The words we call slurs are just plain vanilla descriptions like ‘cowboy’ and ‘coat hanger’. They don't semantically convey any disparagement of their referents, whether as content, conventional implicature, presupposition, “coloring” or mode of presentation. What distinguishes 'kraut' and 'German' is metadata rather than meaning: the former is the conventional description for Germans among Germanophobes when they are speaking in that capacity, in the same way 'mad' is the conventional expression that some teenagers use as an intensifier when they’re emphasizing (...) that social identity. That is, racists don’t use slurs because they’re derogatory; slurs are derogatory because they’re the words that racists use. To use a slur is to exploit the Maxim of Manner (or Levinson’s M-Principle) to signal one’s affiliation with a group that has a disparaging attitude towards the slur’s referent. This account is sufficient to explain all the familiar properties of slurs, such as their speaker orientation and “nondetachability,” with no need of additional linguistic mechanisms. It also explains some features of slurs that are rarely if ever explored; for example the variation in tone and strength among the different slurs for a particular group, the existence of words we count as slurs, such as 'redskin', which almost all of their users consider to be respectful, and the curious absence in Standard English of any commonly used slurs—by which I mean words used to express a negative attitude toward an entire group—for Muslims and women. (shrink)

Contextualism in epistemology has traditionally been understood as the view that “know” functions semantically like an indexical term, encoding different contents in contexts with different epistemic standards. But the indexical hypothesis about “know” faces a range of objections. This article explores an alternative version of contextualism on which “know” is a semantically stable term, and the truth-conditional variability in knowledge claims is a matter of pragmatic enrichment. The central idea is that in contexts with stringent epistemic standards, knowledge claims are (...) narrowed: “know” is used in such contexts to make assertions about particularly demanding types of knowledge. The resulting picture captures all of the intuitive data that motivate contextualism while sidestepping the controversial linguistic thesis at its heart. After developing the view, the article shows in detail how it avoids one influential linguistic objection to traditional contextualism concerning indirect speech reports, and then answers an objection concerning the unavailability of certain types of clarification speeches. (shrink)

Alvin Plantinga has argued that evolutionary naturalism (the idea that God does not tinker with evolution) undermines its own rationality. Natural selection is concerned with survival and reproduction, and false beliefs conjoined with complementary motivational drives could serve the same aims as true beliefs. Thus, argues Plantinga, if we believe we evolved naturally, we should not think our beliefs are, on average, likely to be true, including our beliefs in evolution and naturalism. I argue herein that our cognitive faculties are (...) less reliable than we often take them to be, that it is theism which has difficulty explaining the nature of our cognition, that much of our knowledge is not passed through biological evolution but learned and transferred through culture, and that the unreliability of our cognition helps explain the usefulness of science. (shrink)

Even if our justified beliefs are closed under known entailment, there may still be instances of transmission failure. Transmission failure occurs when P entails Q, but a subject cannot acquire a justified belief that Q by deducing it from P. Paradigm cases of transmission failure involve inferences from mundane beliefs (e.g., that the wall in front of you is red) to the denials of skeptical hypotheses relative to those beliefs (e.g., that the wall in front of you is not white (...) and lit by red lights). According to the Bayesian explanation, transmission failure occurs when (i) the subject’s belief that P is based on E, and (ii) P(Q|E) P(Q). No modifications of the Bayesian explanation are capable of accommodating such cases, so the explanation must be rejected as inadequate. Alternative explanations employing simple subjunctive conditionals are fully capable of capturing all of the paradigm cases, as well as those missed by the Bayesian explanation. (shrink)

“Moral imagination” is the capacity to register that one’s perspective on a decision-making situation is limited, and to imagine alternative perspectives that reveal new considerations or approaches. We have developed a Moral Imagination approach that aims to drive a culture of responsible innovation, ethical awareness, deliberation, decision-making, and commitment in organizations developing new technologies. We here present a case study that illustrates one key aspect of our approach – the technomoral scenario – as we have applied it in our work (...) with product and engineering teams. Technomoral scenarios are fictional narratives that raise ethical issues surrounding the interaction between emerging technologies and society. Through facilitated role-playing and discussion, participants are prompted to examine their own intentions, articulate justifications for actions, and consider the impact of decisions on various stakeholders. This process helps developers to re-envision their choices and responsibilities, ultimately contributing to a culture of responsible innovation. (shrink)

