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[Bernice Ebesugawa]

InitiallyI considered studying computer science at a university for one semester. However, after looking at the syllabus and showing it to my friends with a technological background, it soon became clear that this wasn't a good idea. Usually, during the first semesters in computer science, a lot of basic mathematics as well as some computer hardware knowledge are taught. Most of this is not relevant for a high-level understanding of AI.

The second prerequisite is statistics. The books recommended on the website How to Learn Statistics for Data Science, which again the original website refers to, were really complex however, so I stopped working through them at some point. Instead, I only used their overview of topics one should get familiar with to decide on these two coursera online courses which I really enjoyed. Some of the things they cover were not necessary for my goal, but so far I didn't find anything more suitable (let me know if you do!). Overall, I think they were really valuable and also made me feel much more comfortable with mathematical signs and equations in general.

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.

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:

- 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':

Thanks to Leonie for their post and to Henry for this comment! I've now bought & downloaded Artificial Intelligence: A Guide for Thinking Humans (since it was available as an audiobook), I've added this post to my Collection of AI governance reading lists, syllabi, etc., and I expect I'll revisit this post at some future point as well.

Hi Henry :) Thanks a lot for your kind words - and for sharing your thoughts and resources on the topic! I am very grateful you've commented on the post as someone with a technological background. Will definitely have a look at them myself as well.

RE maths: I think I do understand the basics. We had pretty much of that at highschool and the statistics courses included a lot of mathematics as well (especially probabilities). So I agree that you probably need some knowledge here, but maybe this is the reason why I didn't need to go deeper(?)

Evgeny Morozov was a critic of Big Tech long before it became fashionable. Then he built The Syllabus, an online system that breaks the laws of the attention economy. At a time when misinformation about Covid-19 can spread faster than the virus itself, his system is even more important. I was with him when he first shared it with the world.

How did I get to know Morozov? As a journalist trying to get to grips with the influence of technology on society and our lives, the Belarusian writer has been indispensable to me for more than 10 years.

The myth was powerful and influential. Google, Facebook and Amazon were given special legal and tax exemption status because for a long time, politicians believed these were exceptional companies. And cities unthinkingly rolled out the red carpet for Uber and Airbnb.

The idea is that by Monday, a website will go online, where visitors can subscribe to nine different newsletters that link to the most relevant information on the 60 most important themes of our time, and where they can compile their own personalised newsletter.

Morozov and Tomordy studied together in Berlin and have been friends for over 15 years. "I know a lot of very smart people, but Evgeny really is on a different level," Tomordy tells me. "When we were 20, it was already clear that he had a different kind of mind, which continues to surprise me. He thinks in a completely different way, superhuman. The great thing is that The Syllabus will make a part of Evgeny available to a larger audience."

It started in 2013, when Morozov started working on his new book while completing a PhD at Harvard. His book To Save Everything, Click HereA very comprehensive and rich review of that book appeared in the Atlantic . had just appeared and made him world famous at the age of 28.

So Morozov thought about a method to work out the relevance of books. "I had to think of a way of reviewing all 10 million books in Harvard Library without reading them. I had to organise them, rank them based on my interests."

So he ordered a special rubber work mat on which he can stand painlessly for 12 hours. He bought two soup gadgets to make soup quickly. A cook from the village brings steaming pasta dishes for lunch at exactly 1.30pm every day.

By now, Morozov is sitting on a large orange-red beanbag in his office. There is a pregnancy pillow on the beanbag because it allows him to sit longer without discomfort. We have about half an hour, he says, maybe 40 minutes. Then the next to-do will demand his attention.

"I also see this as hijacking the way the attention economy works. Instead of all those celebrities posting things on Instagram, we hope that intellectuals can turn the attention of their followers towards more serious content."

Morozov also sees The Syllabus as a kind of "guerrilla campaign". "The fact that the information based on the greatest amount of research, which is of the highest quality, remains completely inaccessible is absurd. Large scientific publishers are not at all interested in disclosing this research, even though it has been paid for with tax money! Imagine people seeing what research has been carried out using their taxes. They might demand that this knowledge be made public for free. Changing the way scientific publishers work would be a nice side effect."

The Syllabus automatically scores and categorises information from sources that matter to Morozov (scientific publishers, universities, etc). It does this for 60 themes.You can find the curated newsletters here. From "Energy & Extractivism" to "Post-fascism & Far-right Populism" and from "Geopolitics of Tech & Cybersecurity" to "Finance" and "Migration & Demography". You might say the most important themes of our time. Morozov explains that these are also the themes that are essential to the book he wants to write. "These are my research interests, supplemented with five to 10 themes that I find vital to understanding the world."

All incoming books, articles, videos and podcasts receive a score on each of those 60 themes. As Morozov puts it: "Suppose a scientific article about architecture, the history of drugs, neoliberalism and climate change is published. The system would award this article high scores on those four topics, and low scores on the 56 other topics."

"Taxonomies" introduced by Morozov and his team are crucial to this. These are the most important words, concepts, names and institutions related to the 60 themes. The taxonomy of, for example, neoliberalism naturally includes Hayek and Friedman, Davos and the World Bank, Thatcher and Reagan. If there is an overlap between the content of a piece of information and the taxonomies, it will be awarded a high score on that particular theme.

And this is just the first phase. The categorisation and scoring of all information is an initial screening. Everything is then assessed by Morozov and his assistants, several times, ultimately resulting in a selection of the very best and most relevant information that appears during a week, sorted by theme.

On Monday morning, launch day, I wake up to a rhythmic rattling. I walk on to the balcony to see a cheerful Morozov on his home trainer, busy with his iPad in its holder. The view is beautiful, the sun hanging low above the hills.

On Tuesday morning, I get up at seven. In the corridor, I run into a cheerful Morozov. No, The Syllabus will not be launched for the time being, he says, due to "a few minor technical issues." This afternoon, maybe. Probably. "Around 1pm," he thinks.

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