Invited Lecture at the SRM ACM Student Chapter, India, on Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence. The lecture proposes a historical and technical overview of strategies for commonsense reasoning in AI.

The commercial VR/AR marketplace is gaining ground and is becoming an ever larger and more significant component of the global economy. While much attention has been paid to the commercial promise of VR/AR, comparatively little attention has been given to the ethical issues that VR/AR technologies introduce. We here examine existing codes of ethics proposed by the ACM and IEEE and apply them to the unique ethical facets that VR/AR introduces. We propose a VR/AR code of ethics for developers and (...) apply this code to several commercial applications. (shrink)

Bu makalede, bilim felsefecisi kimliğiyle tanınan Thomas Kuhn’un eğitim ve özellikle fen eğitimi alanındaki görüşlerine değinilmektedir. Fen eğitimi, bilim, bilimin doğası ve bilim uygulamaları hakkında düşünceler geliştirmeye odaklanarak fen öğrenimi için gerekli olan beceri ve anlayışın geliştirilmesini amaçlamaktadır. Fen eğitiminin temel amaçlarından biri bilimin gerçek doğasının tespit edilmesi ve bu doğrultuda bir eğitim modelinin belirlenmesidir. Bu çerçevede Kuhn’un bilim tarihine yönelik incelemeleri neticesinde ileri sürdüğü paradigma kavramı bilimin doğası ve fen eğitimi konusundaki görüşlerin değişimine yol açmıştır. Kuhn açısından fen eğitimi (...) yürürlükteki bilim yapma tarzının temelinde yatan paradigma ve öğretilerinin bilim insanlarına ve öğrencilere aktarılması sürecidir, bu nedenle fen eğitimi yalnızca olağan bilim döneminde mümkündür. Kuhn’un eğitim modeli, mevcut paradigmayla ilişkili olarak karşılaşılan bulmaca ya da sorunları çeşitli örneklerden hareketle tekrar tekrar çözmeye çalışan öğrenciler aracılığıyla gerçekleştirilir. Kuhn’un olağan bilimin sınırları içerisinde kalarak değerlendirdiği fen eğitimi anlayışı eleştirel düşünceyi engellediği iddiasıyla Karl Popper, John Watkins ve Richard Bailey tarafından katı, tutucu, dogmatik ve endoktrinasyonu vurgulayan bir eğitim anlayışı olarak görülmektedir. Bu çerçevede makalede, öncelikli olarak Kuhn’un bilimin doğası ve bilimin gelişim tarzına yönelik belirlemeleri doğrultusunda fen eğitimine yönelik düşünceleri ve bu düşüncelerin eğitim alanındaki yansımaları incelenmektedir. Ardından, Kuhn’un fen eğitimi üzerine görüşlerinin iddia edildiği gibi dogmatik bir yapıda olmadığı, endoktrinasyonu ya da zorla öğretimi vurgulamadığı, bu tür yorumların radikal bir yaklaşımdan öteye gidemediği ileri sürülmektedir. Son olarak makalede, Kuhn’un fen eğitimi anlayışının yalnızca bir durum tespiti ya da bir fen eğitimi tasviri olarak değerlendirilmesi gerektiği düşüncesi ön plana çıkarılmaktadır. -/- In this article, Thomas Kuhn’s impact, who is known as a philosopher of science, on science education are mentioned. Science education aims to develop the skills and understanding necessary for science learning, with a focus on developing ideas about science and the nature of science. One of the main purposes of science education is to determine the true nature of science and to determine an education model in this direction. In this context, the concept of paradigm, which Kuhn put forward as a result of his studies on the history of science, has led to a change in views on the nature of science and science education. For Kuhn, science education is the process of conveying the paradigm underlying the current way of doing science to scientists and students because science education is possible only in the normal science period. Kuhn’s educational model is carried out through students who repeatedly try to solve puzzles or problems encountered in relation to the current paradigm. Kuhn’s understanding of science education is seen by Karl Popper, John Watkins and Richard Bailey as a rigid, conservative, dogmatic and indoctrinational education approach with the claim that it prevents critical thinking. In this context, the article primarily examines Kuhn’s thoughts on science education and the reflections of these thoughts in the field of education. Then, it is argued that Kuhn’s views on science education are not dogmatic as claimed, he does not emphasize indoctrination, and that such interpretations cannot go beyond a radical approach. Finally, in the article, it is emphasized that Kuhn’s understanding of science education should be evaluated only as a description of science education. (shrink)

