Feminist philosophers have long emphasized the ways in which women’s oppression takes a variety of forms depending on complex combinations of factors. These include women’s objectification, dehumanization and unjust gendered divisions of labour caused in part by sexist ideologies regarding women’s social role. This paper argues that feminized artificial intelligence (feminized AI) poses new and important challenges to these perennial feminist philosophical issues. Despite the recent surge in theoretical and empirical attention paid to the ethics of AI in general, (...) a strikingly small portion of this work has considered the impact of feminized AI in particular. Our aim is thus to draw attention to the new and pressing ethical challenges posed by feminized AI. Doing so is crucial not just to understanding the impact of these increasingly ubiquitous technologies, but also to our understanding of longstanding feminist philosophical concerns and efforts to ameliorate them. (shrink)

From music recommendation to assessment of asylum applications, machine-learning algorithms play a fundamental role in our lives. Naturally, the rise of AI implementation strategies has brought to public attention the ethical risks involved. However, the dominant anti-discrimination discourse, too often preoccupied with identifying particular instances of harmful AIs, has yet to bring clearly into focus the more structural roots of AI-based injustice. This paper addresses the problem of AI-based injustice from a distinctively epistemic angle. More precisely, I argue that the (...) injustice generated by the implementation of AI machines in our societies is, in some paradigmatic cases, also a form of epistemic injustice. With a particular focus on AIs employed as gatekeepers of our epistemic resources, this paper shows how their epistemically conformist behaviour is responsible for the marginalisation and the ostracism of minoritarian perspectives. Because it clarifies key structural flaws and weaknesses of current AI design, this paper helps make headway in critical discussion of current AI technologies. And because it forges new theoretical tools to understand forms of epistemic oppression, this paper also contributes to the advancement of feminist theorisation. (shrink)

The editorial introduces issue 21.1 of Technoetic Arts via a critical reflection on the artificial intelligence hype (AI hype) that emerged in 2022. Tracing the history of the critique of Large Language Models, the editorial underscores that there are substantial ethical challenges related to bias in the training data, copyright issues, as well as ecological challenges which the technology industry has consistently downplayed over the years. -/- The editorial highlights the distinction between the current AI technology’s reliance on extensive pre-existing (...) human-generated data for pattern recognition and the performative process inherent in art practice. Patterns of creative output can be replicated without a thorough understanding of underlying concepts. In contrast, the performative process of art practice, as explored through the conceptual frameworks of creativity by Noam Chomsky, Charles Sanders Peirce, and Roger T. Ames and with reference to an earlier publication of the editorial’s author, creates concepts and continually ‘strives to extend itself towards the unknown.’ -/- Following this introductory section, the editorial provides an overview of the ten articles featured in this issue of Technoetic Arts. The first four texts engage with emerging technologies from various perspectives in art and design. The subsequent six articles, part of a special section titled 'Perspectives from Chandigarh,' reflect a quest for meaningful existence within colonial, patriarchal, and biopolitical structures that frame everyday practices of exclusion and oppression. (shrink)

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo with (...) the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

Cultural code-switching concerns how we adjust our overall behaviours, manners of speaking, and appearance in response to a perceived change in our social environment. We defend the need to investigate cultural code-switching capacities in artificial intelligence systems. We explore a series of ethical and epistemic issues that arise when bringing cultural code-switching to bear on artificial intelligence. Building upon Dotson’s (2014) analysis of testimonial smothering, we discuss how emerging technologies in AI can give rise to epistemic oppression, and specifically, (...) a form of self-silencing that we call “cultural smothering.” By leaving the sociodynamic features of cultural code-switching unaddressed, AI systems risk negatively impacting already-marginalised social groups by widening opportunity gaps and further entrenching social inequalities. (shrink)

