Recommended Reading

Summary. This page reviews some of the major insights that I've gleaned from various academic subjects. I would especially recommend these topics to students just beginning to learn about utilitarianism. You can see more random link recommendations on my Delicious profile.

Authors

• Nick Bostrom (infinite ethics, simulation argument, anthropic reasoning, future of human evolution, astronomical waste, degrees of experience, paperclipping AIs)
• Eliezer Yudkowsky (intelligence explosion, cognitive biases, reductionism, philosophical zombies, Solomonoff induction, clusters in thingspace, fake explanations)
• Gary Drescher (decision theories as applied to free will, many-worlds interpretation of quantum mechanics, reductionist understanding of consciousness)
• Paul Almond (naturalism, reductionist approach to consciousness)
• David Pearce (wild-animal suffering, general transhumanism, replacing pleasure-pain axis with gradients of happiness)
• Robin Hanson (Aumann's disagreement theorem, AI upload scenarios, information markets)
• Peter Singer (obligation to assist, general animal suffering)
• Yew-Kwang Ng (wild-animal suffering, hedonistic rather than preference utilitarianism)
• Max Tegmark (levels of multiverses)
• Oscar Horta (wild-animal suffering)

Economics

A key notion is the idea of maximizing an objective function subject to constraints. This shows up in microeconomics with the consumer's utility-maximization problem and the firm's profit-maximization problem. A lot of good decision-analysis tools are taught in the context of strategic corporate finance, where the objective function is the net present value of the firm. The notion of the time value of money is itself an important concept, as is the efficient-market hypothesis (EMH). (EMH may not be strictly correct, but it probably is in the practical sense: That unless you spend a substantial fraction of your life researching investments, you may as well pick stocks within a given risk class at random.)

When you have a fixed budget of resources (say, a fixed amount to donate), it generally suffices to choose the option with the highest marginal utility, which leads naturally to the discipline of cost-effectiveness analysis. Health economists, for instance, often report the DALYs averted per dollar for various interventions. Similar principles can and ought to be applied to charitable giving more generally.

Decision-making under uncertainty is also important. The von Neumann-Morganstern theorem shows that any agent whose preferences satisfy certain axioms must act as if she's maximizing the expected value of some utility function. This is a representation theorem, so it doesn't automatically imply that the said utility function corresponds to subjective well-being. However, Yew-Kwang Ng has argued that it in fact does. In any event, I think it's normatively clear that we ought to maximize the expected value of subjective welfare, summed over all organisms that experience such emotions.

Most people are risk-averse because of diminishing marginal utility of income, or so the standard model says. People are also scope insensitive, perhaps because of diminishing marginal utility as a function of good accomplished. (Helping 2,000 rats doesn't feel twice as good as helping 1,000.) Indeed, many have faulty intuitions about diminishing marginal utility of utility that lead them to be risk averse when they ought to be risk-neutral.

It's surprising how many unconventional conclusions can follow from the simple rule: Shut up and multiply. Many people refuse to worry about possibilities that don't think have a high probability of happening. But when the stakes are sufficiently large, a risk-neutral altruist may find it optimal to worry about highly speculative scenarios, like lab universes, hell, or friendly AI. Needless to say, risk neutrality may also have implications for utilitarian investors.

Statistics

The rule of maximizing expected value leaves open the question: Where do the probabilities come from? The answer is given by Bayesian epistemology. Bayes' theorem takes a little bit of time to understand fluently, but the effort is well worth it; hardly a day goes by when I don't think about it in one form or another. An understanding of measure theory and such concepts as countable vs. uncountable infinities can be enlightening but isn't strictly necessary.

I like the information partition framework for probability, in which we start with a set of complete descriptions of possible states of the world, and each new fact we learn cuts down that set to the subset of possible states in which that fact is true. This is, for instance, the model used by Robert Aumann in his important paper on Agreeing to Disagree. Robin Hanson's subsequent work on whether we ought to have common prior probabilities is also important.

Indeed, the standard complaint about Bayesian statistics is that your prior probability distribution is arbitrary. This is, of course, just a restatement of the fundamental problem of epistemological uncertainty in philosophy, but I do think some priors are better than others. In particular, Occam's razor is a fundamental principle that I think our priors ought to reflect, and algorithmic information theory seems like a promising approach for formalizing that intuition.

Physics

We probably live in a multiverse of some type in which, for instance, infinitely many copies of you exist. This leads to the question of how to define, say, reductions in suffering when the expected amount of suffering in the multiverse is infinite.

The block universe conception of time implies that past suffering is just as real as that in the present and future, though there appears to be little we can do to affect it. The many-worlds interpretation of quantum mechanics, if correct, implies that our universe is deterministic and that, moreover, there exist hell-like branches of the multiverse containing suffering as bad as is physically possible; these, too, appear beyond our control and so might be regarded as part of our generalized past. Moreover, the worst of these worlds thankfully have small measure and so shouldn't use up too much of our cognitive resources. (The hell worlds can be even worse in a Tegmarkian level-4 multiverse, but similar qualifications apply.)

Of course, our understanding of physics may change, and we shouldn't rule out the possibility that our smarter descendants will figure out ways to undertake cosmic rescue missions to alleviate the Darwinian suffering endured by wild-animal-like extraterrestrials. Unfortunately, in view of the anthropic fact that we ourselves have not been so rescued, the odds we place on such a scenario are rather small. (Related to the topic of self-locating belief, the doomsday argument and simulation argument are both important to think about.)

The mathematical universe hypothesis of Max Tegmark is fun to think about. So is Jürgen Schmidhuber's A Computer Scientist's View of Life, the Universe, and Everything, which is close to the most comprehensible way to conceive of the universe that I've come across. (Whether it's actually true is up to future scientists to speculate upon.)

Ethics

From a consequentialist perspective, there is no intrinsic distinction between doing harm and failing to do good: Decreasing an organism's utility from 0 to -5 has the same effect as failing to take advantage of the opportunity to increase a suffering organism's utility from -5 to 0. The status quo is arbitrary and so has no claims to being a preferred option to fall back to. (This is the problem with Pareto efficiency.)

Ethicists have spilled much ink trying to solve the is-ought problem, but without success (see Singer's The Triviality of the Debate Over 'Is-Ought' and the Definition of 'Moral'), because fundamentally, justification of an ethical claim reduces to explaining why I care about it.

I don't understand what an objective morality could look like; rather, I maintain an emotivist view of ethics. My desire to relieve suffering is fundamentally no different from my affirmation that I enjoy chocolate: It's a product of chemicals in my brain that impel me to act in certain ways. It needs no fundamental justification. Why do I care about reducing suffering? I just do.

Decision Theories

Philanthropy

Wild-animal suffering

Social change

Inspiration

Home: Essays on Reducing Suffering