyway, let's. I must admit that I was still skeptical back then, and didn't know exactly what they do, but I thought I would eventually come to get it. And even if it did not seem that they'll save the world from anything in the end[1], it still seemed a place I'd have loved to work at, assuming they are similar to the less wrongers I met at the european LessWrong community week-end.

Note that Buck Schlegeris's message does not directly concerns me. I'm not EA, but only EA adjacent. I still fail to see any effective actions I could take appart from giving some money, and when I applied for 80k career coaching, they told me they couldn't help[2]. It also does not concern me because I used to be a post doc researcher who sometimes programmed, and not a software engineer in itself. But I wanted to let them decide wether I'd be a good fit or not.

The application process went as follows: First it started off with a triplebyte quizz. This one was extremely easy. I think there was at most two questions which answers I didn't know. The second part was two one hour calls with a MIRI researcher. The first call was a general presentation of myself, how I've heard of MIRI, why I am interested in working there, what were my past experiences, and so on. I told the interviewer something such as:

I am not even convinced that MIRI's work is important. At best, I am convinced that you were convinced that it is important. But even if EY is a good writer who I admire, the fact that he his set on the importance of his mission is not sufficient for me to think he is right. Furthermore, MIRI gets money by convincing people that their work is important, which means that MIRI has a strong incentive to be persuasive, whether or not your beliefs are true, and whether or not you still hold that belief. I do believe that when MIRI was created, it was not clear they would ever get money. If EY is as good as he seems to be when he writes, he could probably have cashed money in in far easier ways. So the best argument I have currently regarding AGI alignment's importance is that the founders of MIRI thought it was important at the time of MIRI's creation.

Honestly, after saying all of this, I thought my application was over and we would have stopped there, but it seemed okay with him. The second interview was more technical, the interviewer asked me plenty of questions on various topics pertaining to computer science, programming and theory. He also gave me a short programming exercice, which I succeeded (I won't tell you what the questions and exercice were for obvious reasons). I should emphasize that my answers were far from being perfect. When discussing with friends I learned that I had got some answers wrong; I had questions related to the Coq language for instance, I gave the closest answer I knew, which was haskell/ocaml related while Coq's construction was greatly generalized as far as I understand it[3]. One question asked me how I would create a data structure allowing to have an efficient access to some functions. I gave a correct answer, I knew that the worst time complexity was logarithmic, but was not able to prove it. After the interview, I did realize that actually the proof was extremely easy.

The interviewer told me that, before taking a decision, MIRI wanted to meet me at a workshop, so they invited me to AIRCS, and that they also wanted me to take a 2 day long programming test. I still don't understand that: what's the point of inviting me if the test fails ? It would appear more cost efficient to wait until after the test to decide whether they want me to come or not (I don't think I ever asked it out loud, I was already happy to have a trip to California for free). I want to emphasize that at this point, I still had no idea of why they had found my application interesting, and what I would actually do if I worked for them. I kind of hoped that I'd get an answer eventually. I was noticing my confusion, as a good rationalist should do. Alas, as always when I notice my confusion, I stay confused and can't figure out what to do with it.

Last part of the interview was a two day long programming problem. There was a main programming task, with two options, I did only one of them. I mean, the second one seems way more interesting, but with my knowledge today, I fear that I would have needed a week to really read enough and implement it correctly. As I told my interviewer, it relates to a topic I do not know well. There was one thing which I had particularly appreciated: I was being paid for the whole time doing this programming exercice for them. This is a practice I've never seen elsewhere. I do not wish to disclose how much I have been paid, but I'll state that two hours at that rate was more than a day at the French PhD rate. I didn't even ask to be paid; I hadn't even thought that being paid for a job interview was possible. The task had to be done in 14 hours, i.e. after 2 days of 7 hours work each. I did not know if that rate also applied to me being an intern, but that salary was nice regardless, especially since they'd paid very quickly - it takes three months for every payment back in France. [4] As a quick note here: thank you to everyone who gave at MIRI :p.

