Alessio Tartaro

Polanyi says that the concept of tacit knowledge is “necessarily fraught with the roots that it embodies” (TD, xviii). This paper demonstrates that these roots can be seen in Polanyi’s early writings between 1939 and 1946. In particular, the concepts of “intuitive judgment” and “personal judgment” have some peculiar features that flow subsequently into the idea of tacit knowledge. In this regard, they can be considered ancestors of Polanyi’s best-known concept. In the present paper, I propose a historical reconstruction of the two concepts. In particular, I focus on the problems from which they stem, namely Polanyi’s criticism of research planning and his account on the functioning of science and its institutional and social arrangement. Besides this historical reconstruction, I draw a comparison between the concept of tacit knowledge and its early predecessors.

Explanations are conceived to ensure the trustworthiness of AI systems. Yet, relying solemnly on algorithmic solutions, as provided by explainable artificial intelligence (XAI), might fall short to account for sociotechnical risks jeopardizing their factuality and informativeness. To mitigate these risks, we delve into the complex landscape of ethical risks surrounding XAI systems and their generated explanations. By employing a literature review combined with rigorous thematic analysis, we uncover a diverse array of technical risks tied to the robustness, fairness, and evaluation of XAI systems. Furthermore, we address a broader range of contextual risks jeopardizing their security, accountability, reception alongside other cognitive, social, and ethical concerns of explanations. We advance a multi-layered risk assessment framework, where each layer advances strategies for practical intervention, management, and documentation of XAI systems within organizations. Recognizing the theoretical nature of the framework advanced, we discuss it in a conceptual case study. For the XAI community, our multifaceted investigation represents a path to practically address XAI risks while enriching our understanding of the ethical ramifications of incorporating XAI in decision-making processes.

Explanations are conceived to ensure the trustworthiness of AI systems. Yet, relying solemnly on algorithmic solutions, as provided by explainable artificial intelligence (XAI), might fall short to account for sociotechnical risks jeopardizing their factuality and informativeness. To mitigate these risks, we delve into the complex landscape of ethical risks surrounding XAI systems and their generated explanations. By employing a literature review combined with rigorous thematic analysis, we uncover a diverse array of technical risks tied to the robustness, fairness, and evaluation of XAI systems. Furthermore, we address a broader range of contextual risks jeopardizing their security, accountability, reception alongside other cognitive, social, and ethical concerns of explanations. We advance a multi-layered risk assessment framework, where each layer advances strategies for practical intervention, management, and documentation of XAI systems within organizations. Recognizing the theoretical nature of the framework advanced, we discuss it in a conceptual case study. For the XAI community, our multifaceted investigation represents a path to practically address XAI risks while enriching our understanding of the ethical ramifications of incorporating XAI in decision-making processes.

This perspective paper critically examines value-laden challenges that emerge when using standards to support regulation in the field of artificial intelligence, particularly within the context of the AI Act. It presents a dilemma arising from the inherent vagueness and contestable nature of the AI Act’s requirements. The effective implementation of these requirements necessitates addressing hard normative questions that involve complex value judgments. These questions, such as determining the acceptability of risks or the appropriateness of accuracy levels, need to be addressed in order to achieve compliance with the AI Act. However, this creates a dilemma: either the hard normative questions left open by the AI Act are addressed by the standards or they are addressed by the actors involved in the conformity assessment. This paper argues that the latter approach is more likely. Consequently, regulatory intermediaries such as notified bodies will be responsible for making critical value judgments while evaluating compliance with the AI Act’s value-laden requirements. This shift raises a series of concerns and implications that warrant further exploration.