What were the true reasons of the second scientific revolution? – To answer the question, the epistemic model is applied, according to which radical breakthroughs in science were not due to the fanciful excogitation of new ideas ‘ex nihilo’, but rather to the tedious, long-term and troublesome processes of the mutual lapping, reconciliation, interpenetration and intertwinement of ‘old’ research traditions preceding such breaks. It is contended that Einstein's 'annus mirabilis' constituted an acme of the second scientific revolution. To fathom in (...) what felicitous ways Einstein's 1905 writings hang together one is bound to pay special tribute to his longed strive for unity evinced in incessant attempts to coordinate the profound research traditions of classical physics. Though Einstein's efforts sprung out of Max Planck's pioneering attempts to comprehend electromagnetic phenomena through the lenses of conceptual structures of statistical thermodynamics . It was Planck, who clearly realized the cross-contradiction between 'the physics of material bodies’ and ‘the physics of the ether' and outlined the sketch of its withdrawal: the paradigms 'must be modified to remain compatible'. And it was Planck who took the first step in modifying the physics of the ether and contending that 'not only matter itself but also the effects radiated from matter' possess discontinuous properties, which can be characterized by a new natural constant: the elementary quantum of action. Einstein's part consisted in that he took the second step in modifying the second component of the encounter – the physics of material bodies. Einstein’s foolhardy light quanta hypothesis and distinctive special theory of relativity turn out to be mere milestones of the unwinding of Maxwellian electrodynamics and statistical thermodynamics reconcilement research program. The notorious conception of luminiferous ether was a substantial obstacle for Einstein’s wayward statistical thermodynamics in which the pivotal lead was played by flagrant light quanta paper. Einstein was aware that his enticing light quanta hypothesis was too audacious to be taken literally and he laid out his version of 'electrodynamics of moving bodies' in a markedly Machian/ Duhemian, phenomenological way. As a result of the revision of the second scientific revolution key episode, the arguments are exhibited in favor of the necessity to modify the history of the genesis of general relativity; correspondingly, the process of unification of electromagnetic and weak interactions that took place in the second half of the XX-th century is scrutinized. Eventually, the encounter and interpenetration of the two dominating research traditions of modern physics – that of general relativity and quantum field theory – is elicited. (shrink)

An interview with The philosopher James Moore on the occasion of his ACM Making a Difference Award, in 2003.

Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.

Joseph Conrad’s Heart of Darkness is a frequent point of reference for Edward Said’s investigations into the various forces that structure and define the encounter of imperial societies with others. In Culture and Imperialism, Said explains the importance of Conrad’s novella by linking it to his concept of culture as the aesthetic acme of a society that simultaneously marks it and divides it from others. In Heart of Darkness, Said claims, we have a narrative that challenges its own imperial society (...) by emphasizing the ambiguity of its cultural limit. Heart of Darkness is thereby able to dramatize and emphasize the constituent elements of imperial society, even as it is unable to exceed that society’s fundamental character. Said’s reading is important, and even vital, for an appreciation of the complexities of Conrad’s novella, but it does not go far enough. The ambiguity of Conrad’s depiction of imperial society is only an ambiguity to the extent that the novella is critiqued at the level of content, with a corresponding lack of emphasis upon its rhetorical form. Through a consideration of the three primary elements of this form – the careful situation of the Nellie as the site of the narrative, the work of interruption in Marlow’s narrative, and the reverberation of Kurtz’s dying words in the conclusion of the novella – this essay argues that there is very little ambiguity in Conrad’s text. Indeed, what ambiguity remains is a function of its effort to dramatize the limit of imperialism precisely as a limitation, as a cultural determinant that through its form perpetually determines other societies as inferior, even as this very culture, as a limit set against these other societies, shows their richness to which imperialism is essentially blind. (shrink)