Since it seemed that MIRI was actually interested in my application, I believed that I should read more about MIRI. I was mostly reading what MIRI wrote, but to have an informed opinion, I thought I should read what other people wrote about it. Sometimes, EY made fun of the sneer club on twitter. I also saw a copy of an email sent to a lot of people related to CFAR about some creepy stuff that allegedly occurred at MIRI/CFAR. I wanted to get an idea of what I was getting myself into, so I started to browse through all of it. My inner Slytherin argues that the sneer club is filled with rationalists who posts non important stuff so that the actual important stuff get lost in the middle of everything else. I'm not going to write down everything I've read, but let me write a few examples as to explain of why I still went through with the application process. I've read that MIRI's work is not important, this one I might agree with but if I'm getting paid and there is only a one percent chance the work is important, that's still way XXXway?XXX better than most other job I can find now. Miri is male-dominated... well; according to their "team" page, it's hard to argue with this one too, however, given that I'm looking for a job as a computer programmer, I fear that's a problem I'll have everywhere. "At a MIRI's workshop, some guy touched a woman without her consent, and did it again after she asked him to stop and he was banned for this". I do not want to belittle the importance of sexual assault, but if MIRI's reaction was to bam him, I guess that's better than most conference I've heard of. I have no more details, so I don't know how easy it was to report the assault to staff, but I assume that if there were any problem here, the author would have wrote it. I also read that some people have mentioned the idea that infohazard could be used to blackmail people. I kind of assume that less wrong/rationality groups is the best place for this kind of scams, but I'm still okay with this, especially since I have not heard of people actually implementing the idea.

Long story short: it's quite hard to believe that LW/MIRI is a cult (after all, they ask for money to save the world). But since I was actually being offered things by them and obtained the best wage I ever had for the working test, it was hard to be frightened by this cult-idea. And while I sent a few hundreds euros to Berlin's LW community, it was used to pay 3 nights at an hostel, and 4 days of food, so I highly doubt there are making huge profits on it.

Let's now skip a whole month and go to AIRCS.

AIRCS

Before discussing AIRCS, I want to stress this is a personal view, which may not represent the way anyone else felt about AIRCS. In particular, the fact that, after meeting me at AIRCS, I received an email telling me I won't have an internship at MIRI have probably affected my views. At least because I would probably have been more MIRI aligned if I was actually at MIRI nowadays. I tried to write as much as possible before receiving MIRI's answer to remain as "objective" as possible, however they were quite quick to answer, and I'm a slow writer. And anyway, as you'll see below, the simple fact that I was at AIRCS to help them decide whether they hire me or not meant that my experience was distinct from the others'.

Now that this is written down, I can begin to describe AIRCS.

Normal life

Before going into activities in the workshop's planning, I'm going to speak of the workshop generally. After all, the workshop was 5 night and 4 day long, so of course we've spent times doing other stuff. Usually, there were 1h10 long activities separated by 20 minutes breaks, while lunch and dinner breaks were longer. The last night was an "after party" instead of workshops, and we had two breakout sessions prior. In those, people were free to offer whatever they wanted. There was a lecture about category theory and quantum circuits if I remember correctly. There was some coding in Haskell. I said I would gladly do an introduction to Anki, but no one found this more interesting than the other stuff - This still led to some anki-related questions later by some participants. During some breaks, there were "two minutes clean up", where everyone were cleaning whatever they saw near them. Usually, the clean up were announced in the main room, which means that people far from it didn't hear it and so didn't clean what was near them. Since most of the disorder was actually in the main room that was not an issue. At the end of the two minute cleaning, we resumed the break.

