Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...

The use of machine learning instead of traditional models in neuroscience raises significant questions about the epistemic benefits of the newer methods. I draw on the literature on model intelligibility in the philosophy of science to offer some benchmarks for the interpretability of artificial neural networks used as a predictive tool in neuroscience. Following two case studies on the use of ANN’s to model motor cortex and the visual system, I argue that the benefit of providing the scientist with understanding (...) of the brain trades off against the predictive accuracy of the models. This trade-off between prediction and understanding is better explained by a non-factivist account of scientific understanding. (shrink)

Is there progress in philosophy? A glass-half-full view is that there is some progress in philosophy. A glass-half-empty view is that there is not as much as we would like. I articulate a version of the glass-half-empty view, argue for it, and then address the crucial question of what explains it.

Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been largely silent on this technology so far. This is remarkable, given that deep learning neural networks have blown past predicted upper limits on artificial intelligence performance—recognizing complex objects in natural photographs and defeating world champions in strategy games as complex as Go and chess—yet there remains no universally accepted explanation (...) as to why they work so well. This article provides an introduction to these networks as well as an opinionated guidebook on the philosophical significance of their structure and achievements. It argues that deep learning neural networks differ importantly in their structure and mathematical properties from the shallower neural networks that were the subject of so much philosophical reflection in the 1980s and 1990s. The article then explores several different explanations for their success and ends by proposing three areas of inquiry that would benefit from future engagement by philosophers of mind and science. (shrink)

Ethics, in the sense in which that word is used by philosophers, may be described as the theoretical treatment of moral phenomena. I use the phrase “moral phenomena” to cover all those facts and only those in describing which we have to use such words as “ought,” “right and wrong,” “good and evil,” or any others which are merely verbal translations of these.

I argue that the best explanation of the multiplicity of available frameworks for treating any given philosophical topic is that philosophy currently (though not insuperably) lacks fixed standards; I then go on to identify three barriers to philosophical progress associated with our present epistemic situation. First is that the lack of fixed standards encourages what I call “intra‐disciplinary siloing,” and associated dialectical and argumentative failings; second is that the lack of fixed standards makes room for sociological factors (including elite influence (...) and disciplinary inertia) to be determinative of which philosophical frameworks are embraced; third is that the lack of fixed standards encourages (implicit and/or explicit) bias. I close by offering some suggestions about how to move beyond these barriers, even in the absence of fixed standards. (shrink)

Recently, philosophers have been carrying out a certain amount of soul searching. In this context, the term “professionalism” gets thrown around. The thought is that too much of what we philosophers do looks inward at the work of colleagues instead of outwards at the issues. Sometimes it can seem that it is more important for one's career to demonstrates that one is on top of the literature rather than on top of the problems the literature is addressing. There is, however, (...) a kind of professionalism that we should applaud. It consists of being sufficiently on top of a range of different areas of philosophical inquiry to see key connections between different areas. Although progress in the sense of convergence in doctrines is nothing for philosophers to write home about, I think we are making progress in seeing connections. (shrink)

Philosophy, as I use it here, is a conversation, one stretching back through various canonical European and Ancient Greek texts at least to Thales. Has this conversation progressed? The main objection to philosophy's having a linear progression is dissensus – the fact that philosophers all disagree but still accept each other as peers. In this chapter, I argue that we should conceive of philosophy as being capable of a branching kind of progression: philosophy progresses when it gives us more ways (...) of conceiving of ourselves. (shrink)

I argue that the present (if not insuperable) lack of fixed standards in philosophy is associated with three barriers to philosophical progress, pertaining to intra-disciplinary siloing, sociological rather than philosophical determinants of philosophical attention, and the encouraging of bias.

Humanity stands at a precipice. -/- Our species could survive for millions of generations — enough time to end disease, poverty, and injustice; to reach new heights of flourishing. But this vast future is at risk. With the advent of nuclear weapons, humanity entered a new age, gaining the power to destroy ourselves, without the wisdom to ensure we won’t. Since then, these dangers have only multiplied, from climate change to engineered pandemics and unaligned artificial intelligence. If we do not (...) act fast to reach a place of safety, it may soon be too late. -/- The Precipice explores the science behind the risks we face. It puts them in the context of the greater story of humanity: showing how ending these risks is among the most pressing moral issues of our time. And it points the way forward, to the actions and strategies we can take today to safeguard humanity’s future. (shrink)

Many people believe that philosophy makes no progress. Members of the general public often find it amazing that philosophers exist in universities at all, at least in research positions. Academics who are not philosophers often think of philosophy either as a scholarly or interpretative enterprise, or else as a sort of pre-scientific speculation. And many well-known philosophers argue that there is little genuine progress in philosophy. Daniel Stoljar argues that this is all a big mistake. When you think through exactly (...) what philosophical problems are, and what it takes to solve them, the pattern of success and failure in philosophy is similar to that in other fields. In philosophy, as elsewhere, there is a series of overlapping topics that determine what the subject is about. In philosophy, as elsewhere, different people in different historical epochs and different cultures ask different big questions about these topics. And in philosophy, as elsewhere, big questions asked in the past have often been solved: Stoljar provides examples. Philosophical Progress presents a strikingly optimistic picture of philosophy - not a radical optimism that says that there is some key that unlocks all philosophical problems, and not the kind of pessimism that dominates both professional and non-professional thinking about philosophy, but a reasonable optimism that views philosophy as akin to other fields. (shrink)

The rightness and wrongness of actions fits on a continuous scale. This fits the way we evaluate actions chosen among a diverse range of options, even though English speakers don’t use the words “righter” and “wronger”. I outline and defend a version of scalar consequentialism, according to which rightness is a matter of degree, determined by how good the consequences are. Linguistic resources are available to let us truly describe actions simply as right. Some deontological theories face problems in accounting (...) for degrees of rightness, as they don't invoke continuous parameters among the right-making features of action. (shrink)

If we are eventually to understand the capability of higher organisms for perceptual recognition, generalization, recall, and thinking, we must first have answers to three fundamental questions: 1. How is information about the physical world sensed, or detected, by the biological system? 2. In what form is information stored, or remembered? 3. How does information contained in storage, or in memory, influence recognition and behavior? The first of these questions is in the.

