EA Malaysia Cause Prioritisation Report (2021) 2021-04-24T05:48:58.731Z
Singapore AI Policy Career Guide 2021-01-21T03:05:59.687Z
Local priorities research: what is it, who should consider doing it, and why 2020-09-06T14:57:43.228Z
Singapore’s Technical AI Alignment Research Career Guide 2020-08-26T08:09:57.841Z


Comment by yiyang on EA Malaysia Cause Prioritisation Report (2021) · 2021-04-27T13:16:22.995Z · EA · GW

Hi Brian! Thank for your response.  I'll be using "we" (as a team) to address most of your comments, and "I" at the end to address one point. 

I think it would be a lot better though if you had "problem profiles" like 80,000 Hours's for those causes you listed, especially the top 2-4 causes.  

Yes if there is a case for conducting further research, we are definitely considering deeper research in the top causes, and producing “problem profiles”. 

Or if not making full problem profiles, putting a few sentences or bullets about the scale and neglectedness of each of the causes would help.

We realised that our last point at the disclaimer didn’t make clear an additional related issue, which addresses this concern of yours. We didn’t detail which piece of evidence or arguments that made us give a certain score. Technically we did - it’s probably somewhere in our meeting minutes and it’s very messy - hence we’ve decided not to address this issue at this time. However, if we were to conduct another research like this, we definitely want to be better at making explicit our assumptions, evidences, and arguments.

The 2 that I think are very questionable though are financial literacy and improving diversity and inclusion. I don't see why these two could be in the top 8 causes for Malaysia. Maybe one of you could make the case for why these two causes are very impactful to work on, especially compared to other alternatives I list below?

We actually found a huge variance of scores for the above two causes areas in both the initial ranking stage and weighted factor model stage. So some of us in our team do agree with you that these cause areas shouldn’t be in the top 8. It also might be the case that we didn’t brainstorm enough cause areas that may reach the top 8. 

As a side note, most of us in our team have a lot of strong feelings with diversity and inclusion issues in Malaysia (although some of us did put a lower score for this cause area, we weren’t that surprised it made it in the top 8). In a nutshell, issues of race and religion are often used as a dividing force within Malaysia at the legislative, political and social level in much of Malaysia’s modern history. 

On a personal note, I wouldn't be surprised if these two cause areas actually do drop out in the next iteration of research (unless there's really convincing evidence of a cost-effective intervention).  

Would love to check out EA PH's cause prioritisation report soon! :)

Comment by yiyang on Singapore’s Technical AI Alignment Research Career Guide · 2020-10-16T13:04:42.473Z · EA · GW

Hi Misha, sorry for the late reply. Thanks for the heads up! I've added this feedback for a future draft.

Comment by yiyang on Local priorities research: what is it, who should consider doing it, and why · 2020-09-09T08:48:27.621Z · EA · GW

I appreciate the feedback Peter!

Comment by yiyang on Singapore’s Technical AI Alignment Research Career Guide · 2020-09-01T03:41:08.610Z · EA · GW

That's great! Thanks again for the feedback.

Comment by yiyang on Singapore’s Technical AI Alignment Research Career Guide · 2020-08-27T08:23:22.399Z · EA · GW

In regards to what I meant by "short term AI capabilities", I was referring to prosaic AGI - potentially powerful AI systems that uses current techniques instead of hypothetical new ideas surrounding how intelligence works. When you mentioned "I estimated a very rough 50% chance of AGI within 20 years, and 30-40% chance that it would be using 'essentially current techniques'", I took it as prosaic AGI too, but you might mean something else.

I've reread all the write-ups, and you're right that they don't imply that "research on short term AI capabilities is potentially impactful in the long term". I really have jumped the gun there. Thanks for letting me know!

I've rephrased the problematic part to the following:

"Singapore’s AI research is focused more on current techniques. If you think we need to have new ideas on how intelligence works to tackle AI alignment issues, than Singapore is not a good country for that. However, if you think prosaic AGI [link to Paul's Medium article] is a strong possibility, then working on AI alignment research in Singapore might be good."

If you feel like this rephrasing is still problematic, please do let me know. I don't have a strong background in AI alignment research, so I might have misunderstood some parts of it.