AI Risk for Computer Scientists is a worskhop which, as far as I can tell, is not really for computer scientists. A facebook friend of mine, president of EA France, told me she was invited even though she had a PhD in economics and is not doing any computer science. Most of the people there were computer scientists, however, and most of the non-computer scientists were mathematicians. A lot of the small talk was related to math and computer science and were often far more technical than the workshops themselves, which was quite unexpected to me. Edward Kmett was there and spoke a lot about haskell and theories behind programming languages, which was extremely interesting and not related at all to AI.

A lot of people at the event were vegan, and so at each meal, there was a huge choice of good vegan food, which is incredible to me ! So I was even more intrigued as to why we almost exclusively used throw-away utensil, plates and bowls; as most vegan texts I've read are about how meat arms the environment. I assume that if EA cares about animal suffering in itself, then using throwaways is less of a direct suffering factor.

I had at least four goals arriving at this workshop: - The first one was to discover what could actually be done to advance research related to AI safety. - The second one was to understand why people believe that there is such a high risk that an unaligned AGI will be created in the foreseeable future. - The third one was to get an internship at MIRI; and thus to draw a salary again. - The last one was to discover and enjoy California, the bay area, and this rationalist community I've read a lot about.

Task four is mostly a success, task two is kind of a success and the other two tasks are complete failures.

Workshop activities

Almost all activities were done in small groups, with either a half, a third or a fourth of all participants and so the lectures/activities were repeated two to four times during the day. This way, we all had done the same activities, and being in small groups also allow to have real discussions with the professor and the other participants. Groups were changing a lot, so that we also met all participants.

As far as I understand it, plenty of people are panicked when they really understand what AI risks are. So Anna Salamon gave us a rule: We don't speak of AI safety to people who do not express the desire to hear about it. When I asked for more informations, she specified that it is okay to mention the words "AI Safety"; but not to give any details until the other person is sure they want to hear about it. In practice, this means it is okay to share a book/post on AI safety, but we should warn the person to read it only if they feel ready. Which leads to a related problem: some people never experienced an existential crisis or anxiety attack of their life, so it's all too possible they can't really "be ready". On the same note, another researcher at MIRI answered me -when asked as to why they don't hold a lecture explaining the imminence of AI- that they do not want to be the one explaining to everyone why we're all going to die in the next few decades. On the one hand, I guess I understand why, but on the other hand, I'd say it's kind of the point of being there !

To give a more concrete example of how they tried to fight potential panic: during one of the activity, Anna Salamon asked us to list all the reasons why it could be a bad idea of thinking about AI risk. An obvious answer was that thinking about AI may help AGI be created, and so our defeat would come sooner. Another answer, as explained above, would be that some people would panic and not be able to do anything anymore. One of my answer was about a theory we are not allowed to discuss, which if it were true would mean that it's a very bad idea of thinking about it altogether. However, as I expected, she didn't write in on the white board. I still felt that to be exhaustive, I had to mention it to her.

As you can see, the staff really cared about us and wanted to be sure that we would be able to manage the thoughts related to AI risk. This led to a lot of talks which were not directly related to AI. Given the importance of non AI-related talks, I'm going to start to describe the workshop by listing examples of activities which were not AI related.

Non AI related events.

I do not know how much of the stuff we saw is usual at CFAR. There were talks on bucketing, inner sim, world models, question substitution, double crux, focusing... I'm not going to try to explain all of this, as I would probably do a bad job; just go to a CFAR event to learn about them. Or read their book, it seems they just published it. To test those tools, we had to apply them to specific problems; either an AI-related problem, or a personnal one. I don't even know how to start thinking about AI problems, so I decided to choose personal problems.

Sadly, there has been some timing issues, and the professor usually did not have the time to see every participants to help them with the exercices.

If all of this helps to think clearly about problems and how to solve them, then it seems strange to me that CFAR uses it only for AI stuff. If it does help to deal with the horror of unaligned AI, why isn't it used to speak of global warming ? While I admit that the narrative about AI risk is even worse than the one about global warming, I do think that if you really try to grasp the whole impact of global warming you also need some mental help to consider the horror it entails. The same thing would also be true if you want to consider global poverty, slavery, and so many other things in our world.