In 1990, Gilles Deleuze publishedPostscript on the Societies of Control, an introduction to the potentially suffocating reality of the nascent control society. This thirty-year update details how Deleuze’s conception has developed from a broad speculative vision into specific economic mechanisms clustering around personal information, big data, predictive analytics, and marketing. The central claim is that today’s advancing control society coerces without prohibitions, and through incentives that are not grim but enjoyable, even euphoric because they compel individuals to obey their own (...) personal information. The article concludes by delineating two strategies for living that are as unexplored as control society itself because they are revealed and then enabled by the particular method of oppression that is control. (shrink)

We describe the rationale for an application ontology covering the domain of human body fluids that is designed to facilitate representation, reuse, sharing and integration of diagnostic, physiological, and biochemical data, We briefly review the Blood Ontology (BLO), Saliva Ontology (SALO) and Kidney and Urinary Pathway Ontology (KUPO) initiatives. We discuss the methods employed in each, and address the project of using them as starting point for a unified body fluids ontology resource. We conclude with a description of how the (...) body fluids ontology initiative may provide support to basic and translational science. (shrink)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence may be incapable of having coherent macrophenomenal conscious experiences. Section 1 briefly surveys research indicating that neural function and phenomenal consciousness may be both analog in nature. We show that physical and phenomenal magnitudes—such as rates of neural firing and the phenomenally experienced loudness of sounds—appear to covary monotonically with the physical stimuli they represent, forming the basis for an analog relationship between (...) the three. Section 2 then argues that if this is true and micropsychism—the panpsychist view that phenomenal consciousness or its precursors exist at a microphysical level of reality—is also true, then human brains must somehow manipulate fundamental microphysical-phenomenal magnitudes in an analog manner that renders them phenomenally coherent at a macro level. However, Sect. 3 argues that because digital computation abstracts away from microphysical-phenomenal magnitudes—representing cognitive functions non-monotonically in terms of digits—digital computation may be inherently incapable of realizing coherent macroconscious experience. Thus, if panpsychism is true, digital AI may be incapable of achieving phenomenal coherence. Finally, Sect. 4 briefly examines our argument’s implications for Tononi’s Integrated Information Theory theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration. (shrink)

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...) diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)

As humans, we have an innate tendency to ascribe human-like qualities to non-human entities. Whilst sometimes helpful, such anthropomorphic projections are often misleading. This commentary considers how anthropomorphising AI contributes to its misrepresentation and hype. First, I outline three manifestations (terminology; imagery; and morality). Then, I consider the extent to which we ought to mitigate it.

Despite a growing interest in and sympathy with Confucianism, there remains a stereotyped conception of Confucian civil order as a form of authoritarian hierarchy that is responsible for various oppressions in ancient China and is reprehensible from a modern egalitarian perspective. One central target of this modern criticism is the Confucian maxim of sangang 三綱, whose underlying idea is essential for regulating the relationship between sovereign and subject, father and son, and husband and wife in traditional Confucian society. Tu Wei-ming (...) translates sangang as the “Three Bonds” and argues that it is the “least defensible legacy of Confucian ethics” from the “modern egalitarian and liberal perspective.” For Tu.. (shrink)

Roughly, empirical AI alignment research (AIA) is an area of AI research which investigates empirically how to design AI systems in line with human goals. This paper examines the role of non-epistemic values in AIA. It argues that: (1) Sciences differ in the degree to which values influence them. (2) AIA is strongly value-laden. (3) This influence of values is managed inappropriately and thus threatens AIA’s epistemic integrity and ethical beneficence. (4) AIA should strive to achieve value transparency, critical scrutiny (...) from inside and outside the discipline – involving the public –, and to empower actors without strong commercial interests. (shrink)

Edward Wilson wrote in Consilience that “Human history can be viewed through the lens of ecology as the accumulation of environmental prostheses” (1999 p 316), with technologies mediating our collective habitation of the Earth and its complex, interdependent ecosystems. Wilson emphasized the defining characteristic of complex systems, that they undergo transformations which are irreversible. His view is now standard, and his central point bears repeated emphasis, today: natural systems can be broken, species—including us—can disappear, ecosystems can fail, and technological prostheses (...) potentiate rather than ameliorate disaster when the fragilities that they introduce into our evolutionary co-dependencies with natural systems, and with each other, are under-appreciated. (shrink)