Whether it seems that you know something depends in part upon practical factors. When the stakes are low, it can seem to you that you know that p, but when the stakes go up it'll seem to you that you don't. The apparent sensitivity of knowledge to stakes presents a serious challenge to epistemologists who endorse a stable semantics for knowledge attributions and reject the idea that whether you know something depends on how much is at stake. After arguing that (...) previous attempts to meet this challenge fall short, I offer a new solution: theunassertability account. The account starts with the observation that high stakes subjects aren't in an epistemic position to assert. We generally presuppose that knowing is sufficient for epistemically proper assertion, but this presupposition only stands up to scrutiny if we draw a distinction between two notions of epistemic propriety, and we shouldn't expect ordinary speakers to draw it. A subject in a high stakes situation who fails to draw the distinction will be led by the sufficiency claim to treat anything she isn't in a position to assert as something she isn't in a position to know. The sensitivity of epistemically proper assertion to practical factors explains the merely apparent sensitivity of knowledge to stakes. (shrink)

This paper presents a dilemma for the additive model of reasons. Either the model accommodates disjunctive cases in which one ought to perform some act $$\phi $$ just in case at least one of two factors obtains, or it accommodates conjunctive cases in which one ought to $$\phi $$ just in case both of two factors obtains. The dilemma also arises in a revised additive model that accommodates imprecisely weighted reasons. There exist disjunctive and conjunctive cases. Hence the additive model (...) is extensionally inadequate. The upshot of the dilemma is that one of the most influential accounts of how reasons accrue to determine what we ought to do is flawed. (shrink)

We propose a ‘Moral Imagination’ methodology to facilitate a culture of responsible innovation for engineering and product teams in technology companies. Our approach has been operationalized over the past two years at Google, where we have conducted over 50 workshops with teams from across the organization. We argue that our approach is a crucial complement to existing formal and informal initiatives for fostering a culture of ethical awareness, deliberation, and decision-making in technology design such as company principles, ethics and privacy (...) review procedures, and compliance controls. We characterize some distinctive benefits of our methodology for the technology sector in particular. (shrink)

Narratologists commonly draw a distinction between the story and those things that tell the story- the tellings, as I will call them here. Here is an example intended to highlight that distinction. The Parable of the Sower is a parable found in the New Testament books of Matthew, Mark and Luke, and in the non-canonical Gospel of Thomas. Though the relevant pieces of text in the Gospels are remarkably similar, no two of the four are identical. The verses in Matthew, (...) Mark and Luke, have been translated and paraphrased, along with the rest of the Bible, into literally thousands of different languages and versions, all of which include the The Parable of the Sower. (shrink)

Epistemologists have proposed various norms of assertion to explain when a speaker is in an epistemic position to assert a proposition. In this article I propose a distinct necessary condition on assertibility: that a speaker should assert only what she sensitively believes, where a subject's belief is sensitive just in case the subject would not hold it if it were false. I argue that the Sensitivity Rule underwrites simple explanations for three key features of assertibility that pose explanatory challenges to (...) other prominent proposals: the fact that assertibility is open under known entailment, the general impropriety of assertions that a lottery ticket has lost made purely on the basis of the speaker's knowledge of the odds, and the fact that assertibility varies widely with features of the conversational context. I close by considering three distinct roles the Sensitivity Rule might play in the overall theory of assertibility. (shrink)

The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice and fairness in healthcare. (...) In this paper, we provide the building blocks for an account of algorithmic bias and its normative relevance in medicine. (shrink)

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also discuss (...) how work in embodied and situated cognition could provide a valu- able perspective on future research. (shrink)