There were also a lot of so-called "circle". I've heard that circles are not usually done at CFAR, because circles are less effective at mainstream workshop than in AIRCS workshop. We've been told when we started circling that we would not really learn what circle is, that all circles are different. That we could see plenty of circles and they would not seem similar, the same way we could discover a lot of music and think that there is nothing in common between them. For a computer scientist, this did seem extremely strange and dubious. How can I evaluate whether the exercice was correctly done or not ? Or even what was the purpose of this exercice ? As far I as understand, one goal of the circle is to be able to get what we feel and to put words on it. In particular, circle is also about going meta, and being able to think about the current thinking process. I do feel like that's something I was already quite good at, it looks a lot like blogging - I mostly blog in French, so most of you could not really check out yourself. When I want to write about something and fail, I usually try to understand what my problem is; and then I write to explain what I would have liked to write and why I failed doing it. This is also something I really often do with one of my partner; which leads to conversations too meta for my taste sometime, but which helps discussion in the long run. My point here is that it felt so much like something I often do that I didn't really felt like it was new for me. Or maybe I just didn't understand what circling is and just used instead something I already knew. Who knows ? There were two circles in small group the first two days, and a big long circle with everyone the third day. Someone had been more vocal and honest than myself, and asked why we were doing this. We only have four days, they said, and we are supposed to be talking about AI. Personally, I decided to trust MIRI and to suspend my judgement, expecting that at some point I'd get the meaning in all of this.

Job interview

Okay, let's go back to the job interview part. You'll now understand why both «describing AIRCS» and «applying at MIRI» had to be in the same blog post.

I ask you to remember that I was actually at AIRCS because MIRI wanted to meet me before any decision on hiring me. That means that, during circles, I was asked to be as honest as possible about my feelings while also being considered for an internship. This is extremely awkward. Similarly, to discover CFAR tool, they asked us to consider a personal problem we currently have. One of my biggest problem is about having a salary again, which probably means having a job. Other personal problems (like finding a town where I want to live in) are extremely related to the problem of having a job. But the staff member teaching us CFAR materials may also eventually have to give their reading on me. Which means that the person to help me learn how to solve my problems is potentially a part of the problem's solution. The last day, we had to fill a feedback form about the workshop... That is, they asked me to fill a feedback from about a part of my job interview BEFORE I actually had any answers [5].

All of this was extremely awkward. And it really made the workshop hard to enjoy, as I spent time and time again wondering how I should talk about those problems, while talking about them could effectively change my chances of having the job.

I appreciate and entirely realize that the AIRCS workshop is not just a recruiting process. I do believe that all staff members were honest in saying there were meeting people, teaching interesting stuff, and that no one was actually taking notes on me. No one had any thought process focused on me either. The first time I spoke of this problem to someone from MIRI, during a 1-to-1 discussion, he told me that I should not consider this as a job interview but at a place to socialize and potentially network. But just because they do not think of AIRCS as a job interview does not mean AIRCS is not a job interview. Case in point: half a week after the workshop, the recruiter told me that "After discussing some more, we decided that we don't want to move forward with you right now". So the workshop really was what led them to decide not to hire me.

To be more exhaustive, there is a second possibility; maybe after the 2 days long exam, the recruiter already knew they would not hire me. However, they do want to have a lot of people attending AIRCS for reasons I'll discuss later. Thinking that I would not be interested in attending if I knew I didn't have the job, they didn't let me know. However, this would require the recruiter to be able to lie really consistently during the whole workshop, which would be quite impressive.

