Kristina Khutsishvili

The figure of the scientist has long occupied a distinctive place in the epistemic order. From the Enlightenment onward, the scientist was not merely a skilled technician but a disciplined inquirer – a producer and guardian of knowledge – whose legitimacy rested on epistemic virtues such as curiosity, integrity, and humility, as well as on empirical rigour. Today, however, this position appears less secure. The systems we now refer to as ‘artificial intelligence’, and more concretely large language models (LLMs), produce outputs which, in certain domains, rival human work.

The article by Durán and Jongsma attempts to establish philosophical grounds for trust in medical artificial intelligence (AI) by positing concerns about opacity, ‘black box’ algorithms and epistemic justification. However, their argument conflates distinct technical concepts, mischaracterises both machine learning (ML) and statistical inference and fails to engage with established methodological frameworks used in safety-critical domains. Specifically, the article erroneously treats AI and ML as monolithic, assumes that unexplained correlations equate to epistemological opacity and obscures well-developed approaches in economics, biostatistics and epidemiology for handling uncertainty and causal inference. By comparing the authors’ claims to accepted practice in econometrics and clinical statistics, this response shows that the article’s foundational propositions are technically unsound and ethically unhelpful. A more productive ethical analysis of medical AI should foreground rigorous validation, transparent performance metrics and appropriate frameworks for causal inference and accountability. This response proposes alternative criteria for evaluating trust and ethical deployment of AI in medicine.

The analysis undertaken in our study suggests that the ethical challenges associated with artificial intelligence in local government are a consequence of institutional capacity rather than normative uncertainty. Local authorities are not operating in an ethical vacuum: they are surrounded by a dense multi-level system of principles articulating expectations around transparency, accountability, fairness, privacy, explainability, human oversight, and other aspects related to AI development, deployment, and use. The persistent difficulty lies in translating these ethical commitments into stable administrative practices that can be enacted within local bureaucratic constraints.

The design phase in the development of artificial intelligence (AI) systems is a promising period for addressing the problem of bias. This chapter explores the challenge of working towards the ‘Fair AI’, drawing on empirical insights from the CommuniCity Horizon Europe project. Adopting an interdisciplinary perspective – with references to philosophy, informatics, and participatory design – it reflects on the project’s experiences in both the co-creation of technological solutions with target community members and the development of technical ‘Fair AI’ Minimal Interoperability Mechanisms. The chapter underscores the limitations of relying solely on non-anticipatory, technical de-biasing approaches, and instead advocates for a comprehensive strategy that unites efforts across technical and social domains. This begins with work on ‘fairness by design’ and includes public participation and co-creation as essential components.

On July 10, 2025, the European Commission released the final draft of the General-Purpose Artificial Intelligence (GPAI) Code of Practice, a “code designed to help industry comply with the AI Act's rules.” The Code has been under development since October 2024, when the iterative drafting process began after a kick-off plenary in September 2024. The Commission had planned to release the final draft by May 2, 2025, and the subsequent delay has sparked widespread speculation – ranging from concerns about industry lobbying to deeper, more ideological tensions between proponents of innovation and regulation. However, beyond these narratives, a more fundamental issue emerges: an epistemic and conceptual disconnect at the core of the EU Artificial Intelligence Act (EU AI Act), particularly in its approach to “general-purpose AI” (GPAI). The current version, which includes three chapters covering “Transparency,” “Copyright,” and “Safety and Security,” does not address these core problems.

The ascent of tech billionaires—and, depending on the market, soon trillionaires—signals more than a shift in global economic structures; it marks a transformation in the moral and cultural conditions under which democratic life is sustained. This contribution offers a communitarian critique of Big Tech’s influence, grounded in the philosophical frameworks of Charles Taylor, Michael Sandel, and virtue ethicist Shannon Vallor, and further supported by public goods theory and economic insights from Paul Samuelson and Joseph Stiglitz, with Elinor Ostrom’s work emphasizing the civic importance of collective stewardship. It contends that the challenge to democracy posed by concentrated digital power is not merely institutional, economic, or ethical, but a disruption of the very conditions for democratic citizenship.

This contribution aims to analyse current challenges of populism and nationalism by using the apparatus of political philosophy. Three important philosophic categories, such as identity, responsibility, and dialogue, are discussed while reflecting on current collisions. By showing their interrelated character, the author underlines the issue of speechlessness and multilateral lack of communication between people, people and the establishment, different intellectual groups, and so forth. Linking populism and nationalism to identity peculiarities, and reflecting on the fluidity of meanings, the power of words, and the related responsibility, this work claims the crucial importance and necessity of dialogue as the main instrument which can prevent dangerous consequences of irresponsibility, and identifies academics and public intellectuals as possible initiators of the dialogue.

The relationship between creativity and artificial intelligence has been recently discussed in both the expert community and the broader public, with the discussion being driven not only by the challenges of practice or academic interest but also significantly influenced by societal anxieties. Large Language Models (LLMs), such as Chat GPT, Midjourney, DALL-E, have become central to the dialogue on human/machine creativity. Questions arise: Can AI be truly creative and if so, is AI creativity of the same nature as human or non-human animal creativity? If we affirm both of these questions, what implications does that hold for our future selves? This contribution establishes meaningful links of personal and collective identity bridging the debates on AI creativity and human enhancement.

Rapid technological developments may exacerbate the victimhood already experienced by vulnerable individuals and communities. At the same time, broad societal anxieties induced by technology lead to the perception of algorithms, these entities of the unknown, as perpetrators. In this essay, I argue that these tendencies can be addressed by a nuanced process of technological co-creation and by the fostering of a public discourse in which “experts” and “public” are united in the acknowledgment of a shared vulnerability before the unknown, whether this unknown takes a technological, societal, or ethical shape.

This paper aims to reflect on the anthropological nature of the digital infosphere being contextual for phenomena such as epistemic bubbles and echo chambers. Is the digital infosphere, the general context for phenomena such as epistemic bubbles and echo chambers, an anthropological place or a non-place? The answer to this question is important to better understand the issue, and to learn how to approach it in a good enough way to minimize the potential harms such as successful disinformation campaigns and occasions of hate speech.

The book explores narratives of black: brings black into different contexts, compares it with white and other colours of spectrum, reflects on the underneath meanings hidden by black. It is a piece of art that is difficult to be classified by genre: it may be a collection of short stories, an autobiography, an essay. Belonging to both literary and philosophic contexts, this book is not “heavy”, both literally and metaphorically, but filled with unusual observations and reflections on meanings hidden behind the colours.