This essay is one of three published in response to Casper Bruun Jensen's article “Experiments in Good Faith and Hopefulness: Toward a Postcritical Social Science”, which concerns the “postcritical” work of Helen Verran, Richard Rottenburg, and Hirokazu Miyazaki. Verran's response clarifies the stance that she takes in her work, and especially in her book Science and an African Logic, toward critique. Here she argues that critique involves grasping the difference between entities in the here-and-now, while conventional analysis in the (...) social sciences explains away difference in the here-and-now by relocating it to an ideal realm. She explains that the method she has developed is a form of infra critique — a way of “doing difference” that keeps it present, particular, and localized. Her essay concludes that the shift to infra critique requires that the “good faith analyst” make her own ontological commitments explicit and accept responsibility for making judgments. (shrink)

This comment argues that Isabelle Stengers, in her article “Comparison as a Matter of Concern,” is justifiably concerned about the future of science in an imperium of commerce where epistemology has no clout. Agreeing with Stengers that we should focus attention on comparison-as-participant, this comment relates Stengers's argument to Verran's own work in contexts where the epistemic practices of science are challenged—in science lessons in Nigeria (case 1) and in episodes where environmental scientists try to work with Aboriginal Australian landowners (...) (case 2). Drawing inspiration from her African and Aboriginal colleagues, Verran disagrees with Stengers that the only option for science is to make the terms of its defeat explicit. This comment suggests that the sciences might learn from other knowledge traditions in finding the places and the means to develop divergent practices through which resistance is possible. Verran identifies temporal disjunctions as possible sites of innovation, suggesting that contemporary sciences should forego their backward-looking traditional epistemic practices and learn to focus instead on equipping their participant-comparisons for an uncertain future. (shrink)

Nanda's irresponsible book carelessly prescribes for the U.S a return to Cold-War science politics; and for India, nothing less than a cultural revolution which would install science as the arbiter. She sees this as smashing the backwards looking metaphysics of Hindu thought. I argue that her iconoclasm carries with it a purist fetishism deriving from science's denied metaphysics. The metaphysics embedded in Nanda's secularist critique is no more innocent than that she wishes to smash, yet being denied is more tricky (...) to deal with. I claim Nanda's book is irresponsible both in the context of India's contesting social imaginaries, but also in the USA where she seeks to intervene in the so-called science wars. Taking seriously the neo-Buddhist Dalit resistance waged by those occupying the lowest rungs of the Hindu caste system, as Nanda prescribes, requires a refusal of metaphysics and positivist thought generally. Being unaware of the metaphysical ladeness of her critique, the ontological move that is necessary to achieve a shift to generative mode of thought that characterises Dalit Buddhism is invisible to Nanda. (shrink)

What happens when a gallery space dedicated to exhibiting European art is interrupted by introducing African art objects? This essay reviews a temporary exhibition that introduced works of art from Africa, the property of Berlin’s Ethnologisches Museum, into the exhibition space of the Bode Museum, whose collection consists of European art objects from the Classical to the Baroque periods. I offer a reading that is quite different than the curators’, proposing art museums as institutions where philosophies are expressed in the (...) form of art objects. (shrink)

The essay analyses the hermeneutics of civilizational dialogue and identifies four basic principles, or requirements: recognition of the equality of the “lifeworlds;” awareness of the “dialectics” of cultural self-comprehension; acknowledgement of formal “metanorms” such as the principle of mutuality; and transcending the circle of “civilizational self-affirmation.” On the basis of these criteria, the essay investigates how politics will have to be reshaped – domestically, regionally and globally – to enable a genuine dialogue of cultures and civilizations that can also serve (...) as a cornerstone of peaceful coexistence among states. Addressing today’s multicultural reality and its impact on the traditional nation-state, the essay underlines the importance of intercultural openness and “civilizational curiosity” – instead of “civilizational nostalgia” – and suggests a redefinition of “co-existence” in the sense of active mutual engagement. The paper further undertakes a critical assessment of the role of “dialogue” as a fashionable decorum of international politics and questions the instrumentalization of the civilizational paradigm in the context of international politics. (shrink)

Carl Mika claims in the symposium’s lead essay that we need more myth today. In fact, an “unscientific” attitude can potentially reorient the alienation from the world. For Mika, a philosophical mātauranga Māori incorporates such a way of being in the world. Through it, an unmediated and co-existent relationship with the world can be built up. Some of Mika’s co-symposiasts invite Mika to substantiate aspects about this bold claim. Carwyn Jones nudges Mika to discuss the parallels between tikanga Māori—a system (...) that seeks to incorporate Māori law—and the common-law tradition that is adopted in New Zealand today. W. Julian Korab-Karpowicz agrees with Mika that to understand the world through an indifferent “scientific” investigation is to understand the world only partially, while the Māori scientist Ocean Ripeka Mercier illustrates how she seeks to develop a third space in her work that reconciles the fear of the unknown with the propensity to control the world through knowing. Helen Verran invites Mika to think about whether, and how, his understanding of a philosophical mātauranga Māori can help to facilitate the cultivation of a naturalism that is able to generate a cosmopolitics in New Zealand. (shrink)