During a trip to the beach, I finally had the courage to tell the recruiter that AIRCS is quite complex to navigate for me, when it's both a CFAR workshop and a job interview. I assumed that, since the MIRI wanted honest communication, telling them my thoughts would be the best I could do anyway. They answered that they see how having activities such as circles could be a problem, but that there was nothing they could do. I answered two things. First: they could mention people coming to AIRCS for a future job interview that some things will be akward for them; but that they have the same workshop as everyone else so they'll have to deal with it. And I also answered that my problems would be solved if I had an answer already. Since I did know that there was no way for them to already confirm that I had the internship, the conclusion would have been that the workshop would be nicer if they could confirm I was not going to get it. I immediately added by reflex that I was not asking for it. That I was just being exhaustive. I was dishonest then, I was pretty sure I wouldn't have the job, and actually knowing it would have made things quite simpler. However, I had the feeling that asking this would have decreased my probability of being hired, and so I avoided doing it. Furthermore, I do understand why it's generally a bad idea to tell unknown people in your buildings that they won't have the job. Some may react pretty badly, and damage your properties. There was no way for me to convince them that it would be safe to tell me I would not get hired if it were the case. Furthermore, other people were there in order to work at MIRI, and he could not just give informations to me and ignore everyone else.

I do not believe that my first advice will be listened to. During a discussion, the last night near the fire, the recruiter was discussing with some other miri staff and participants. And at some point they mentioned MIRI's recruiting process. I think that they were mentioning that they loved recruiting because it leads them to work with extremly interesting people, but that it's hard to find them. Given that my goal was explicitly to be recruited, and that I didn't have any answers yet, it was extremely awkward for me. I can't state explicitly why, after all I didn't have to add anything to their remark. But even if I can't explain why I think that, I still firmly believe that it's the kind of things a recruiter should avoid saying near their potential hire.

AI-related activities

Ok, now, let's go back to AI related activities. The disparity in the participants' respective knowledge was very impressive to me. One of the participants was doing a PhD related to AI safety; while another one knew the subject so well that they could cite researchers and say that "in research paper A, person B states C", and that was related to the current discussion. And some other participants were totally new to all of this and came there by pure curiosity, or as to understand why EA spoke so much of AI. While the actual activities were created to be accessible to everyone, the discussions between participants was not always so. Because of course, people who already know a lot about those topics speak of the facts they know, they use their knowledge when they discuss with the staff.

Most discussions were pretty high level. For example, someone presented a talk where they explained how they tried and failed to model and simulate a brain of C. Elegansis. A worm with an extremely simple and well understood brain. They explained to us a lot of things about biology, and how they had been trying and scanning precisely a brain. If I understood correctly, they told us they failed due to technical constraints and what those were. They believe that, nowadays, we can theoretically create the technology to solve this problem. However there is no one interested in said technology, so it won't be developed and be available to the market. Furthermore, all of their research was done prior to them discovering AI safety stuff so it's good that no one created such a precise model of a - even if just a worm - brain.

Another talk was about a possible AI timeline. This paragraph is going to describe a 70 minutes-long talk, so I'll be omitting a lot of stuff. The main idea of the timeline was that, if you multiply the number of times a neuron fire every seconds, the number of neurons in the brain, the number of living creatures on earth on one side, and if you multiply the number of processors, their speed, and the memory of computers on the other, then you obtain two numbers you can compare. And according to this comparison, we should have been able to simulate a human with today's supercomputer, and tomorrows computer. Similarly, with tomorrows supercomputer we should be able to simulate the whole evolution of life. However, it seems no one did anything close to those simulations. So, Buck Shlegeris, who gave the talk, asked us: "all of this are just words. What are your thoughts" and "what's wrong with this timeline" ? Those are actually questions he asked us a lot: he wanted our opinions, and why we disagreed. That's quite an interesting way to check how we think I guess, and an extremely hard one to answer. Because there were so many thing wrong with the talk we head. I think I answered that one does not only have to simulate brains, but also all of their environments. And the interactions between brains, as opposed to just each brains in their own simulation. But honestly, my real answer would be that it's just not how science and technology works. You can't just hand wave ideas and expect things to work. By default, things do not work. They work when an actual precise effort have been made, because someone had a plan. I used to teach introduction to programming; and the talk reminded me of some of my students asking why their program does not work - while I was trying to understand why they believed it would work in the first place. Even with parallel super computer, having a program simulating the evolution from a single cell to humanity is a task that does not seems trivial, and there is no reason for it to have occurred by itself. The fact that this does not occur is the default. I guess I could also have answered that most programs bugs when they start, and if you need to use super computer for weeks, even a really passionate hacker is not going to have enough resources today to actually do this work. However, I didn't gave this long answer; I didn't feel like it was something I could easily convey with words. That the whole point made no sense. And it probably would not have helped my recruitment either.