The pervasiveness of AI-empowered technologies across multiple sectors has led to drastic changes concerning traditional social practices and how we relate to one another. Moreover, market-driven Big Tech corporations are now entering public domains, and concerns have been raised that they may even influence public agenda and research. Therefore, this chapter focuses on assessing and evaluating what kind of business model is desirable to incentivise the AI for Social Good (AI4SG) factors. In particular, the chapter explores the implications of this (...) discourse for SDG #17 (global partnership) and how this goal may encourage Big Tech corporations to strengthen multi-stakeholder partnerships that promote effective public-private and civil society partnerships and the meaningful co-presence of non-market and market values. In doing so, the chapter proposes an analysis of the sociological notion of "social license to operate" (SLO) elaborated in the mining and extractive industry literature and introduces it into the discourse on sustainable digital business models and responsible management of risks in the digital age. This serves to explore how such a social license can be adopted as a practice by digital business models to foster trust, collaboration and coordination among different actors - AI researchers and initiatives, institutions and civil society at large - for the support of SDGs interrelated targets and goals. (shrink)

Philosophers have highlighted a dilemma for the criminal law. Unjust, racist policies in the United States have produced conditions in which the dispossessed are more likely to commit crime. This complicity undermines the standing of the state to blame their offenses. Nevertheless, the state has reason to punish those crimes in order to deter future offenses. Tommie Shelby proposes a way out of this dilemma. He separates the state’s right to condemn from its right to punish. I raise doubts about (...) Shelby’s proposed resolution. So long as punishment is widely and reasonably understood to condemn crime, Shelby’s proposal does not resolve the dilemma. Moreover, there is reason to think the blaming aspect of punishment plays a role in the justification of its hard treatment. I conclude by considering some other ways out of the dilemma, focusing especially on how the United States might take responsibility for its complicity. (shrink)

“Strong AI” is the view that it is possible for an artificial agent to be mentally indistinguishable from human agents. Because the behavioral dispositions of artificial agents are determined by underlying dispositional systems, Strong AI seems to entail human behavioral dispositions are also determined by dispositional systems. It is, however, highly intuitive that non-dispositional, phenomenal properties, such as being in pain, at least partially determine certain human behavioral dispositions, like the disposition to take a pain killer. Consequently, Strong AI seems (...) to conflict with an intuitive view of phenomenal properties’ role in determining human behavioral dispositions. My goal here is not directly to evaluate this tension, but rather to clarify how dispositionalism in the metaphysics of properties bears on it. While a tempting thought is that dispositionalism fits well with Strong AI’s thoroughly dispositional account of human behavior, I argue that this thought does not hold for dispositionalism in general. In particular, I argue that combining a version of the “powerful qualities view” with certain dispositionalist conceptions of the will leads to a version of the intuitive view of phenomenal properties that is radically incompatible with Strong AI. I argue further that this view also raises a challenge for the weaker claim that an artificial agent could be behaviorally indistinguishable from a human agent. (shrink)

In Beyond Neutrality, George Sher criticises the idea that state neutrality between competing conceptions of the good helps protect society from oppression. While he is correct that some governments are non-neutral without being oppressive, I argue that those governments may be neutral at the core of their foundations. The possibility of non-neutrality leading to oppression is further explored; some conceptions of the good would favour oppression while others would not. While it is possible that a non-neutral state (...) may avoid oppression, it is argued that the risks are so great that it is better to bet on government being neutral, thereby minimizing the possibility of oppression. (shrink)

This paper proposes that existing computational modeling research programs may be combined into platforms for the information of public policy. The main idea is that computational models at select levels of organization may be integrated in natural terms describing biological cognition, thereby normalizing a platform for predictive simulations able to account for both human and environmental costs associated with different action plans and institutional arrangements over short and long time spans while minimizing computational requirements. Building from established research programs, the (...) proposal aims to take advantage of current momentum in the direction of the integration of the cognitive with social and natural sciences, reduce start-up costs and increase speed of development. These are all important upshots given rising unease over the potential for AI and related technologies to shape the world going forward. (shrink)