This introduction to the Common Knowledge symposium titled “Comparative Relativism” outlines a variety of intellectual contexts where placing the unlikely companion terms comparison and relativism in conjunction offers analytical purchase. If comparison, in the most general sense, involves the investigation of discrete contexts in order to elucidate their similarities and differences, then relativism, as a tendency, stance, or working method, usually involves the assumption that contexts exhibit, or may exhibit, radically different, incomparable, or incommensurable traits. Comparative studies are required to (...) treat their objects as alike, at least in some crucial respects; relativism indicates the limits of this practice. Jensen argues that this seeming paradox is productive, as he moves across contexts, from Lévi-Strauss's analysis of comparison as an anthropological method to Peter Galison's history of physics, and on to the anthropological, philosophical, and historical examples offered in symposium contributions by Barbara Herrnstein Smith, Eduardo Viveiros de Castro, Marilyn Strathern, and Isabelle Stengers. Comparative relativism is understood by some to imply that relativism comes in various kinds and that these have multiple uses, functions, and effects, varying widely in different personal, historical, and institutional contexts that can be compared and contrasted. Comparative relativism is taken by others to encourage a “comparison of comparisons,” in order to relativize what different peoples—say, Western academics and Amerindian shamans—compare things “for.” Jensen concludes that what is compared and relativized in this symposium are the methods of comparison and relativization themselves. He ventures that the contributors all hope that treating these terms in juxtaposition may allow for new configurations of inquiry. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of (...) variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

As machine learning has gradually entered into ever more sectors of public and private life, there has been a growing demand for algorithmic explainability. How can we make the predictions of complex statistical models more intelligible to end users? A subdiscipline of computer science known as interpretable machine learning (IML) has emerged to address this urgent question. Numerous influential methods have been proposed, from local linear approximations to rule lists and counterfactuals. In this article, I highlight three conceptual challenges that (...) are largely overlooked by authors in this area. I argue that the vast majority of IML algorithms are plagued by (1) ambiguity with respect to their true target; (2) a disregard for error rates and severe testing; and (3) an emphasis on product over process. Each point is developed at length, drawing on relevant debates in epistemology and philosophy of science. Examples and counterexamples from IML are considered, demonstrating how failure to acknowledge these problems can result in counterintuitive and potentially misleading explanations. Without greater care for the conceptual foundations of IML, future work in this area is doomed to repeat the same mistakes. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence, a fast-growing research area that is so far lacking in firm theoretical foundations. In this article, an expanded version of a paper originally presented at the 37th Conference on Uncertainty in Artificial Intelligence, we attempt to fill this gap. Building on work in logic, probability, and causality, we establish the central role of (...) necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We propose a novel formulation of these concepts, and demonstrate its advantages over leading alternatives. We present a sound and complete algorithm for computing explanatory factors with respect to a given context and set of agentive preferences, allowing users to identify necessary and sufficient conditions for desired outcomes at minimal cost. Experiments on real and simulated data confirm our method’s competitive performance against state of the art XAI tools on a diverse array of tasks. (shrink)

Unsupervised learning algorithms are widely used for many important statistical tasks with numerous applications in science and industry. Yet despite their prevalence, they have attracted remarkably little philosophical scrutiny to date. This stands in stark contrast to supervised and reinforcement learning algorithms, which have been widely studied and critically evaluated, often with an emphasis on ethical concerns. In this article, I analyze three canonical unsupervised learning problems: clustering, abstraction, and generative modeling. I argue that these methods raise unique epistemological and (...) ontological questions, providing data-driven tools for discovering natural kinds and distinguishing essence from contingency. This analysis goes some way toward filling the lacuna in contemporary philosophical discourse on unsupervised learning, as well as bringing conceptual unity to a heterogeneous field more often described by what it isnot(i.e., supervised or reinforcement learning) than by what itis. I submit that unsupervised learning is not just a legitimate subject of philosophical inquiry but perhaps the most fundamental branch of all AI. However, an uncritical overreliance on unsupervised methods poses major epistemic and ethical risks. I conclude by advocating for a pragmatic, error-statistical approach that embraces the opportunities and mitigates the challenges posed by this powerful class of algorithms. (shrink)

Some implications of Tomasello et al.'s theory derive from incorporating a variant of a common assumption that humans are biologically adapted to take an intentional stance in relation to conspecifics. I argue that, rather than being cued, intentions and other dispositional states may be inferred logically from an evolved commitment to determinism and evidence of state-dependent behavior.