AI Discussion

I'm not going to list in details every lectures. One major aspect of it however, is that even after all of them I didn't know what one can concretely do to help with AI safety/alignment problems. Neither did I know why they believed that it was such a high risk. So I went to speak with staff members directly and asked them those questions. One staff member told me that I could go to AI alignment forums, read on the problem they were discussing and, if I had any ideas, write them down. If I had been really honest, I would have asked "why do you want to hire developers, I was hoping to learn that, but I still have no ideas as to what I would be doing if hired". I did not. Because at some point it felt like it was of bad taste to recall that that was my initial goal, and I was pretty sure that I would not be hired anyway.

It would be interesting to read the forum and thinking about those questions myself. As I wrote earlier, MIRI's stuff does seem fun to consider. But then again, there are tons of fun stuff to consider in the world, and plenty of things I don't know yet and want to learn. Currently, what I must learn, I believe, is what will help me have a job. It won't save lives. But it is an interesting perspective to me. And even once I have a stable job, there will be so much more things to be curious about; I'm not sure that I'll just take the time to work on AI. After all, if they don't think I can help them by doing this full-time, I don't see how I could help by doing it part-time.

The question I asked most during discussions was something along the line of :

I do agree that an unaligned AI would be extremly dangerous. I will accept the idea that spending the career of a hundred researchers in my field is totally worth it if there is even a two percent chance of having every life destroyed in the next century. Can you explain to me why you believe that the probability is at least two percent ?

I think that I was being quite generous with my question. Low probability, high time-frame. According to Anna Salamon's rule I gave earlier, if you don't feel ready to hear the answer I received, and understand why there is such a risk, you should skip to next section.

The first person who answered this question told me they had followed the recent progress of machine learning and thought that we are less than ten breakthrough away from AGI. So it is going to occur imminently. It also means that I can't get convinced the same way as I have not seen the speed of progress of the field. Another answer I got was that there is so many progress going so quick that AGI is bound to occur. Personally, I do agree that progress is quick; and I expect to be amazed and astonished multiple time again in the years to come. However, it does not necessarily means that we are going to reach AGI. Let's say that the progress is going exponentially fast, and that AGI is aleph_0 (the smallest uncountable ordinal). Then the speed does not really matter, the function can't reach aleph_0. I've been answered that anyway, even if AI gets stuck again and fails to reach AGI, we will reach AGI as soon as we know how to model and simulates brain. I must admit that I found Age of EM extremly interesting as well as frightening. However I have no certitudes that we will reach EMs one day. In both cases, AGI and EMs, I see the same problem: I can imagine that we need fundamental breakthrough to make real progress. However, while private companies are happy to do more and more amazing technological creations, it does not seems to me that they are willing to do decade-long researches which won't bring back any money in the next few years. If you need a biological/chemical discovery which requires something as large as the hardron collider, then I don't see any private company financing it. Especially since, once the thing is discovered, other companies may use it. On the other hand and as far as I know, universities have less and less fundings worldwide, and professors need to be able to justify they'll publish papers soon and regularly. All in all, I really don't think research is going to be able to make fundamental important discoveries that would allow to create a new kind of science probably required for AGI/Ems. I held this last discussion just after the introduction to «double crux». And I don't know whether this introduction helped, but after this discussion, I understood that one big difference between me and most of the staff is that I'm far more pessimistic about the future of research than they are.