Astrology research has been using artificial intelligence (AI) to improve the understanding of astrological properties and processes. Like the large language models of AI, astrology is also a language model with a similar underlying linguistic structure but with a distinctive layer of lifestyle contexts. Recent research in semantic proximities and planetary dominance models have helped to quantify effective astrological information. As AI learning and intelligence grows, a major concern is with maintaining its alignment with human values and intentions. Astrology has (...) an extensive background and theory on how different values and expressions of intelligence are resolved. As AI learns to interact with improved astrological models backed by evidence, the integration could produce a stable and insightful alignment of the two disciplines. (shrink)

Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions of decision-maker role appropriate- (...) ness. In terms of decision makers, the use of human decision makers over AIs generally resulted in better perceptions of respectful treatment. In terms of decision valence, people experiencing positive over negative decisions generally resulted in better perceptions of respectful treatment. In instances where these cases conflict, on some indicators people preferred positive AI decisions over negative human decisions. Qualitative responses show how people identify justice concerns with both AI and human decision making. We outline implications for theory, practice, and future research. (shrink)

Our contribution aims at individuating a valid philosophical strategy for a fruitful confrontation between human and artificial representation. The ground for this theoretical option resides in the necessity to find a solution that overcomes, on the one side, strong AI (i.e. Haugeland) and, on the other side, the view that rules out AI as explanation of human capacities (i.e. Dreyfus). We try to argue for Analytic Pragmatism (AP) as a valid strategy to present arguments for a form of weak AI (...) and to explain a notion of representation common to human and artificial agents. (shrink)

This article argues that the aesthetics of the oppressed—a series of artistic practices elaborated by Augusto Boal (1931-2009) that comprises the theatre of the oppressed, the rainbow of desire technique, and legislative theatre—utilizes art in order to resist epistemic injustice and promote democratic freedom.

This book explores how robotics and artificial intelligence can enhance human lives but also have unsettling “dark sides.” It examines expanding forms of negativity and anxiety about robots, AI, and autonomous vehicles as our human environments are reengineered for intelligent military and security systems and for optimal workplace and domestic operations. It focuses on the impacts of initiatives to make robot interactions more humanlike and less creepy. It analyzes the emerging resistances against these entities in the wake of omnipresent AI (...) applications. It unpacks efforts by developers to have ethical and social influences on robotics and AI, and confronts the AI hype that is designed to shield the entities from criticism. The book draws from science fiction, dramaturgical, ethical, and legal literatures as well as current research agendas of corporations. Engineers, implementers, and researchers have often encountered users' fears and aggressive actions against intelligent entities, especially in the wake of deaths of humans by robots and autonomous vehicles. The book is an invaluable resource for developers and researchers in the field, as well as curious readers who want to play proactive roles in shaping future technologies. (shrink)

In the rapidly evolving landscape of artificial intelligence (AI), disparities in access and benefits are becoming increasingly apparent, leading to the emergence of an AI divide. This divide not only amplifies existing socio-economic inequalities but also fosters the creation of AI caste systems, where marginalized groups—referred to as AI Dalits—are systematically excluded from AI advancements. This article explores the definitions and contributing factors of the AI divide and delves into the concept of AI caste systems, illustrating how they perpetuate inequality. (...) Furthermore, it proposes comprehensive strategies for bridging this divide through inclusive and equitable approaches. Key strategies include promoting equal access to AI education and resources, enhancing diversity and representation in AI development, implementing fair and transparent AI policies, promoting public awareness and engagement, and empowering AI Dalits through targeted initiatives. By championing an "All in AI" and "AI for All" paradigm, this paper envisions an inclusive future where the benefits of AI are universally shared, ensuring that no group is left behind in the AI-driven world. (shrink)