Using historical documents and evidence gathered in the field, Rubie Watson provides a social history of the 600-year-old Chinese lineage village of Ha Tsuen in the New Territories of Hong Kong, and demonstrates the crucial role that the lineage played in the evolution of the community from a few scattered households in the fourteenth century into a regional power from the 1700s onwards. Despite a patrilineal ideology that extols the virtues of brotherhood and equality, Dr Watson shows that (...) the lineage has in fact played a central role in the formation, development and maintenance of an élite class of landlords and merchants, who, even though their economic importance has now declined, continue to exert political control. Dr Watson examines the dynamics of interclass relations within a single lineage and shows how these relations have been transformed as a consequence of the growth of wage labour. (shrink)

In this captivating book, Helen Verran addresses precisely that question by looking at how science, mathematics, and logic come to life in Yoruba primary schools.

We project the future accumulation of profiles belonging to deceased Facebook users. Our analysis suggests that a minimum of 1.4 billion users will pass away before 2100 if Facebook ceases to attract new users as of 2018. If the network continues expanding at current rates, however, this number will exceed 4.9 billion. In both cases, a majority of the profiles will belong to non-Western users. In discussing our findings, we draw on the emerging scholarship on digital preservation and stress the (...) challenges arising from curating the profiles of the deceased. We argue that an exclusively commercial approach to data preservation poses important ethical and political risks that demand urgent consideration. We call for a scalable, sustainable, and dignified curation model that incorporates the interests of multiple stakeholders. (shrink)

Located in a settler-Australian tertiary education institution we develop a worldly or mundane approach to working in and between institutions enacting two distinct world philosophies. We engage with the epistemics embedded and expressed in the functioning of modern institutions committed to a naturalistic scientific world. And albeit to a more limited extent we engage with epistemics embedded in and expressed by institutions framed and ordered by collectively enacting intentions of Eternal World-Making Beings of Yolngu Aboriginal Australian lands and peoples.

Drawing on a landscape analysis of existing data-sharing initiatives, in-depth interviews with expert stakeholders, and public deliberations with community advisory panels across the U.S., we describe features of the evolving medical information commons. We identify participant-centricity and trustworthiness as the most important features of an MIC and discuss the implications for those seeking to create a sustainable, useful, and widely available collection of linked resources for research and other purposes.

On the whole, the US Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic approach to balancing the benefits and risks of automated decision systems. Yet there is still room for improvement. This commentary highlights how the US AAA can both inform and learn from the European Artificial Intelligence Act (EU AIA).

This article aims to focus on how signatories versus nonsignatories in the U.S. pharmaceutical sector compare with respect to the internal and external stakeholders and principles of the United Nations Global Compact (UNGC). We seek to answer the question: Do signatories to the UNGC walk the talk better than nonsignatories as determined by a variety of published rankings and data? This research presents an innovative approach to the evaluation of UNGC signatories. It uses several objective and independent data sources to (...) assess a matched group of signatories versus nonsignatories in the U.S. pharmaceutical sector. Signatory organizations in the same sector as determined by SIC codes were matched with nonsignatories on variables such as size and number of employees in U.S. pharmaceutical companies. Then both types of organizations were compared on the following data sources: Coalition for Environmentally Responsible Economies ratings, ratings by external stakeholders, ratings by employees, unionization data, financial measures, and annual reports to shareholders. Using nonparametric testing the research found there are differences between signatories and nonsignatories in the U.S. pharmaceutical sector for some of the external stakeholder measures and no differences were found for the internal stakeholder measures. (shrink)

Organisations that design and deploy artificial intelligence (AI) systems increasingly commit themselves to high-level, ethical principles. However, there still exists a gap between principles and practices in AI ethics. One major obstacle organisations face when attempting to operationalise AI Ethics is the lack of a well-defined material scope. Put differently, the question to which systems and processes AI ethics principles ought to apply remains unanswered. Of course, there exists no universally accepted definition of AI, and different systems pose different ethical (...) challenges. Nevertheless, pragmatic problem-solving demands that things should be sorted so that their grouping will promote successful actions for some specific end. In this article, we review and compare previous attempts to classify AI systems for the purpose of implementing AI governance in practice. We find that attempts to classify AI systems proposed in previous literature use one of three mental models: _the Switch_, i.e., a binary approach according to which systems either are or are not considered AI systems depending on their characteristics; _the Ladder_, i.e., a risk-based approach that classifies systems according to the ethical risks they pose; and _the Matrix_, i.e., a multi-dimensional classification of systems that take various aspects into account, such as context, input data, and decision-model. Each of these models for classifying AI systems comes with its own set of strengths and weaknesses. By conceptualising different ways of classifying AI systems into simple mental models, we hope to provide organisations that design, deploy, or regulate AI systems with the vocabulary needed to demarcate the material scope of their AI governance frameworks. (shrink)