I claim that ‘cause and effect’ only appears to involve distinct existences insofar as we can’t adequately understand the relationship, or insofar as we are determined to look at the matters of fact involved from a logically deductive point of view. Since ‘cause and effect’ often represents the first stab at understanding what happens in a situation, this means it will often appear to involve distinct existences, and since logical deduction is the acme of what it is to perform adequate (...) reasoning, for philosophers, this re-enforces this appearance, to philosophers. In contrast I claim we can try to avoid drawing conclusions beyond objects or factors in a situation, by comparing them as we attempt to trace them about. In so far as we succeed, since we have not had to go beyond the continued existence of those factors, they themselves must appear sufficient to produce that part of the situations they continue into and so construct. I also claim if somethings appear themselves sufficient to bring something about this is inconsistent with the claim it depends on something else e.g. human understanding, or language. Two cases; 1) If we assume this object has, or continues to have some properties e.g. weight, then on this basis we can validly deduce such & such consequences. 2) The continued existence of this object with weight would (or is) itself be sufficient to bring about…. The first makes what we are up to depend on our mode of reasoning, or what we recognize as ‘our way and principles of reasoning’. The second discovers the situation to be autonomous. (shrink)

“İntihar Üzerine” (Ek 1) ve “Ruhun Ölümsüzlüğü Üzerine” (Ek 2) denemeleri, David Hume’un din bağlamında dogmatik inanışları, uslamlamaları en keskin bir biçimde eleştirdiği yazılarıdır. Görgül felsefesinin temel doğruları ve izlediği kuşkucu yöntem uyarınca ortaya koyduğu sonuçlar, bu denemelerin hem yayınlandıkları dönemde hem de sonrasında pek çok olumsuz eleştiriyle karşılaşmasına yol açmıştır. İnsanın doğasına ilişkin her türlü konuyu soruşturma niyetliliği ile yola çıkan Hume, dogmatik dinin ve uygulamalarının köklendiği inanışları ve uslamlamalarını da aynı niyetle irdelemiştir. Özellikle döneminde yaşanan toplumsal sorunların bu (...) dogmalara duyulan kuşkusuz inançlardan köklendiğini göstermeye çalıştığı bu iki denemenin, yine aynı dogmalara dayanarak eleştirilmesi, basımının engellenmesi ve metinlere müdahale edilmesi ise ironiktir. Bu çalışmada, Hume’un her iki denemedeki savlarının bir çözümlemesi değil, denemelerde ele alınan sorunun ne kadar gerçek olduğu, bu iki denemenin yayınlanma süreci örnek gösterilerek incelenecektir. (shrink)

Ken Forbus's Qualitative Process Theory (QPT) is a popular theory for reasoning about the physical aspects of the daily world. Qualitative Process Theory Using Linguistic Variables by Bruce D'Ambrosio (Springer-Verlag, New York, 1989) is an attempt to fill some gaps in QPT.

This is a review of Mind Design II: Philosophy, Psychology, and Artificial Intelligence, edited by John Haugeland and published by The MIT Press in 1997.

Review of "Artificial Intelligence: An MIT Perspective, Volume 1: Expert Problem Solving, Natural Language Understanding, Intelligent Computer Coaches, Representation and Learning," Patrick Henry Winston & Richard Henry Brown (eds.), The MIT Press, Cambridge, MA, 1979.

Review of "Artificial Intelligence: An MIT Perspective, Volume 2: Understanding Vision, Manipulation, Computer Design, Symbol Manipulation," Patrick Henry Winston & Richard Henry Brown (eds.), The MIT Press, Cambridge, MA, 2nd printing, 1980.