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Guide to Personal Knowledge: The Philosophy of Michael Polanyi: Tacit Knowledge, Emergence and the Fiduciary Program by Dániel Paksi and Mihály HéderAlessio TartaroPAKSI, Dániel and Mihály Héder. Guide to Personal Knowledge: The Philosophy of Michael Polanyi: Tacit Knowledge, Emergence and the Fiduciary Program. Wilmington, Del.: Vernon Press, 2022. xxiii + 209 pp. Cloth, $65.00Famous for the concept of "tacit knowledge," Polanyi is a figure who looms over twentieth-century philosophy without ever establishing himself as one of its major protagonists. Yet, Polanyi tackled central problems in twentieth-century Western philosophy and offered [End Page 358] insightful and original analyses thereof. In Personal Knowledge, Polanyi articulates ideas about metaphysics, mathematics, evolution, philosophy and sociology of science, epistemology, philosophy of language, political theory, theology, and more. The richness of the contents, but also their deep unity, make Polanyi's work a unique piece in the philosophical landscape of his time, full of fruitful insights that are still relevant nowadays.Guide to Personal Knowledge, written by two of the leading experts on Polanyi's philosophy, deserves the merit of providing an accessible introduction to this complex work. The book is divided into thirteen chapters, each corresponding to the respective chapter of Personal Knowledge. In each chapter, Paksi and Héder clearly explain Polanyi's main ideas, presenting them in the same order as they appear in Personal Knowledge. The chapters are introduced by a "Goals of the chapter" section that provides a series of key points, where the authors summarize Polanyi's objectives in the corresponding chapter of Personal Knowledge.The Guide is interspersed with many direct quotations from Personal Knowledge that allow the reader to link the Guide to the original text. The use of figures and tables illuminates even the most complex concepts, such as "tacit integration" and the difference between "random and ordered systems." The Guide is enriched by twenty-five boxes that provide information on ideas, authors, and concepts directly or indirectly referenced by Polanyi in Personal Knowledge. These boxes are a valuable supplement. In some cases, they offer insight into contemporary events, theories, and scholars to which Polanyi alludes but that he does not elaborate on, for example, about the role of the Michelson-Morley experiments in Einstein's development of the theory of relativity. In other cases, boxes develop a comparison between Polanyi's ideas and related philosophical figures, such as Thomas Kuhn and Samuel Alexander. Thanks to the boxes, the reader gains a richer and more complete view of Polanyi's thought.In the preface, Paksi and Héder preliminarily introduce some key concepts for understanding Polanyi's work, including "objectivity," "trust" and "fiduciary program," "tacit knowledge," "intellectual passions," "deceptive substitution," "moral inversion," "operational principles," "logic of achievement," and "emergence." Their analysis always proves faithful to Polanyi's thought, and the authors show how these concepts are interrelated and constitute the pillars of Personal Knowledge's argumentative structure. Other equally crucial concepts in Polanyi's work, for example, "commitment," "indwelling," "tradition," "conviviality," "anthropogenesis," "ultrabiology," are not introduced in the preface, but they are explored in depth in the respective chapters.The thirteen chapters of the book recapitulate in detail the main thematic segments of Personal Knowledge. The critique of objectivism and positivist views of science is explained and analyzed in chapters 1 to 4. This critique is articulated on several levels. Polanyi first criticizes [End Page 359] objectivism because it attempts to remove the personal element from scientific knowledge in order to pursue ever higher degrees of formalism, neutrality, and impersonality. Polanyi asserts, however, that the personal element is irreducible, and then proceeds to demonstrate how it operates: in the evaluation of probability statements (chapter 2), in the appreciation of ordered patterns (chapter 3), and in the practice of skills (chapter 4). The ineliminability of the personal element shows that objectivism is false. Paksi and Héder brilliantly retrace the train of thought that leads Polanyi to this conclusion.The second theme that runs across Personal Knowledge concerns the tacit foundation of human intellectual abilities and, consequently, of science and society. In chapter 6, the authors follow Polanyi's disparate arguments about animal intelligence, human...

Digital Earth applications provide a common ground for visualizing, simulating, and modeling real-world situations. The potential of Digital Earth applications has increased significantly with the evolution of artificial intelligence systems and the capacity to collect and process complex amounts of geospatial data. Yet, the widespread techno-optimism at the root of Digital Earth must now confront concerns over high-risk artificial intelligence systems and power asymmetries of a datafied society. In this commentary, we claim that not only can current debates about data governance and ethical artificial intelligence inform development in the field of Digital Earth, but that the specificities of geospatial data, together with the expectations surrounding Digital Earth applications, offer a fruitful lens through which to examine current debates on data governance and artificial intelligence ethics. In particular, we argue that for the implementation of ethical artificial intelligence and inclusive approaches to data governance, Digital Earth initiatives need to involve stakeholders and communities at the local level and be sensitive to social, legal, cultural, and institutional contexts, including conflicts that might arise within those contexts.

Starting in 1946, Polanyi begins to criticize a comprehensive system of ideas that he names positivism. His criticism is twofold. On the one hand, it has the narrow aim of pointing out the inconsistencies of a positivist account of science, according to which the essence of scientific objec­tivity lies in establishing rigorous mathematical relations between measured variables employing fixed rules. On the other hand, it examines the broad assumptions underlying this view, namely radical empiricism and skeptical doubt. The present paper analyzes both aspects of this criticism, stressing its crucial role in the development of Polanyi’s philosophy.