Recent work takes both philosophical and scientific progress to consist in acquiring factive epistemic states such as knowledge. However, much of this work leaves unclear what entity is the subject of these epistemic states. Furthermore, by focusing only on states like knowledge, we overlook progress in intermediate cases between ignorance and knowledge—for example, many now celebrated theories were initially so controversial that they were not known. -/- This paper develops an improved framework for thinking about intellectual progress. Firstly, I argue (...) that we should think of progress relative to the epistemic position of an intellectual community rather than individual inquirers. Secondly, I show how focusing on the extended process of inquiry (rather than the mere presence or absence of states like knowledge) provides a better evaluation of different types of progress. This includes progress through formulating worthwhile questions, acquiring new evidence, and increasing credence on the right answers to these questions. I close by considering the ramifications for philosophical progress, suggesting that my account supports rejecting the most negative views while allowing us to articulate different varieties of optimism and pessimism. (shrink)

In the latter half of the twentieth century, philosophers of science have argued (implicitly and explicitly) that epistemically rational individuals might compose epistemically irrational groups and that, conversely, epistemically rational groups might be composed of epistemically irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they together imply that methodological prescriptions for scientific communities and those for individual scientists might be logically independent of one another. We develop a formal model of scientific inquiry, define four (...) criteria for individual and group epistemic rationality, and then prove that the four definitions diverge, in the sense that individuals will be judged rational when groups are not and vice versa. We conclude by explaining implications of the inconsistency thesis for (i) descriptive history and sociology of science and (ii) normative prescriptions for scientific communities. (shrink)

This article argues, first, that there is plenty of agreement among philosophers on philosophically substantive claims, which fall into three categories: reasons for or against certain views, elementary truths regarding fundamental notions, and highly conditionalized claims. This agreement suggests that there is important philosophical progress. It then argues that although it's easy to list several potential kinds of philosophical progress, it is much harder to determine whether the potential is actual. Then the article attempts to articulate the truth that the (...) deniers of philosophical progress are latching on to. Finally, it comments on the significance of the agreement and progress. (shrink)

Derek Parfit presents the third volume of On What Matters, his landmark work of moral philosophy. Parfit develops further his influential treatment of reasons, normativity, the meaning of moral discourse, and the status of morality. He engages with his critics, and shows the way to resolution of their differences.

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of (...) our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. (shrink)

The second volume in the _Blackwell Brown Lectures in Philosophy_, this volume offers an original and provocative take on the nature and methodology of philosophy. Based on public lectures at Brown University, given by the pre-eminent philosopher, Timothy Williamson Rejects the ideology of the 'linguistic turn', the most distinctive trend of 20th century philosophy Explains the method of philosophy as a development from non-philosophical ways of thinking Suggests new ways of understanding what contemporary and past philosophers are doing.

Contemporary virtue epistemology (hereafter ‘VE’) is a diverse collection of approaches to epistemology. At least two central tendencies are discernible among the approaches. First, they view epistemology as a normative discipline. Second, they view intellectual agents and communities as the primary focus of epistemic evaluation, with a focus on the intellectual virtues and vices embodied in and expressed by these agents and communities. -/- This entry introduces many of the most important results of the contemporary VE research program. These include (...) novel attempts to resolve longstanding disputes, solve perennial problems, grapple with novel challenges, and expand epistemology’s horizons. In the process, it reveals the diversity within VE. Beyond sharing the two unifying commitments mentioned above, its practitioners diverge over the nature of intellectual virtues, which questions to ask, and which methods to use. -/- It will be helpful to note some terminology before proceeding. First, we use ‘cognitive’, ‘epistemic’ and ‘intellectual’ synonymously. Second, we often use ‘normative’ broadly to include not only norms and rules, but also duties and values. Finally, ‘practitioners’ names contemporary virtue epistemologists. (shrink)

This article examines the central epistemological issues tied to the recognition of disagreement.

Computers have far to go to match human strengths, and our estimates will depend on analogy and extrapolation. Fortunately, these are grounded in the first bit of the journey, now behind us. Thirty years of computer vision reveals that 1 MIPS can extract simple features from real-time imagery--tracking a white line or a white spot on a mottled background. 10 MIPS can follow complex gray-scale patches--as smart bombs, cruise missiles and early self-driving vans attest. 100 MIPS can follow moderately unpredictable (...) features like roads--as recent long NAVLAB trips demonstrate. 1,000 MIPS will be adequate for coarse-grained three-dimensional spatial awareness--illustrated by several mid-resolution stereoscopic vision programs, including my own. 10,000 MIPS can find three-dimensional objects in clutter--suggested by several "bin-picking" and high-resolution stereo-vision demonstrations, which accomplish the task in an hour or so at 10 MIPS. The data fades there--research careers are too short, and computer memories too small, for significantly more elaborate experiments. (shrink)