This is a short piece of humor (I hope) on nonstandard set theories. An earlier version appeared in Bull. EATCS 45: 146-147 (1991).

We provide an intuitive motivation for the hyperreal numbers via electoral axioms. We do so in the form of a Socratic dialogue, in which Protagoras suggests replacing big-oh complexity classes by real numbers, and Socrates asks some troubling questions about what would happen if one tried to do that. The dialogue is followed by an appendix containing additional commentary and a more formal proof.

One shortcoming of the chain rule is that it does not iterate: it gives the derivative of f(g(x)), but not (directly) the second or higher-order derivatives. We present iterated differentials and a version of the multivariable chain rule which iterates to any desired level of derivative. We first present this material informally, and later discuss how to make it rigorous (a discussion which touches on formal foundations of calculus). We also suggest a finite calculus chain rule (contrary to Graham, Knuth (...) and Patashnik's claim that "there's no corresponding chain rule of finite calculus"). (shrink)

I examine the legitimacy of immigration controls in the context of Canada and this country’s restrictive immigration policies. Despite the fundamental, philosophical arguments against immigration restrictions, the necessity of immigration controls is rarely questioned in Canadian politics. In this paper I suggest that there is an incredible cynicism of Canadian immigration policies with respect to this country’s own political principles. The idea of international migration controls is neither sustainable from a larger liberal- theory perspective nor a political-economy viewpoint. I suggest (...) that geographers should imagine alternatives to the current systems of immigration control and the regulation of the international movement of people. (shrink)

The advent of the so-called Companion Robots is raising many ethical concerns among scholars and in the public opinion. Focusing mainly on robots caring for the elderly, in this paper we analyze these concerns to distinguish which are directly ascribable to robotic, and which are instead preexistent. One of these is the “deception objection”, namely the ethical unacceptability of deceiving the user about the simulated nature of the robot’s behaviors. We argue on the inconsistency of this charge, as today formulated. (...) After that, we underline the risk, for human-robot interaction, to become a hallucinatory relation where the human would subjectify the robot in a dynamic of meaning-overload. Finally, we analyze the definition of “quasi-other” relating to the notion of “uncanny”. The goal of this paper is to argue that the main concern about Companion Robots is the simulation of a human-like interaction in the absence of an autonomous robotic horizon of meaning. In addition, that absence could lead the human to build a hallucinatory reality based on the relation with the robot. (shrink)

We introduce translations between display calculus proofs and labeled calculus proofs in the context of tense logics. First, we show that every derivation in the display calculus for the minimal tense logic Kt extended with general path axioms can be effectively transformed into a derivation in the corresponding labeled calculus. Concerning the converse translation, we show that for Kt extended with path axioms, every derivation in the corresponding labeled calculus can be put into a special form that is translatable to (...) a derivation in the associated display calculus. A key insight in this converse translation is a canonical representation of display sequents as labeled polytrees. Labeled polytrees, which represent equivalence classes of display sequents modulo display postulates, also shed light on related correspondence results for tense logics. (shrink)

Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation outcomes? (...) If k% of employers were to voluntarily adopt a fairness-promoting intervention, should we expect k% progress (in aggregate) towards the benefits of universal adoption, or will the dynamics of partial compliance wash out the hoped-for benefits? How might adopting a global (versus local) perspective impact the conclusions of an auditor? In this paper, we propose a simple model of an employment market, leveraging simulation as a tool to explore the impact of both interaction effects and incentive effects on outcomes and auditing metrics. Our key findings are that at equilibrium: (1) partial compliance by k% of employers can result in far less than proportional (k%) progress towards the full compliance outcomes; (2) the gap is more severe when fair employers match global (vs local) statistics; (3) choices of local vs global statistics can paint dramatically different pictures of the performance vis-a-vis fairness desiderata of compliant versus non-compliant employers; (4) partial compliance based on local parity measures can induce extreme segregation. Finally, we discuss implications for auditors and insights concerning the design of regulatory frameworks. (shrink)

Dramatic advances in 3D Web technologies have recently led to widespread development of virtual world Web browsers and 3D content. A natural question is whether 3D thumbnails can be used to find one’s way about such 3D content the way that text and 2D thumbnail images are used to navigate 2D Web content. We have conducted an empirical experiment that shows interactive 3D thumbnails, which we call worldlets, improve travelers’ landmark knowledge and expedite wayfinding in virtual environments.

