Warmhold Jan Thomas Mollema

In “The Apt Curation Model: An Epistemic Virtue Theory of AI-assisted Authorship” (Philosophy & Technology 39 (2026)) Tiegue Vieira Rodrigues argues that we should conceive of the author in AI-supported processes as an apt curator of texts. He pleads for extending the accurate-adroit-apt framework towards human-AI authorship and developing four curatorial virtues: dialogical, evaluative, integrative, and architectural. This ‘Apt Curation Problem’ solves the problems constituted by the lack of a locus for the epistemic and semantic properties of authorship in the case of AI-assisted text production. In this commentary on Rodrigues’ article, I aim to do three things: (1) summarize and praise the article; (2) reframe the apt curation model as a possible move in the conceptual engineering of AI and authorship; and (3) I argue that the apt curation model stands in need of more conceptual ethics – the metaphilosophical practice of giving reasons for the (sustained) use of a concept. Before we can accept new models of authorship, we still have to weigh our concerns and goals associated with construing authorship in the context of AI in Rodrigues’ way, against other concerns and goals that might drive other conceptualizations, given our current capacities and circumstances.

This articles replies to Tiegue Vieira Rodrigues’s commentary “The Epistemology of Algorithmic Narrative and the Problem of Creative Authenticity” on Mollema’s “AI-generated Literature, Distant Writing and the Reader: Reflections on Floridi and Calvino”. I appreciate the opportunity of engaging in discussion with Rodrigues, a fellow ‘early reflector’ on Luciano Floridi’s concept of ‘distant writing’. Rodrigues and I agree on my core claims (a) that the reader’s interpretative role with respect to AI-generated literature remains constitutive for AI-generated literature’s meaning; and (b) that AI’s narrative capabilities are not exceptional, but stand in continuity with the human author’s literary production. But Rodrigues argues against (b) that this de-anthropomorphized conception of literary production glosses over a major epistemological difference: Large Language Models (LLMs) do not understand their navigation through narrative space, while human authors do. It is this concern that I shall address here. I object to Rodrigues’s conclusion that we can still account for psychological differences in creation (i.e., human authors interpret themselves, whereas LLMs do not), while maintaining a structural equivalence on a specific functional domain. Furthermore, I express Wittgensteinian doubts regarding the dependence of his argument on the concept of understanding.

Bringing Luciano Floridi’s conceptions of distant writing and narrative isotropy in connection with Italo Calvino’s praxis and philosophy of literature yields a fundamental insight into the virtual interaction (the spasmodic tango) of human and Large Language Model (LLM) in the production of literary texts. Floridi’s concept of ‘distant writing’ is a methodology for using LLMs to produce text, with the writer taking on the role of designer, rather than producer, of the text. Floridi conceptualizes the ‘boundless narrative isotropy’ of distant writing as: “the principle that any narrative domain is equally workable in any direction, provided coherence is maintained”. Calvino’s work provides metaphorical models of isotropic narrative exploration that emphasize both the potential of distant writing and the importance of the reader for the constitution of literature, thereby anticipating Floridi’s conclusions. By exploring the mapping of Floridi’s LLM and Calvino’s tarot decks onto the explication of distant writing the paper shows that there is continuity between close and distant writing. Distant writing as process of literary production aligns with Calvino’s creative practice and vision of a combinatorial writing in which a machine could replace the human writer: Calvino’s practice is the _disautomated_ counterpart of distant writing. The result is the navigation of narrative space, while maintaining narrative isotropy: a de-anthropomorphized conception of what it is to produce narrative literature that undermines any technological exceptionalism about LLMs' narrative capabilities, and refutes Floridi’s idea of a qualitatively new access to narrative modality via LLMs. Finally, this conclusion is connected to the multiplicity of reading and an informational conception of authorship; the problem of automating cultural universalism is raised; and literary reductionism is conceptualized as threat for the AI-generated literature to come.

