henrycooksley

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Anki deck for "Some key numbers that (almost) every EA should know"

I'm going to make a Quizlet version too. Watch this space.

How to get technological knowledge on AI/ML (for non-tech people)

Hi Leonie - great post! It's really valuable to see people give an honest account of their learning journey in a public forum like this one. 

I am a data scientist and work with machine learning in some capacity for my job, so have plenty of more mathematical textbooks I could recommend, but I won't do that. My background is actually philosophy, so I have had a journey moving from an essay-writing undergraduate student to graduate data scientist, and I know what it's like to not feel like you know anything about this stuff. 

With that said, here are three books I would recommend to a non-technical person wanting to learn more about AI, for AI governance or otherwise. These are not AI safety books, or AI policy books, but are merely introductory books for someone with close to zero starting knowledge about AI.
 

  1. The Hundred-Page Machine Learning Book by Andriy Burkov. This one is commonly suggested as a quick overview of machine learning and tries to go deep without going too technical. It has glowing recommendations from many experienced people in the field, such as Peter Norvig. https://www.amazon.de/Hundred-Page-Machine-Learning-Book/dp/199957950X/
  2. Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell. This is in the Pelican series, which is a series of short explanatory books on a single topic for a general reader (another one is the book The Art of Statistics by David Spiegelhalter, also recommended for learning the intuition behind statistics). I have heard good things about this book and Melanie Mitchell has a well-established reputation in the field of AI research. https://www.amazon.de/Artificial-Intelligence-Thinking-Humans-Pelican/dp/0241404835/
  3. The Quest for Artificial Intelligence: A History of Ideas and Achievements by Nils J. Nilsson. This book is unique. The author has lived through some of the most important developments in the history of artificial intelligence and has often directly worked with many of the key characters in the story. For someone with a more arts or humanities background, getting to know a technical field by its history is sometimes a really good tactic. I read this a few years ago and it really gave me a high-level sense of where the field has come from and where the field might be going. This one is highly recommended. https://www.amazon.de/Quest-Artificial-Intelligence-Nils-Nilsson/dp/0521122937/ 

     

I hope your learning journey goes well and that you continue to write down things that you learn (as you have already done so with this post), as I'm sure it will be really useful to others in a similar position. 

Best of luck!

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EDIT: I was reflecting on what you wrote in the post regarding math and felt like I should say something else just about learning mathematics. Math can definitely feel like something that people are either good at or not, with no in-between. I am sure that you've already done some thinking about this yourself(!) It's a personal choice for everyone but I think trying to learn the basics of geometry, algebra, calculus, etc, is so important for everyone that you should at least give it multiple attempts, kind of like learning to drive a car! Here are some resources that I have found useful to motivate myself:

https://brilliant.org/courses/ - Brilliant is a math and science education website with a free and paid-for tier. I have the paid tier at the moment. It has everything from daily problems, games, and many short courses that range in difficulty from high school through to approximately first-year university/college level. I have particularly enjoyed some of the linear algebra and probability courses, which I did this year, because they were relevant to my job, but I would recommend to not choose the course by its 'utility' as such - try to choose a course that interests you!

Also, here's a TED talk I enjoyed by math educator Jo Boaler on the idea of a 'math person':

My current impressions on career choice for longtermists

Great post.

Regarding the section on software engineering for biosecurity:

"...potentially on biosecurity and pandemic preparedness (I don't currently know any examples of the latter, but think it's reasonably likely there will be some down the line)."

— I have some experience with this having worked for the UK Joint Biosecurity Centre during the height of the pandemic (albeit briefly) in a data science role. I think it's fair to say we had a reasonably sized influence on the analysis that went into government policy relating to the pandemic, with my seniors often reporting straight to the Prime Minister's Office, and where 'reasonably sized' means JBC technical reports or slide decks might have made it into the top ten or even top five most influential policy documents that the most senior health officials would look at that day (very rough guess).