We might worry that our seamless reliance on AI systems makes us prone to adopting the strange errors that these systems commit. One proposed solution is to design AI systems so that they are not phenomenally transparent to their users. This stops cognitive extension and the automatic uptake of errors. Although we acknowledge that some aspects of AI extension are concerning, we can address these concerns without discouraging transparent employment altogether. First, we believe that the potential danger should be put (...) into perspective – many unreliable technologies are unlikely to be used transparently precisely because they are unreliable. Second, an agent who transparently employs a resource may also reflect (opaquely) on its reliability. Finally, agents can rely on a process transparently and be yanked out of their transparent use when it turns unreliable. When an agent is responsive to the reliability of their process in this way, they have epistemically integrated it, and the beliefs they form with it are formed responsibly. This prevents the agent from automatically incorporating problematic beliefs. Responsible (and transparent) use of AI resources – and consequently responsible AI extension – is hence possible. We end the paper with several design and policy recommendations that encourage epistemic integration of AI-involving belief-forming processes. (shrink)

In this paper, I provide a novel account of gaslighting according to which gaslighting involves mistakenly failing to see oneself as a source of reasons with respect to some domain. I argue that this account does a nice job of explaining what's gone wrong in various popular examples of gaslighting, and that it captures what different instances of gaslighting have in common even when they are quite different in other respects. I also show how this account of gaslighting explains a (...) common intuition according to which gaslighting is autonomy-undermining--something other accounts, I argue, have failed to do. And finally, I show that this explanation of why gaslighting is autonomy-undermining also shows that certain forms of oppressive socialization are autonomy-undermining as well, thus providing us with an argument in favor of more substantive theories of autonomy according to which a certain kind of self-respect is necessary for autonomy. (shrink)

Despite the importance of human blood to clinical practice and research, hematology and blood transfusion data remain scattered throughout a range of disparate sources. This lack of systematization concerning the use and definition of terms poses problems for physicians and biomedical professionals. We are introducing here the Blood Ontology, an ongoing initiative designed to serve as a controlled vocabulary for use in organizing information about blood. The paper describes the scope of the Blood Ontology, its stage of development and some (...) of its anticipated uses. (shrink)

This chapter is an extended version (almost 2x in length) of an essay first published in Australasian Philosophical Review. -/- Abstract: In On Female Body Experience, Iris Marion Young argues that a central aim of feminist and queer theory is social criticism. The goal is to understand oppression and how it functions: know thy enemy, so as to better resist. Much of Sally Haslanger’s work shares this goal, and her newest article, “Cognition as a Social Skill,” is no exception. (...) In this essay, I will specify what I believe is special and insightful about Haslanger’s theory of oppression and her most recent addition to it. However, I also explore what it is missing, namely, an account of what Young calls “individual [embodied] experience, subjectivity, and identity.” Echoing a chorus of critical voices, I argue that this omission undermines Haslanger’s ability to effectively theorize group oppression and how to resist it. The core problem is this. Haslanger privileges a third-person methodology that prioritizes social structures over all else. I conclude by amplifying a collective call to action: any adequate theory of oppression must attend to both the lived experiences of individuals and to social structures, that is, to the broad institutional and cultural underpinnings of oppression. A theory that does only one, or the other, will fail. Through this analysis, the chapter contributes to an overall aim of this volume, namely, to advance our understanding of racial and gender-based group oppressions by paying closer attention to facts about embodiment. (shrink)

In ‘Cognition as a Social Skill’, Sally Haslanger enhances her theory of oppression with new concepts: ‘mindshaping,’ ‘doxa,’ ‘heterodoxy,’ and ‘hidden transcripts.’ This essay examines these new c...

