Samir Okasha

Sceptical arguments in epistemology typically employ sceptical hypotheses, which are rivals to our everyday beliefs so constructed that they fit exactly the evidence on which those beliefs are based. There are two ways of using a sceptical hypothesis to undermine an everyday belief, giving rise to two distinct sorts of sceptical argument: underdetermination‐based and closure‐based. However, both sorts of argument, as usually formulated in the literature, fall foul of evidential holism, for they ignore the crucial role of background beliefs. An analogy with the philosophy of science makes this point explicit. There is no simple way to “holism proof” the two sceptical arguments.

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

A long-established consensus in the philosophy of biology holds that biological species are not natural kinds with intrinsic essences, despite what Putnam (1975) and Kripke (1980) thought. This anti-essentialist consensus has recently been challenged by Michael Devitt, who insists that it rests on a mistake. According to Devitt, philosophers of biology have failed to recognise the distinction between two quite different questions one can ask about species: the Category question and the Taxon question. The various “species concepts” found in the biological literature are attempts to answer the former but are silent about the latter, Devitt claims, so do not conflict with essentialism, pace what philosophers of biology believe. By carefully attending to the logical relation between the Category and Taxon questions, Devitt’s claim that the anti-essentialist consensus rests on a mistake is shown to be untenable.

Biological agency has received much attention in recent philosophy of biology. But what is the motivation for introducing talk of agency into biology and what is meant by “agent”? Two distinct motivations can be discerned. The first is that thinking of organisms as agents helps to articulate what is distinctive about organisms vis-à-vis other biological entities. The second is that treating organisms as agent-like is a useful heuristic for understanding their evolved behavior. The concept of agent itself may be understood in at least four different ways: minimal agent, intelligent agent, rational agent, and intentional agent. Which understanding is most appropriate depends on which of the two motivations we are concerned with.

Discoverer of the theory of evolution by natural selection, and thus the founder of modern evolutionary biology, Charles Darwin is responsible for one of the most fundamental and far‐reaching contributions to the modern scientific world view. Born in 1809 in Shrewsbury into a wealthy Victorian family, Darwin was educated at the universities of Edinburgh and Cambridge. Though his formal education was of little interest to him ‐ “my time was wasted, as far as the academical studies were concerned” (1969, p. 58) ‐ Cambridge did provide the opportunity to pursue his childhood interest in natural history. Upon graduating in 1831, Darwin joined a charting expedition around South America on board HMS Beagle, which was to last for five years. During this time, he made lengthy expeditions inland, studying the flora, fauna, and geology of South America and the Pacific Islands, and accumulating a massive biological and geological collection. These years were critical for Darwin's intellectual development, as he admitted, sowing the seeds of his doubt in the fixity of individual species. Darwin was impressed by a large number of facts that could not be explained on the assumption of the fixity of species, including the close structural similarities between extinct and living species revealed by the fossil record. Most important of all were the tortoises and finches of the Galapagos Islands: each island was inhabited by very similar, yet distinct varieties ‐ clear evidence for Darwin of common ancestry shaped by adaptation to local conditions. The creatures of the Galapagos, Darwin wrote, bring us close “to that great fact ‐ that mystery of mysteries ‐ the first appearance of new beings on this earth” (1839, p. 466).

It is widely agreed that Hume's description of human inductive reasoning is inadequate. But many philosophers think that this inadequacy in no way affects the force of Hume's argument for the unjustifiability of inductive reasoning. I argue that this constellation of opinions contains a serious tension, given that Hume was not merely pointing out that induction is fallible. I then explore a recent diagnosis of where Hume's sceptical argument goes wrong, due to Elliott Sober. Sober argues that Hume committed a quantifier-shift fallacy, i.e. inferred a statement of ?? form from one of ?? form. The implications of this diagnosis for the traditional problem of induction are briefly examined

Kuhn’s famous thesis that there is ‘no unique algorithm’ for choosing between rival scientific theories is analysed using the machinery of social choice theory. It is shown that the problem of theory choice as posed by Kuhn is formally identical to a standard social choice problem. This suggests that analogues of well-known results from the social choice literature, such as Arrow’s impossibility theorem, may apply to theory choice. If an analogue of Arrow’s theorem does hold for theory choice this would refute Kuhn’s thesis, but it would also pose a threat to the rationality of science, a threat that is if anything more worrying than that posed by Kuhn. Various possible ‘escape routes’ from Arrow’s impossibility result are examined, in particular Amartya Sen’s idea of ‘enriching the informational basis’. It is shown that Sen’s idea can be applied to the problem of theory choice in science. This in turn sheds light on two well-known approaches to inductive inference in philosophy of science: Bayesianism and statistical model selection

We critically examine a number of aspects of Grafen’s ‘formal Darwinism’ project. We argue that Grafen’s ‘selection-optimality’ links do not quite succeed in vindicating the working assumption made by behavioural ecologists and others—that selection will lead organisms to exhibit adaptive behaviour—since these links hold true even in the presence of strong genetic and developmental constraints. However we suggest that the selection-optimality links can profitably be viewed as constituting an axiomatic theory of fitness. Finally, we compare Grafen’s project with Fisher’s ‘fundamental theorem of natural selection’, and we speculate about whether Grafen’s results can be extended to a game-theoretic setting

In his “A New Program for Philosophy of Science?”, Ronald Giere expresses qualms regarding the critical and political projects I advocate for philosophy of science—that the critical project assumes an underdetermination absent from actual science, and the political project takes us outside the professional pursuit of philosophy of science. In reply I contend that the underdetermination the critical project assumes does occur in actual science, and I provide a variety of examples to support this. And I contend that the political project requires no more than what other academic fields even in science studies are already providing.

Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico-deductive inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen, we analyze a problem for the putative Bayesian justification of H-D inference in the case where what we learn from observation is logically stronger than what our theory implies. Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient conditions for the mismatch in logical strength to be justifiably ignored as a "harmless idealization''. Thirdly, we argue, based upon scientific examples, that the pattern of H-D inference of which there is a ready Bayesian justification is only rarely the pattern that one actually finds at work in science. Whatever the other virtues of Bayesianism, the idea that it yields a simple justification of a pervasive pattern of scientific inference appears to have been oversold.

In a recent paper, Takacs and Bourrat (Biol Philos 37:12, 2022) examine the use of geometric mean reproductive output as a measure of biological fitness. We welcome Takacs and Bourrat’s scrutiny of a fitness definition that some philosophers have adopted uncritically. We also welcome Takacs and Bourrat’s attempt to marry the philosophical literature on fitness with the biological literature on mathematical measures of fitness. However, some of the main claims made by Takacs and Bourrat are not correct, while others are correct but not for the reasons they give.

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease.

Evolutionary biology is striking for its ability to explain a large and diverse range of empirical phenomena on the basis of a few general theoretical principles. This article offers a philosophical perspective on the way that evolutionary biology has come to achieve such impressive generality, by focusing on “the strategy of endogenization”. This strategy involves devising evolutionary explanations for biological features that were originally part of the background conditions, or scaffolding, against which such explanations take place. Where successful, the strategy moves biology a step closer to the ideal of explaining as much as possible from evolutionary first principles. The strategy of endogenization is illustrated through a series of biological examples, historical and recent, and its philosophical implications are explored.