The point of the workshop

Some people asked what was the point of the workshop. Why had MIRI paid the travel and food of ~20 participants, and provided the staff to work with us. It was supposed to be about AI and we spent a lot of time doing circles. We didn't really learn how to help with alignment problems. I'm going to write down some answers to that that I heard during the workshop. It is beneficial to see a lot of things that are not related to AI, because we need to have a really big surface in order to interact with plenty of parts of the world (this is a chemical reaction metaphor). Maybe some useful ideas will be coming from some other fields, fields that are not yet related to AI safety. So the AI safety field need to interact with a lot of people from the outside. Some people might get interested enough to actually want to work on AI safety after this workshop, and go to MIRI or to some other places which work on those stuff, such as CHAI, FHI, etc. Some people may come to AIRCS alumni workshop, where they get more technical (I've not yet seen anything related to the alumni workshop, and I doubt I'll ever be invited - I didn't really give any new ideas in the first workshop). Also, if at some point they need a lot of people to work on the alignment problem, they'll have all the AIRCS alumni they can contact. AIRCS alumnis have been introduced to their ideas and could start working quicker on those topics. However, I didn't understand why they would suddenly need so urgently a team to work on the alignment problem (and it sounds a little bit Terminator-ish).

Now, there is a second question: what was the point of me going there. I mean, I went there because I was invited and curious. But what was their goal when inviting me ? While I was not told exactly why my application was rejected after the workshop, I have strong intuitions about it. First, I was not able to participate in discussions as much as the other participants did. As I said a lot of time, I am not convinced that the risk is as high as they perceive it. And I found that most talks were so high levels that there was no way for me to say anything concrete about them. At least not without seeing how they actually would try to implement things first. Worse, I was saying all of this out loud! A staff member from MIRI told me that my questions meant I didn't really understood the risks. And understanding them is, supposedly, a prerequisite to be able to work on AI alignment. So it was easy to conclude that I would not get the internship. But all of this was already known to the recruiter after the first screening we had. I already told him I skimmed though MIRI's post but had not had read a lot. And I was not even convinced that it was a serious risk. We already had a discussion where they tried to understand my thoughts on this, and why I did not believe in the scenarios they were depicting. As I wrote in the introduction, I notice I am confused and I'm quite perplex by the fact that my confusion has only increased. Every time a company decides not to hire me, I would love to know why, at least as to avoid making the same mistakes again. Miri here is an exception. I can see only so many reasons not to hire me that the outcome was unsurprising. The process and they considering me in the first place was.

The confusion does not decrease.

Notes

[1] Most probable ending. Because either someone crafts an unaligned AGI by not taking MIRI's position into consideration, or because AGI is impossible

[2] I still wonder why. I assume there are already a lot of computer scientists wanting to have an impact, and that they specialize more in the US and UK whereas I was in France back then.

[3] My friend tells me that actually, it's not even a generalization. Both concepts are unrelated, appart that they have the same name.

[4] There are actually teacher assistants who are still waiting for their 2018-2019 salary.

[5] To be honest, at this point, I was pretty sure I wasn't going to have the job. But not quite sure enough to feel comfortable about it.

Learning how to play music with anki

I've been playing music for half of my life. But while I was enjoying sight reading partitions, and sometime practiced a little bit the boring part (scales, arpeggios), I have been stuck. Here is a list of what changed:

  • The most frustrating thing for me being that I relied on partitions. Which means that if you gave me a piano or guitar without a partition, I wasn't able to play anything. I found that ridiculous, and anki helped me solve that.
  • Similarly, I played classical guitar, and I didn't know how to read tab. Because, honestly, they are so many chords, I keep forgetting them. Which means that, if you give me a song with tab, as they are hundred of thousands of them, I couldn't play it, because it was not written in a way I can easily read. I don't know every single chord yet (and I'll probably never know them all), I know far more chords today than what I knew before I started anki, and it clearly helps learning songs and doing improv.