The psychological contract refers to the implicit and subjective beliefs regarding a reciprocal exchange agreement, predominantly examined between employees and employers. While contemporary contract research is investigating a wider range of exchanges employees may hold, such as with team members and clients, it remains silent on a rapidly emerging form of workplace relationship: employees’ increasing engagement with technically, socially, and emotionally sophisticated forms of artificially intelligent (AI) technologies. In this paper we examine social robots (also termed humanoid robots) as likely (...) future psychological contract partners for human employees, given these entities transform notions of workplace technology from being a tool to being an active partner. We first overview the increasing role of robots in the workplace, particularly through the advent of sociable AI, and synthesize the literature on human–robot interaction. We then develop an account of a human-social robot psychological contract and zoom in on the implications of this exchange for the enactment of reciprocity. Given the future focused nature of our work we utilize a thought experiment, a commonly used form of conceptual and mental model reasoning, to expand on our theorizing. We then outline potential implications of human-social robot psychological contracts and offer a range of pathways for future research. (shrink)

It is well-known that racism is encoded into the social practices and institutions of medicine. Less well-known is that racism is encoded into the material artifacts of medicine. We argue that many medical devices are not merely biased, but materialize oppression. An oppressive device exhibits a harmful bias that reflects and perpetuates unjust power relations. Using pulse oximeters and spirometers as case studies, we show how medical devices can materialize oppression along various axes of social difference, including race, (...) gender, class, and ability. Our account uses political philosophy and cognitive science to give a theoretical basis for understanding materialized oppression, explaining how artifacts encode and carry oppressive ideas from the past to the present and future. Oppressive medical devices present a moral aggregation problem. To remedy this problem, we suggest redundantly layered solutions that are coordinated to disrupt reciprocal causal connections between the attitudes, practices, and artifacts of oppressive systems. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...) boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

In this Interview, Professor Robert B. Brandom answered ten detailed questions about his philosophy of Rational Pragmatism and Semantic Expressivism, grouped into four topics. 1. Metaphysics and Anthropology, 2. Pragmatics and Semantics, 3. Epistemic Expressivism and 4. Philosophy of Logic. With his careful answers Professor Brandom offers many additional insights into his rigorously constructed account of the relationship “between what we say and think, and what we are saying and thinking about” around the human practice of asking for and giving (...) reasons. A final, additional question pointed at a principal motivation for putting together the present issue: how to reconcile Wittgenstein’s assertion that philosophy must not proffer any theories with the very explicit system of explanations Brandom has constructed. This same issue is addressed to some extent already in Professor Brandom’s new article contained in this issue, but his answer, asserting that he does not proffer a theory but only makes explicit what is already there, might be seen as an unambiguous statement of the continuous presence of a contested Wittgensteinian principle in Brandom’s work. (shrink)

Epistemologies have power. They have the power not only to transform worlds, but to create them. And the worlds that they create can be better or worse. For many people, the worlds they create are predictably and reliably deadly. Epistemologies can turn sacred land into ‘resources’ to be bought, sold, exploited, and exhausted. They can turn people into ‘labor’ in much the same way. They can not only disappear acts of violence but render them unnamable and unrecognizable within their conceptual (...) architectures. Settler systems of epistemic and conceptual resources and the relations among them are constructed to preclude certain forms of knowledge. This is not an accident; it is a central goal of colonial violence. Colonization and land dispossession would not be possible without the violent disruption of Indigenous knowledge systems and ongoing organized attempts to disrupt their survival. Violently disrupting the relationships of people to land is as much an epistemic project as it is a material one, and these two projects are inherently linked. The task of theorizing epistemic oppression is not only about epistemic oppression. Epistemic oppression is a story that gives language to a phenomenon in order to get past it, to carry on with the maintaining and reviving the forms of Indigenous and diasporic knowledge that colonialism has worked tirelessly to corrupt and silence. (shrink)

Arthur C. Danto did not live to witness the proliferation of AI in artistic creation. However, his philosophy of art offers key ideas about art that can provide an interesting perspective on artwork generated by artificial intelligence (AI). In this article, I analyze how his ideas about contemporary art, intention, interpretation, and authorship could be applied to the ongoing debate about AI and artistic creation. At the same time, it is also interesting to consider whether the incorporation of AI into (...) artistic creation marks a new chapter in the narrative, which seems to have reached its end, or if it represents a significant rupture with past artistic traditions. (shrink)