Virtual environment landmarks are essential in wayfinding: they anchor routes through a region and provide memorable destinations to return to later. Current virtual environment browsers provide user interface menus that characterize available travel destinations via landmark textual descriptions or thumbnail images. Such characterizations lack the depth cues and context needed to reliably recognize 3D landmarks. This paper introduces a new user interface affordance that captures a 3D representation of a virtual environment landmark into a 3D thumbnail, called a worldlet. Each (...) worldlet is a miniature virtual world fragment that may be interactively viewed in 3D, enabling a traveler to gain first-person experience with a travel destination. In a pilot student conducted to compare textual, image, and worldlet landmark representations within a wayfinding task, worldlet use significantly reduced the overall travel time and distance traversed, virtually eliminating unnecessary backtracking. (shrink)

In this position paper for the 2019 CSCW workshop Good Systems: Ethical AI for CSCW I propose one tool and one idea for navigating the complex ethical problem space that results from the interaction of human and/or AI agents in shared, hopefully cooperative, computing environments.

The aim of this project to expose the reasons behind the pandemic of misinformation (henceforth, PofM) by examining the enabling conditions of epistemic agency and the emerging technologies that threaten it. I plan to research the emotional origin of epistemic agency, i.e. on the origin of our capacity to acquire justification for belief, as well as on the significance this emotional origin has for our lives as epistemic agents in our so-called Misinformation Age. This project has three objectives. First, I (...) plan to expose the degree to which epistemic agency is made possible by an under-researched species of emotion called epistemic feelings. Perhaps, the most epistemically significant is the feeling of confidence. In particular, epistemic feelings make epistemic agency possible by making errors in reasoning salient or the potential lack thereof. -/- Second, in order to diagnose the reasons for PofM, I will analyze the emotional basis of epistemic agency in the context of emerging technologies. Epistemic feelings ought to be construed as motivators of epistemic acts, specifically acts following exposure to misinformation spread by social media. For example, a recent study found that subjects on YouTube have a 6.3% probability in five clicks to go from watching innocuous videos to misogynistic videos. Accordingly, one prominent view holds that social media algorithms lead subjects down the proverbial rabbit hole, producing content that elicits strong emotional reactions. -/- But under-researched is the degree to which these emotions are intertwined with epistemic feelings, so that subjects are likely to misjudge the information as correct due to being primed to do so by processing the AI's suggested media. Thus, when this technology is used in epistemic practices, the result is invariably epistemically bad behavior because of how this manner of producing content motivates epistemic acts through the production of erroneous feelings of confidence, which result from the perceived ease of cognitive processing: the content is easy to process and so, the subject confidently misjudges, it is true. As of yet, an account of this cognitive and emotional decision-making process has not been used to analyze how emerging technologies are threatening epistemic agency, and thus our wellbeing as knowers. -/- Finally, I plan to develop therapeutics for PofM by outlining how to reform our collective epistemic practices. Thus, this project complements existing research in virtue epistemology, specifically by articulating the challenges to cultivating epistemic virtues and warding off the vices of the mind. In summation, the project aims to account for how emerging technologies are committing a form of epistemic injustice through the exploitation of cognitive biases and the production of erroneous epistemic feelings, with the overarching goal being a framework for convalescing from the pandemic of misinformation plaguing our age. (shrink)