The example in this post are related to ocarina, guitar, piano, harmonica and tin whistle. I will explain what differs and what is similar for all of those instruments. Some explanation may not always be clear, if you don't know the instruments I'm talking about. But don't worry, if you don't understand, just read the next paragraph, you should be able to get the general idea.

This article will be illustrated using almost only cards that I have really seen the day I was writing this article. You can find here my [piano], [guitar] and [ocarina] decks. They are far from being perfect, some typos may still be in them. But it may help you to understand what I write here. And maybe you can find them useful in your collection.

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Anki and learning which require practice (origami, knot, instrument...)

I use anki to learn things which require practice. Origami, drawing, music, rope (nodes and shibari). Music will be considered in another text.

I consider two kinds of practical knowledge:

  • some practice requires making choices regularly (like drawing, or musical improv)
  • some practice requires learning and practicing some exact moves over and over. That may be the case when you want to learn a musical piece, or how to tie some particular note.

I don' have any idea how to deal with the first kind of knowledge, thus I'll only consider the second kind. I'll list here different methods, which depends on what I want to learn. I don't know in general how to decide which method is the best one.

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Lists in anki: desiderata and partial solution

In this text, I assume you are familiar with anki, and in particular know what is a field, a card, a card's type (aka template), a note and a note's type (aka a model), and that you have an idea of what are the rules used by anki to decide which cards should be generated or not.

There is one big limitation in anki, it concerns lists[1]. Here I list my trouble, the existing work arounds I know, their limits, and the functionnality I would really want. Sadly, this functionnality seems to require such a big modification of anki's underlying model that I fear that no add-on can answer my request. In particular if I want this request to also be satisfied in smartphone's application, which does not allows to add add-ons.

Learning a list of things is hard, but it's something I sometime want to do. A poem/song is just a list of line. Sometime, a mathematical notions have 4 distinct names. E.g. a pullback is also called a fiber product, a fibered product and a Cartesian square. In some othe case, a mathematical objects admits many distinct definitions[2]. E.g. I've got 5 definitions of left-trivial monoids. And I'd also wanted to see if I can learn the list of the prime number less than 100. Mostly to see how hard it is to learn an arbitrary list.

Notes

[1] I assume here that sets are list, with an arbitrary order

[2] This is in general considered to be a proof that the object is really interesting

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Note on an introduction on Anki given a 35C3

This post is a comment about a self-organised workshop Introduction to anki I gave at #35C3 (35th Chaos Communication Congress, a congress of 17k hackers). This workshop was announced on the anki's subredd where I asked for ideas. I received a lot of useful feedback from this subreddit and from the related discord server. The main audience of the current blog post is thus those person, already in anki's community. This post contains idea in random order.

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The trolley problem, and what you should do if I'm on the tracks

Originally published in French and crossposted on LessWrong. Translation by Épiphanie.

Trigger warning: Death, suicide, and murder. Trolley problem.

This is quite the conventional and ethical conundrum: You are near train tracks, and a train is rolling down the hill. It is going to run over 4 people who are tied to the rails of the main track. However, you can change the train's direction to a secondary track by pulling a lever; so that it runs over only one guy, also tied down the rails. Should you pull the lever?

I do believe there is a more interesting way to frame it: What would you choose if you are yourself tied to the rails, alone, while the train is not heading toward you yet. My own answer is very simple: I want the person deciding where the train should go to have _no doubts_ they should pull the lever! Because, for lack of context, I assume that the other four people are just me, or rather copy of mes. That's a bit simplistic, of course they are not perfect clone. But as far as concrete predicates go, they are indistinguishable. That is to say I have odds of being on tracks alone of 1 in 5, and odds for being in the group of 4 in 5. And tell you what, I prefer dying with 20% probability because of what someone did, rather than to die with 80% probability because no one was ever willing to take the burden of responsibility.

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