Artificially intelligent (AI) technologies are increasingly being used in many workplaces. It is recognised that there are ethical dimensions to the ways in which organisations implement AI alongside, or substituting for, their human workforces. How will these technologically driven disruptions impact the employee–employer exchange? We provide one way to explore this question by drawing on scholarship linking Integrative Social Contracts Theory (ISCT) to the psychological contract (PC). Using ISCT, we show that the macrosocial contract’s ethical AI norms of beneficence, non-maleficence, (...) autonomy, justice, and explicability can feed into national- and organisational-level microsocial contracts. We also outline the role of employees’ technology frames in this process. We then use an illustrative example to demonstrate how this multilevel normative background helps to inform the content of individuals’ PCs in the context of working with AI technologies. (shrink)

Oppression can be unjust from a luck egalitarian point of view even when it is the consequence of choices for which it is reasonable to hold persons responsible. This is for two reasons. First, people who have not been oppressed are unlikely to anticipate the ways in which their choices may lead them into oppressive conditions. Facts about systematic phenomena (like oppression) are often beyond the epistemic reach of persons who are not currently subject to such conditions, even (...) when they possess adequate information about the particular consequences of their choices. Second, people may be (much) less responsible for remaining in oppressive conditions, even if they are responsible for entering circumstances of oppression. Oppression that results from a person’s choice may cause or contribute to dramatic changes in that person, and these changes may be sufficient to undermine the person’s responsibility for the results of her earlier choice. (shrink)

Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.

Gender, race, and sexuality are not just identities; they are also systems of social organization – i.e., systems of privilege and oppression. This article addresses two main ways privilege and oppression (e.g., racism, misogyny, heteronormativity) are relevant topics in and for philosophical aesthetics: (i) the role of the aesthetic in privilege and oppression, and (ii) the role of philosophical aesthetics, as a discipline and a body of texts, in constructing and naturalizing relations of privilege and oppression (...) (i.e., white heteropatriarchy). The first part addresses how systems of privilege and oppression use the aesthetic. I will discuss various ways race, gender, and sexuality, as both embodied identities and broader social institutions, work with and through “the aesthetic”. The second part addresses racism and (hetero) sexism in the discipline of aesthetics. Both in its history and its present practice aesthetics’apparent neutrality on questions of privilege and oppression is actually evidence of its investment in systems of privilege and oppression. (shrink)

The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...) more fruitful exploration of this question will involve a different comparison class. We routinely treat judgments made by highly trained experts in specialized fields as fair or well-grounded even though—by the nature of expert/layperson division of epistemic labor—an expert will not be able to provide an explanation of the reasoning behind these judgments that makes sense to most other people. Regardless, laypeople are thought to be acting reasonably—and ethically—in deferring to the judgments of experts that concern their areas of specialization. I suggest that we reframe our question regarding the appropriate standards of transparency in AI as one that asks when, why, and to what degree it would be ethical to accept opacity in AI. I argue that our epistemic relation to certain opaque AI technology may be relevantly similar to the layperson’s epistemic relation to the expert in certain respects, such that the successful expert/layperson division of epistemic labor can serve as a blueprint for the ethical use of opaque AI. (shrink)

