Systems engineers, project managers and other professionals have a “Body of Knowledge,” the set of things that all members of the profession are supposed to know. Likewise, I argue that there is a minimum set of knowledge that allows people to understand the debates in the effective altruist community and participate effectively in its discussions. I don’t mean domain knowledge in AI alignment or poverty alleviation, but rather what is needed to evaluate and prioritize issues and proposals.
So, if I am right, what should this Effective Altruist Body of Knowledge (EALBOK) include? And should we encourage effective altruists to make it a part of their higher education? The following list is incomplete; it doubtless reflects my expertise, my interests, and my prejudices. But I believe it is a good starting point.
· Economics. Effective altruists should understand utility, trade-offs, incentives, and discounting. All this should be covered in your standard beginner microeconomics course. Or study it for free here: https://www.edx.org/course/microeconomics. Paradoxically for people who think big, the study of macroeconomics would likely be much less useful.
· Probability and statistics. Probability deals with predicting the likelihood of future events, while statistics involves the analysis of the frequency of past events. Concepts such as conditional probability, the main probabilistic distributions, and correlation are necessary to understand much of the effective altruist literature in any depth. I would also argue that they are essential for any educated person. There are many free online courses in probability, and even more in statistics; pick your poison: https://www.my-mooc.com/en/categorie/statistics-and-probability.
· Decision analysis. The whole point of effective altruism is to address important decisions in a formal manner, taking into account our values (i.e., our utility function), our time and risk preferences, and uncertainty (represented by probability distributions, most of them subjective). Effective altruists should consider how this “ideal” prescriptive model is affected by biases. Bonus points for understanding how Monte Carlo simulation and discretization work. Decision analysis courses are uncommon, especially at the undergraduate level, but you can find much of the material here: https://online-learning.tudelft.nl/courses/effective-decision-making-dealing-with-business-complexity/. If you want to study the matter in depth, there is an excellent free textbook at https://smartorg.com/wp-content/uploads/2011/08/Decision-Analysis-for-the-Professional.pdf. Decision analysis is tremendously useful in everyday life, whether you are an altruist or a misanthropist.
· Big history. Bill Gates strongly endorsed the teaching of big history, and I concur. Big history studies the history of our Universe, from the Big Bang to date, searching for universal patterns and trends. It provides much needed “situational awareness” for effective altruists. It is interesting, eye-opening, and free at https://www.coursera.org/learn/big-history.
· Game theory. Best known for its use in economics, game theory underlies concepts as relevant to effective altruists as the tragedy of the commons. You can do worse than the introductory course at https://www.coursera.org/learn/game-theory-1. For the serious reader, a comprehensive but accessible free textbook is available at http://faculty.econ.ucdavis.edu/faculty/bonanno/PDF/GT_book.pdf.
· System dynamics simulation. System dynamics is a technique for understanding socio-technical systems over time using mathematical models. What makes system dynamics different from other approaches is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems produce complex behavior. I am probably biased, but I find system dynamics tremendously useful for understanding phenomena such as the spread of epidemics and climate change. While geared towards medical applications, the course at https://www.edx.org/course/system-dynamics-for-health-sciences should cover the basics. If you like to do your own modeling, I recommend the Vensim package. Its Personal Learning Edition has good documentation and can be downloaded for free at https://vensim.com/free-download/.
· Expert judgment. Many of the inputs for the models described above are “expert judgments,” i.e., best guesses by knowledgeable people. How to elicit (i.e., get the experts to talk) and aggregate (i.e., average the experts when they disagree) this often tacit knowledge is a growing field, and the free course at https://www.my-mooc.com/en/mooc/decision-making-under-uncertainty-introduction-to-structured-expert-judgment/ should cover the basics. Philip Tetlock has distilled expert judgment into a science, identifying “superforecasters” who routinely outperform leading experts in their fields. Check out Tetlock’s book at https://www.amazon.com/Superforecasting-Science-Prediction-Philip-Tetlock-ebook/dp/B00Y78X7HY (it’s cheap).
· Long-range planning. The RAND Corporation is probably the gold standard in long-range planning under uncertainty. People who obsess about the future will thus be interested in the recent textbook, Decision Making under Deep Uncertainty. This is cutting-edge stuff, so do not expect a free online course anytime soon. But the free textbook can be found at https://link.springer.com/content/pdf/10.1007%2F978-3-030-05252-2.pdf.
A big absence here is that of any mathematics beyond high school algebra. While calculus can make the above concepts much more powerful, it often introduces an algebraic barrier that prevents true understanding. If you have, or want, a calculus background, go for it. But you can survive without it.
An even more glaring omission is that of philosophy, especially ethics. What should we want? Our values are not “just there.” However, I have preferred not to include Philosophy in the above list for four reasons:
1. Much useful work can be done using the simple utilitarian framework that is tacit, for instance, in economics.
2. I find it difficult to offer prescriptive ethical advice. To my knowledge, there is no “right set” of values; at least not yet.
3. I suspect that our values are not arrived at rationally, but gradually and holistically. How much does the study of philosophy impact our values? I don’t know if there is any data out there; my uneducated guess is “not much.”
4. I cannot claim any particular expertise in philosophy, so I will defer to the advice of those better qualified.