The assumptions and value commitments in the discourse on and development of Lethal Autonomous Weapons Systems (LAWS) do not reflect the plurality of perspectives from the South. Both the regulatory discourse on LAWS and the development of these military Artificial Intelligence (AI) systems are entangled with epistemic forms of exclusion. LAWS suffer from, on the one hand, a vulnerability to unintended risks and failures due to an epistemic misrepresentation of targets and cultural particulars, and, on the other hand, the failure to distinguish between civilian and military targets rooted in algorithmic bias and exclusion of affected parties from the training data and algorithm development. In this paper, it is argued that three forms of exclusion of the global South stand out: a lack of training data for the algorithmic systems, stakeholder exclusion from the development of LAWS, and the exclusion from the regulation discourse. These exclusions are conceptualized as a form of discriminatory epistemic injustice. As an extension of a taxonomy of algorithmic epistemic injustice, we make the case for the concept of algorithmic epistemic marginalization as explainer for the epistemic forms of exclusion—‘epistemic misalignments’ of LAWS with the global South. Algorithmic epistemic marginalization is defined as ‘the rendering marginal of the experiences of citizens from the global South and their epistemic-cultural particulars in LAWS development and regulation’ and is shown to lead to representational harm and system failure. Finally, the importance of institutional safeguards and epistemic inclusivity for minimizing the epistemic misalignments at the base of LAWS’ algorithmic epistemic marginalization.

Epistemic injustice related to AI is a growing concern. In relation to machine learning models, epistemic injustice can have a diverse range of sources, ranging from epistemic opacity, the discriminatory automation of testimonial prejudice, and the distortion of human beliefs via generative AI’s hallucinations to the exclusion of the global South in global AI governance, the execution of bureaucratic violence via algorithmic systems, and interactions with conversational artificial agents. Based on a proposed general taxonomy of epistemic injustice, this paper first sketches a taxonomy of the types of epistemic injustice in the context of AI, relying on the work of scholars from the fields of philosophy of technology, political philosophy and social epistemology. Secondly, an additional conceptualization on epistemic injustice in the context of AI is provided: generative hermeneutical erasure. I argue that this injustice the automation of ‘epistemicide’, the injustice done to epistemic agents in their capacity for collective sense-making through the suppression of difference in epistemology and conceptualization by LLMs. AI systems’ ‘view from nowhere’ epistemically inferiorizes non-Western epistemologies and thereby contributes to the erosion of their epistemic particulars, gradually contributing to hermeneutical erasure. This work’s relevance lies in proposal of a taxonomy that allows epistemic injustices to be mapped in the AI domain and the proposal of a novel form of AI-related epistemic injustice.

Bringing Luciano Floridi’s conceptions of distant writing and narrative isotropy in connection with Italo Calvino’s praxis and philosophy of literature yields a fundamental insight into the virtual interaction (the spasmodic tango) of human and Large Language Model (LLM) in the production of literary texts. Floridi’s concept of ‘distant writing’ is a methodology for using LLMs to produce text, with the writer taking on the role of designer, rather than producer, of the text. Floridi conceptualizes the ‘boundless narrative isotropy’ of distant writing as: “the principle that any narrative domain is equally workable in any direction, provided coherence is maintained”. Calvino’s work provides metaphorical models of isotropic narrative exploration that emphasize both the potential of distant writing and the importance of the reader for the constitution of literature, thereby anticipating Floridi’s conclusions. By exploring the mapping of Floridi’s LLM and Calvino’s tarot decks onto the explication of distant writing the paper shows that there is continuity between close and distant writing. Distant writing as process of literary production aligns with Calvino’s creative practice and vision of a combinatorial writing in which a machine could replace the human writer: Calvino’s practice is the _disautomated_ counterpart of distant writing. The result is the navigation of narrative space, while maintaining narrative isotropy: a de-anthropomorphized conception of what it is to produce narrative literature that undermines any technological exceptionalism about LLMs' narrative capabilities, and refutes Floridi’s idea of a qualitatively new access to narrative modality via LLMs. Finally, this conclusion is connected to the multiplicity of reading and an informational conception of authorship; the problem of automating cultural universalism is raised; and literary reductionism is conceptualized as threat for the AI-generated literature to come.

Understanding human behaviour, neuroscience and psychology using concepts from the domain of AI is increasing in popularity. Given the massive integration of AI technologies into our daily lives, AI-related concepts are being used to compare AI systems with human behaviour, brain functions, and cognitive abilities like language acquisition. But scientists and philosophers are also increasingly tempted to take the AI-framing of the human conceptual domain as a literal one. This paper investigates the epistemic and practical success of these ‘AI-framings’: What does it mean to apply the conceptual constellation of AI to the human conceptual domain? We consider and compare two possible answers: either these examples are conceptual metaphors, or they are attempts at conceptual engineering. Firstly, we argue that when viewed as conceptual metaphors, the AI-framed descriptions risk committing the “map-territory fallacy”. Secondly, we argue the comparisons also contain a misleading ‘double metaphor’ because of the metaphorical connection between human psychology and computation at the conceptual foundation of computation. But we also argue that there is a possible semantic catch to the AI-framing, which is captured by the conceptual engineering view. This is that the AI-framings point towards avenues for forms of conceptual engineering. If the challenges of conceptual ethics and reductionism are overcome, some AI-framings might enrich our epistemic and practical lives. So, at its worst - as implicit conceptual metaphor - the AI-framing leads us completely astray; at its best, it prompts us to reflect anew on how the boundaries of our current concepts serve us and how they could be improved.