Artificial intelligence (AI), blockchain, virtual and augmented reality, (semi-)autonomous ve- hicles, autoregulatory weapon systems, enhancement, reproductive technologies and human- oid robotics – these technologies (and many others) are no longer speculative visions of the future; they have already found their way into our lives or are on the verge of a breakthrough. These rapid technological developments awaken a need for orientation: what distinguishes hu- man from machine and human intelligence from artificial intelligence, how far should the body be allowed to (...) be changed and what are the dangers and opportunities presented by these technologies? Many of these questions are also addressed to theology. For example, questions about the image of humanity, the understanding of creation, the ethics of technological body interventions or the moral status of robots. What does theology have to say about these technological developments? It is the right time for theology to scientifically explore tech- nologization and AI and to formulate answers. As technology changes the various areas of human life, society and the world around us, the places and topics of theology are also undergoing transformation. Puzio, Anna: Theology Meets AI: Examining Perspectives, Tasks, and Theses on the Intersection of Technology and Religion. In: Puzio, Anna/Kunkel, Nicole/Klinge, Hendrik (Hg.): Alexa, How Do You Feel About Religion? Theological Approaches to Technology and Artificial Intelligence (Theology and AI 1). Darmstadt: wbg 2023, S. 29–41. DOI: 10.53186/1030373. (shrink)

Artificially intelligent (AI) technologies are increasingly being used in many workplaces. It is recognised that there are ethical dimensions to the ways in which organisations implement AI alongside, or substituting for, their human workforces. How will these technologically driven disruptions impact the employee–employer exchange? We provide one way to explore this question by drawing on scholarship linking Integrative Social Contracts Theory (ISCT) to the psychological contract (PC). Using ISCT, we show that the macrosocial contract’s ethical AI norms of beneficence, non-maleficence, (...) autonomy, justice, and explicability can feed into national- and organisational-level microsocial contracts. We also outline the role of employees’ technology frames in this process. We then use an illustrative example to demonstrate how this multilevel normative background helps to inform the content of individuals’ PCs in the context of working with AI technologies. (shrink)

I offer a working analysis of the concept of 'epistemic corruption', then explain how it can help us to understand the relations between epistemic vices and social oppression, and use this to motivate a style of vice epistemology, inspired by the work of Robin Dillon, that I call critical character epistemology.

Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues that AI (...) image generation is a kind of theft. This paper analyzes, substantiates, and critiques these arguments, concluding that AI image generators involve an unethical kind of labour theft. If correct, many other AI applications also rely upon theft. (shrink)

Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive a (...) systematic treatment in the literature: when such algorithms are used in life-changing decisions, they can obstruct us from effectively shaping our lives according to our goals and preferences, thus undermining our autonomy. I argue that this concern deserves closer attention as it furnishes the call for transparency in algorithmic decision-making with both new tools and new challenges. (shrink)

This paper delves into the significance and challenges of Artificial Intelligence (AI) ethics and justice in terms of Common Good and Well-being, fairness and non-discrimination, rational public deliberation, and autonomy and control. Initially, the paper establishes the groundwork for subsequent discussions using the Academia Sinica LLM incident and the AI Technology R&D Guidelines of the National Science and Technology Council(NSTC) as a starting point. In terms of justice and ethics in AI, this research investigates whether AI can fulfill human common (...) interests and welfare. Taking AI injustice as an example, I analyze the practical assessment of AI regarding regional, industrial, and social impacts. Further, this paper discusses the challenges of fairness and non-discrimination in AI, specifically addressing the issue of training on biased data, discussing the acquisition of bias by AI and post-processing supervision issues, and emphasizing the importance of rational public deliberation in this process. Then, this research examines the challenges and countermeasures the rational public faces in public deliberation, such as the importance of education in STEM scientific literacy and technological capabilities. Finally, in discussing AI and autonomy, I propose a 'Human-Centered Approach’ rather than relying solely on the 'Technological Utility Maximization' brought by AI to achieve substantial AI justice. -/- Keywords: AI Ethics and Justice, Fairness and Non-Discrimination, Biased Data Training, Public Deliberation, Autonomy, Human-Centered Approach . (shrink)

An AI winter may be defined as the stage when technology, business, and the media come to terms with what AI can or cannot really do as a technology without exaggeration. Through discussion of previous AI winters, this paper examines the hype cycle (which by turn characterises AI as a social panacea or a nightmare of apocalyptic proportions) and argues that AI should be treated as a normal technology, neither as a miracle nor as a plague, but rather as of (...) the many solutions that human ingenuity has managed to devise. (shrink)