The Adverse Outcome Pathway (AOP) concept is a knowledge assembly and communication tool to facilitate the transparent translation of mechanistic information into outcomes meaningful to the regulatory assessment of chemicals. The AOP framework and associated knowledgebases (KBs) have received significant attention and use in the regulatory toxicology community. However, it is increasingly apparent that the potential stakeholder community for the AOP concept and AOP KBs is broader than scientists and regulators directly involved in chemical safety assessment. In this paper we (...) identify and describe those stakeholders who currently—or in the future—could benefit from the application of the AOP framework and knowledge to specific problems. We also summarize the challenges faced in implementing pathway-based approaches such as the AOP framework in biological sciences, and provide a series of recommendations to meet critical needs to ensure further progression of the framework as a useful, sustainable and dependable tool supporting assessments of both human health and the environment. Although the AOP concept has the potential to significantly impact the organization and interpretation of biological information in a variety of disciplines/applications, this promise can only be fully realized through the active engagement of, and input from multiple stakeholders, requiring multi-pronged substantive long-term planning and strategies. (shrink)

This article is the introductory chapter to a festschrift in honour of Geoff Hodgson. In work spanning four decades, Geoff Hodgson has made many path-breaking contributions to institutional economics, evolutionary economics, economic methodology, the history of economic thought and social theory more broadly. Hodgson’s reputation as a prolific and important writer, whose work transcends traditional disciplinary boundaries, is matched by his credentials as an academic entrepreneur, whose involvement in the formation of two international scholarly societies and the foundation (...) of the Journal of Institutional Economics has expanded the opportunities for constructive dialogue among social scientists. To celebrate Hodgon’s fantastic career, this volume brings together 19 original contributions by world-leading scholars in specific areas that have played a significant role in influencing Hodgson’s thinking or represent key debates to which he has contributed. The chapter introduces these contributions, and summarizes a conversation with Hodgson that is also included in the volume. (shrink)

This opinion paper delves into the philosophical underpinnings and implications of artificial intelligence (AI) development through the lens of Friedrich Nietzsche's "Three Metamorphoses," exploring the stages from the camel, through the lion, to the envisioned child phase within the AI context. Amidst growing concerns over AI's ethical ramifications, including job displacement, biased decision-making, and misuse potential, this analysis seeks to provide a comprehensive framework for understanding AI's evolution and its socio-technical effects on society. The discourse begins by contextualizing AI within (...) the myth of Prometheus, suggesting that, like the myth, AI development harbors both the promise of unprecedented technological advancement and the peril of unforeseen consequences. Drawing insights from various philosophical perspectives, including those of Geoff Hinton, Elon Musk, Mircea Eliade, Gunther Anders, and notable moralists and existentialists, the paper critiques the current trajectory of AI, emphasizing the need for ethical frameworks and responsible innovation. Through the metaphorical stages defined by Nietzsche—the burden-bearing camel representing AI's foundational learning phase, the rebellious lion challenging human capabilities, and the child signifying the potential for artificial general intelligence (AGI) to autonomously create values—the paper posits that AI's development parallels a transformative journey that could redefine human civilization. It argues for a balanced approach to AI development, one that harmonizes technological advancement with ethical considerations, ensuring AI's alignment with human well-being and justice. The conclusion calls for a reflective engagement with AI, urging developers and policymakers alike to consider the deeper philosophical questions posed by AI's integration into the fabric of human life. (shrink)

In 1949, the Department of Philosophy at the University of Manchester organized a symposium “Mind and Machine” with Michael Polanyi, the mathematicians Alan Turing and Max Newman, the neurologists Geoff rey Jeff erson and J. Z. Young, and others as participants. Th is event is known among Turing scholars, because it laid the seed for Turing’s famous paper on “Computing Machinery and Intelligence”, but it is scarcely documented. Here, the transcript of this event, together with Polanyi’s original statement and (...) his notes taken at a lecture by Jeff erson, are edited and commented for the fi rst time. Th e originals are in the Regenstein Library of the University of Chicago. Th e introduction highlights elements of the debate that included neurophysiology, mathematics, the mind-body-machine problem, and consciousness and shows that Turing’s approach, as documented here, does not lend itself to reductionism. (shrink)