Living organisms are the ultimate survivalists, having evolved phenotypes with unprecedented adaptability, ingenuity, resourcefulness, and versatility compared to human technology. To harness these properties, functional descriptions and design principles from all sources of biodiversity information must be collated − including the hundreds of thousands of possible survival features manifest in natural history museum collections, which represent 12% of total global biodiversity. This requires a consortium of expert biologists from a range of disciplines to convert the observations, data, and hypotheses into (...) the language of engineering. We hope to unite multidisciplinary biologists and natural history museum scientists to maximize the coverage of observations, descriptions, and hypotheses relating to adaptation and function across biodiversity, to make it technologically useful. This is to be achieved by developments in meta‐ taxonomic classification, phylogenetics, systematics, biological materials research, structure and morphological characterizations, and ecological data gathering from the collections − the aim being to identify and catalogue features essential for good biomimetic design. (shrink)

This volume includes the texts of Erasmus's 1524 diatribe against Luther,De Libero Arbitrio, and Luther's violent counterattack,De Servo Arbitrio.

The Fairness, Accountability, and Transparency (FAccT) literature tends to focus on bias as a problem that requires ex post solutions (e.g. fairness metrics), rather than addressing the underlying social and technical conditions that (re)produce it. In this article, we propose a complementary strategy that uses genealogy as a constructive, epistemic critique to explain algorithmic bias in terms of the conditions that enable it. We focus on XAI feature attributions (Shapley values) and counterfactual approaches as potential tools to gauge these conditions (...) and offer two main contributions. One is constructive: we develop a theoretical framework to classify these approaches according to their relevance for bias as evidence of social disparities. We draw on Pearl’s ladder of causation (Causality: models, reasoning, and inference. Cambridge University Press, Cambridge, 2000, Causality, 2nd edn. Cambridge University Press, Cambridge, 2009. doi:10.1017/CBO9780511803161) to order these XAI approaches concerning their ability to answer fairness-relevant questions and identify fairness-relevant solutions. The other contribution is critical: we evaluate these approaches in terms of their assumptions about the role of protected characteristics in discriminatory outcomes. We achieve this by building on Kohler-Hausmann’s (Northwest Univ Law Rev 113(5):1163–1227, 2019) constructivist theory of discrimination. We derive three recommendations for XAI practitioners to develop and AI policymakers to regulate tools that address algorithmic bias in its conditions and hence mitigate its future occurrence. (shrink)

[from the publisher's website] Questions about the existence and attributes of God form the subject matter of natural theology, which seeks to gain knowledge of the divine by relying on reason and experience of the world. Arguments in natural theology rely largely on intuitions and inferences that seem natural to us, occurring spontaneously—at the sight of a beautiful landscape, perhaps, or in wonderment at the complexity of the cosmos—even to a nonphilosopher. In this book, Helen De Cruz and Johan (...) De Smedt examine the cognitive origins of arguments in natural theology. They find that although natural theological arguments can be very sophisticated, they are rooted in everyday intuitions about purpose, causation, agency, and morality. Using evidence and theories from disciplines including the cognitive science of religion, evolutionary ethics, evolutionary aesthetics, and the cognitive science of testimony, they show that these intuitions emerge early in development and are a stable part of human cognition. -/- De Cruz and De Smedt analyze the cognitive underpinnings of five well-known arguments for the existence of God: the argument from design, the cosmological argument, the moral argument, the argument from beauty, and the argument from miracles. Finally, they consider whether the cognitive origins of these natural theological arguments should affect their rationality. (shrink)

I develop a nontheistic (quasi-)Berkeleyan idealism. The basic strategy is to peel away the attributes of God that aren't essential for role he plays in idealist metaphysics. God's omnibenevolence, his desires, intentions, beliefs, his very status as an agent ... aren't relevant to the work he does. When we peel all these things away, we're left with a view on which reality is a vast unity of consciousness, weaving together sensory experiences of colors, shapes, sounds, sizes, etc. into the trees, (...) electrons, black holes, and central nervous systems that fill the world around us. This phenomenal unity is governed by laws analogous to those posited by materialists, governing the unfolding of reality. I argue that if reality is fundamentally phenomenal in this way, we can give a unique account of perception that robustly captures direct realist intuitions of reality forming the "constituents" of our experiences: In perception, our finite unities of consciousness come to literally overlap with the unity of consciousness that is reality. I assess the unique virtues and challenges such a view faces, paying particular attention to the question of whether idealism entails a profligacy of physical laws. (shrink)