Martin Peterson

Consequentialism, one of the major theories of normative ethics, maintains that the moral rightness of an act is determined solely by the act's consequences and its alternatives. The traditional form of consequentialism is one-dimensional, in that the rightness of an act is a function of a single moral aspect, such as the sum total of wellbeing it produces. In this book Martin Peterson introduces a new type of consequentialist theory: multidimensional consequentialism. According to this theory, an act's moral rightness depends on several separate dimensions, including individual wellbeing, equality and risk. Peterson's novel approach shows that moral views about equality and risk that were previously thought to be mutually incompatible can be rendered compatible, and his precise theoretical discussion helps the reader to understand better the distinction between consequentialist and non-consequentialist theories. His book will interest a wide range of readers in ethics.

This article introduces and explores a distinction between multi-dimensional and one-dimensional consequentialist moral theories. One-dimensional consequentialists believe that an act's deontic status depends on just one aspect of the act, such as the sum total of wellbeing it produces, or the sum total of priority- or equality-adjusted wellbeing. Multi-dimensional consequentialists believe that an act's deontic status depends on more than one aspect. They may, for instance, believe that the sum total of wellbeing produced by an act and the degree to which the wellbeing is equally distributed in the population affect the act's deontic status independently of each other. These two aspects cannot be reduced into any single (composite) aspect. Wellbeing and equality are two separate considerations that cannot be merged into some novel entity that accurately reflects both intuitions. On the multi-dimensional view I defend, such clashes between separate aspects are irresolvable and are best accounted for by claiming that moral rightness and wrongness are non-binary concepts. Some acts are, literally speaking, a little bit right (because they maximise wellbeing) and a little bit wrong (because they do not maximise equality).1

Pure time preference is a preference for something to come at one point in time rather than another merely because of when it occurs in time. In opposition to Sidgwick, Ramsey, Rawls, and Parfit we argue that it is not always irrational to be guided by pure time preferences. We argue that even if the mere difference of location in time is not a rational ground for a preference, time may nevertheless be a normatively neutral ground for a preference, and this makes it plausible to claim that the preference is rationally permitted

You must either save a group of m people or a group of n people. If there are no morally relevant diff erences among the people, which group should you save? is problem is known as the number problem. e recent discussion has focussed on three proposals: (i) Save the greatest number of people, (ii) Toss a fair coin, or (iii) Set up a weighted lottery, in which the probability of saving m people is m / m + n , and the probability of saving n people is n / m + n . is contribution examines a fourth alternative, the mixed solution, according to which both fairness and the total number of people saved count. It is shown that the mixed solution can be defended without assuming the possibility of interpersonal comparisons of value.

In this paper we shed new light on the Argument from Disagreement by putting it to test in a computer simulation. According to this argument widespread and persistent disagreement on ethical issues indicates that our moral opinions are not influenced by any moral facts, either because no such facts exist or because they are epistemically inaccessible or inefficacious for some other reason. Our simulation shows that if our moral opinions were influenced at least a little bit by moral facts, we would quickly have reached consensus, even if our moral opinions were affected by factors such as false authorities, external political shifts, and random processes. Therefore, since no such consensus has been reached, the simulation gives us increased reason to take seriously the Argument from Disagreement. Our conclusion is however not conclusive; the simulation also indicates what assumptions one has to make in order to reject the Argument from Disagreement. The simulation algorithm we use builds on the work of Hegselmann and Krause (J Artif Soc Social Simul 5(3); 2002, J Artif Soc Social Simul 9(3), 2006).

It is a natural assumption in mainstream epistemological theory that ascriptions of knowledge of a proposition p track strength of epistemic position vis-à-vis p. It is equally natural to assume that the strength of one’s epistemic position is maximally high in cases where p concerns a simple analytic truth. For instance, it seems reasonable to suppose that one’s epistemic position vis-à-vis “a cat is a cat” is harder to improve than one’s position vis-à-vis “a cat is on the mat”, and consequently, that the former is at least as unambiguous a case of knowledge as the latter. The current paper, however, presents empirical evidence which challenges this intuitive line of reasoning. Our study on the epistemic intuitions of hundreds of academic philosophers supports the idea that simple and uncontroversial analytic propositions are less likely to qualify as knowledge than empirical ones. We show that our results, though at odds with orthodox theories of knowledge in mainstream epistemology, can be explained in a way consistent with Wittgenstein’s remarks on ‘hinge propositions’ or with Stalnaker’s pragmatics of assertion. We then present and evaluate a number of lines of response mainstream theories of knowledge could appeal to in accommodating our results. Finally, we show how each line of response runs into some prima facie difficulties. Thus, our observed asymmetry between knowing “a cat is a cat” and knowing “a cat is on the mat” presents a puzzle which mainstream epistemology needs to resolve.