I would argue that data engineering was a reasonably sized bottleneck (that could have been addressed by having access to more good software engineers to help improve our data platforms) but that there were also difficulties in knowing what was relevant data etc, which was more of a data science problem. So really there were many bottlenecks to growth/research of which data engineering was just one (personal opinion).

As a piece of general career advice I would say that software engineers thinking of data engineering as a career would probably find their skills remain in the demand or possibly increase in the following decades, which might make it a good bet. Just as research software engineering is a thing, research data engineering is definitely a thing (if not always given that name) and more talented people working in this area would probably be good.

JBC might not exist in quite the same way for much longer because of how much the public health infrastructure in the UK is changing at the moment (personal opinion), but I think data (software) engineering in biosecurity and pandemic preparedness is definitely a thing (for as long as these institutions persist after covid). If you're interested it helps to have some domain experience of what existing public health data infrastructure exists in your country or region, so that you know where to actually search for jobs. Alternatively you could go in through the contractor route although this seems like a less efficient way of working on the things you are actually interested in.

The 80,000 Hours job board is the skeleton of effective altruism stripped of all misleading ideologies

Absolutely right, we would want something like a breakdown of EA spending that could come from the EA survey if we wanted a more robust metaphor of this kind. Marginal spending on new jobs can miss out information about employers with irregular hiring cycles (or who do very little hiring at all), so looking at a snapshot of a job board on any given day is likely to give you a biased picture of EA spending in general.

The 80,000 Hours job board is the skeleton of effective altruism stripped of all misleading ideologies

Thanks for your comment! To build on my comment to Habryka above (“Thanks for this! If I were rewriting this post, I would take more care to emphasise that it's not 100% my view per se, but it is a view you could have that I have some credence in. The flaws in the view being broadly what you've laid out here.”) I would also add that stripping something to its skeleton is not always desirable, and certainly not what you want as your everyday framing of some issue.

In particular I liked your summary of what's left out of the job board, namely: “it's missing roles which orgs don’t advertise, lots of opportunities at early stage orgs, roles you design yourself and doesn’t foreground graduate school enough”.

Or, the skeleton !== the body

Another point to make is that Schumpeter's “all misleading ideologies” works as a quick phrase in an aphorism, but probably works better when describing the state than describing the effective altruism set of ideas and community.

The 80,000 Hours job board is the skeleton of effective altruism stripped of all misleading ideologies

Thanks for this! If I were rewriting this post, I would take more care to emphasise that it's not 100% my view per se, but it is a view you could have that I have some credence in. The flaws in the view being broadly what you've laid out here.

Four EA podcast episodes

Thanks for writing this post!

Should we think more about EA dating?

Yes. On reflection I am tending towards thinking that, given the numbers involved, if you don't have interactions with a wide enough range of people outside of EA meetups to have some interactions that lead to dating, then you probably don't interact with a wide enough range of people outside of EA meetups.

Should local EA groups support political causes?

You could discuss promotional messaging for your group that has emphasis on your group's solidarity with those fighting for these causes, rather than endorsement per se, and link it to other things that you want to promote that are more traditionally EA if you feel that's helpful.

For example, you might talk about having solidarity for the Black Lives Matter movement, and say that while it's not something that EAs have a lot of research on, that EAs have looked into various areas in criminal justice reform that align with some of their goals.

Or you could link Hong Kong democracy protests to political stability and reducing great power conflict, etc.

Call for feedback and input on longterm policy book proposal

I have not read the full proposal so I'm just commenting on this post.

I think you have a good selection of topics and that there is value in covering some of the policy basics if your aim is to also appeal to a larger audience who might not have the same background knowledge as an experienced policy professional.

On this: “The target audience consists of policy practitioners, inside and outside of government, and scholars of the policy process.” – this seems good. I can only mention the obvious point that iterated development is important and I believe these kinds of books do so much better with input from a wide range of people. I'm sure you already know this.

Others have commented on the flow and linkage of chapters with each other, so you are already aware, but I also agree with this point.

I'm interested to hear more and best of luck with the next phase of development!

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