Epistemic injustice related to AI is a growing concern. In relation to machine learning models, epistemic injustice can have a diverse range of sources, ranging from epistemic opacity, the discriminatory automation of testimonial prejudice, and the distortion of human beliefs via generative AI’s hallucinations to the exclusion of the global South in global AI governance, the execution of bureaucratic violence via algorithmic systems, and interactions with conversational artificial agents. Based on a proposed general taxonomy of epistemic injustice, this paper first sketches a taxonomy of the types of epistemic injustice in the context of AI, relying on the work of scholars from the fields of philosophy of technology, political philosophy and social epistemology. Secondly, an additional conceptualization on epistemic injustice in the context of AI is provided: generative hermeneutical erasure. I argue that this injustice the automation of ‘epistemicide’, the injustice done to epistemic agents in their capacity for collective sense-making through the suppression of difference in epistemology and conceptualization by LLMs. AI systems’ ‘view from nowhere’ epistemically inferiorizes non-Western epistemologies and thereby contributes to the erosion of their epistemic particulars, gradually contributing to hermeneutical erasure. This work’s relevance lies in proposal of a taxonomy that allows epistemic injustices to be mapped in the AI domain and the proposal of a novel form of AI-related epistemic injustice.

As the geopolitical superpowers race to regulate the digital realm, their divergent rights-centered, market-driven, and social-control-based approaches require a global compact on digital regulation. If diverse regulatory jurisdictions remain, forms of domination entailed by cultural imposition and hermeneutical injustice related to AI legislation and AI systems will follow. We argue for consensual regulation on shared substantive issues, accompanied by proper standardization and coordination. Failure to attain consensus will fragment global digital regulation, enable regulatory capture by authoritarian powers or bad corporate actors, and deepen the historical geopolitical power asymmetries between the global South and the global North. To prevent an unjust regulatory landscape where the global South’s cultural and hermeneutic resources are absent, two principles for the Global Digital Compact to counter these prospective harms are proposed and discussed: (1) “recognitive consensus on key substantive benefits and harms” and (2) “procedural consensus on global coordination and essential standards.”

What are the limits of Left Wittgensteinianism's point- and need-based account of conceptual change? Based upon Wittgenstein's account of certainty and the riverbed analogy for conceptual change in On Certainty, the question is raised whether Queloz and Cueni's redevelopment of Left Wittgensteinianism can account for the multiplicitous forms of change these concepts are subject to. I argue that Left Wittgensteinianism can only partially do so, because it overemphasises the role of criticism-driven conceptual change, due to its focus on the reason-based contingency of the practices of a local ‘we’. In response, it is argued that Left Wittgensteinianism should be fortified with (i) gradual changes to concepts' sociocultural constraints that concept-users are unaware of and (ii) evolutionary and environmental changes to the biological determinants of natural constraints of conceptual cores. In the end, there are conceptual practices like holding for certain that are generally, and fully contingent, but simultaneously inevitable not only for ‘us’ but also for many other delimitations of ‘we’. Subsequently, the compatibility of this Wittgensteinian account of conceptual change with pragmatic genealogy is discussed. It is concluded that thinking about conceptual changes to practices cannot be about the possibility of criticism alone nor succeed without the inclusion thereof.

What are the limits of Left Wittgensteinianism's point- and need-based account of conceptual change? Based upon Wittgenstein's account of certainty and the riverbed analogy for conceptual change in On Certainty, the question is raised whether Queloz and Cueni's redevelopment of Left Wittgensteinianism can account for the multiplicitous forms of change these concepts are subject to. I argue that Left Wittgensteinianism can only partially do so, because it overemphasises the role of criticism-driven conceptual change, due to its focus on the reason-based contingency of the practices of a local ‘we’. In response, it is argued that Left Wittgensteinianism should be fortified with (i) gradual changes to concepts' sociocultural constraints that concept-users are unaware of and (ii) evolutionary and environmental changes to the biological determinants of natural constraints of conceptual cores. In the end, there are conceptual practices like holding for certain that are generally, and fully contingent, but simultaneously inevitable not only for ‘us’ but also for many other delimitations of ‘we’. Subsequently, the compatibility of this Wittgensteinian account of conceptual change with pragmatic genealogy is discussed. It is concluded that thinking about conceptual changes to practices cannot be about the possibility of criticism alone nor succeed without the inclusion thereof.

Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI (‘affective artificial agents’), with consequences that range from love to suicide. The philosophical question of whether such ascriptions are warranted is thus very relevant. This paper advances the argument that LLMs instantiate language users in Ludwig Wittgenstein’s sense but that ascribing psychological predicates to these systems remains a functionalist temptation. Social AIs are not full-blown language users, but rather more like Italo Calvino’s literature machines. The ideas of LLMs as Wittgensteinian language users and Calvino’s literature-producing writing machine are combined. This sheds light on the misguided functionalist temptation inherent in moving from equating the two to the ascription of psychological predicates to social AI. Finally, the framework of mortal computation is used to show that social AIs lack the basic autopoiesis needed for narrative façons de parler and their role in the sensemaking of human (inter)action. Such psychological predicate ascriptions could make sense: the transition ‘from quantity to quality’ can take place, but its route lies somewhere between life and death, not between affective artifacts and emotion approximation by literature machines.

The development and deployment of machine learning and artificial intelligence (AI) engender “AI colonialism”, a term that conceptually overlaps with “data colonialism”, as a form of injustice. AI colonialism is in need of decolonization for three reasons. Politically, because it enforces digital capitalism’s hegemony. Ecologically, as it negatively impacts the environment and intensifies the extraction of natural resources and consumption of energy. Epistemically, since the social systems within which AI is embedded reinforce Western universalism by imposing Western colonial values on the global South when these manifest in the digital realm is a form of digital capitalism. These reasons require a new conceptualization of AI decolonization. First this paper draws from the historical debates on the concepts of colonialism and decolonization. Secondly it retrieves Achille Mbembe’s notion of decolonization as disenclosure to argue that the decolonization of AI will have to be the abolishment of political, ecological and epistemic borders erected and reinforced in the phases of its design, production, development of AI in the West and drawing from the knowledge from the global South. In conclusion, it is discussed how conceiving of decolonial AI as form of disenclosure opens up new ways to think about and intervene in colonial instantiations of AI development and deployment, in order to empower “the wretched of AI”, re-ecologise the unsustainable ecologies AI depends on and to counter the colonial power structures unreflective AI deployment risks to reinforce.

In Philosophy and Technology 36, David Watson discusses the epistemological and metaphysical implications of unsupervised machine learning (ML) algorithms. Watson is sympathetic to the epistemological comparison of unsupervised clustering, abstraction and generative algorithms to human cognition and sceptical about ML’s mechanisms having ontological implications. His epistemological commitments are that we learn to identify “natural kinds through clustering algorithms”, “essential properties via abstraction algorithms”, and “unrealized possibilities via generative models” “or something very much like them.” The same issue contains a commentary on Watson’s paper in which Tom Sterkenburg fiercely opposes the epistemological claim that clustering algorithms can identify natural kinds. Sterkenburg argues there’s nothing about clustering arguments themselves that enables natural kind identification. What’s at stake in the Watson-Sterkenburg debate is whether it is possible for clustering algorithms to identify natural kinds and whether they underly human identification of natural kinds. My contribution to the Watson-Sterkenburg debate is twofold. First, I argue Sterkenburg’s criticism of Watson’s claim is too severe because it denies any clustering algorithm to identify any natural kind. Secondly, I argue Watson’s reply overestimates both clustering algorithms’ and humans’ access to natural kinds and his claim has to be restricted accordingly to ‘We identify kinds via clustering algorithms, or something very much like them’.

James Baldwin and Ludwig Wittgenstein were both concerned with what language use is capable of and what the duty of the thinker should be. This essay examines, via Italo Calvino’s ideas on the relationship between writing and world, what the contrast Wittgenstein/Baldwin tells us about the ethics of meaning. Wittgenstein’s ‘leaves everything as it is’ conception of thought is contrasted with Baldwin’s thoughts on racism, language and the duty of the writer. It is concluded that Baldwin drives Wittgenstein’s philosophical position further than Wittgenstein could do himself and that ethically neutral language use is itself a linguistic confusion.