In this position paper, we introduce a new epistemic lens for analyzing algorithmic harm. We argue that the epistemic lens we propose herein has two key contributions to help reframe and address some of the assumptions underlying inquiries into algorithmic fairness. First, we argue that using the framework of epistemic injustice helps to identify the root causes of harms currently framed as instances of representational harm. We suggest that the epistemic lens offers a theoretical foundation for expanding approaches to algorithmic (...) fairness in order to address a wider range of harms not recognized by existing technical or legal definitions. Second, we argue that the epistemic lens helps to identify the epistemic goals of inquiries into algorithmic fairness. There are two distinct contexts within which we examine algorithmic harm: at times, we seek to understand and describe the world as it is, and, at other times, we seek to build a more just future. The epistemic lens can serve to direct our attention to the epistemic frameworks that shape our interpretations of the world as it is and the ways we envision possible futures. Clarity with respect to which epistemic context is relevant in a given inquiry can further help inform choices among the different ways of measuring and addressing algorithmic harms. We introduce this framework with the goal of initiating new research directions bridging philosophical, legal, and technical approaches to understanding and mitigating algorithmic harms. (shrink)

As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are hampered by conflations (...) of various understandings of bias, ranging from neutral deviations from a standard to morally problematic instances of injustice due to prejudice, discrimination, and disparate treatment. This terminological confusion impedes efforts to address clear cases of discrimination. -/- In this paper, we examine the promises and challenges of different approaches to disambiguating bias and designing for justice. While both approaches aid in understanding and addressing clear algorithmic harms, we argue that they also risk being leveraged in ways that ultimately deflect accountability from those building and deploying these systems. Applying this analysis to recent examples of generative AI, our argument highlights unseen dangers in current methods of evaluating algorithmic bias and points to ways to redirect approaches to addressing bias in generative AI at its early stages in ways that can more robustly meet the demands of justice. (shrink)

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a (...) variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

There has been an increasing interest into how to build Artificial Moral Agents (AMAs) that make moral decisions on the basis of causation rather than mere correction. One promising avenue for achieving this is to use a causal modelling approach. This paper explores an open and important problem with such an approach; namely, the problem of what makes a causal model an appropriate model. I explore why we need to establish criteria for what makes a model appropriate, and offer-up such (...) criteria which appeals to normative considerations. (shrink)

Human-centered explainable AI (HCXAI) advocates for the integration of social aspects into AI explanations. Central to the HCXAI discourse is the Social Transparency (ST) framework, which aims to make the socio-organizational context of AI systems accessible to their users. In this work, we suggest extending the ST framework to address the risks of social misattributions in Large Language Models (LLMs), particularly in sensitive areas like mental health. In fact LLMs, which are remarkably capable of simulating roles and personas, may lead (...) to mismatches between designers' intentions and users' perceptions of social attributes, risking to promote emotional manipulation and dangerous behaviors, cases of epistemic injustice, and unwarranted trust. To address these issues, we propose enhancing the ST framework with a fifth 'W-question' to clarify the specific social attributions assigned to LLMs by its designers and users. This addition aims to bridge the gap between LLM capabilities and user perceptions, promoting the ethically responsible development and use of LLM-based technology. (shrink)

One of the main lines of research in algorithmic fairness involves individual fairness (IF) methods. Individual fairness is motivated by an intuitive principle, similar treatment, which requires that similar individuals be treated similarly. IF offers a precise account of this principle using distance metrics to evaluate the similarity of individuals. Proponents of individual fairness have argued that it gives the correct definition of algorithmic fairness, and that it should therefore be preferred to other methods for determining fairness. I argue that (...) individual fairness cannot serve as a definition of fairness. Moreover, IF methods should not be given priority over other fairness methods, nor used in isolation from them. To support these conclusions, I describe four in-principle problems for individual fairness as a definition and as a method for ensuring fairness: (1) counterexamples show that similar treatment (and therefore IF) are insufficient to guarantee fairness; (2) IF methods for learning similarity metrics are at risk of encoding human implicit bias; (3) IF requires prior moral judgments, limiting its usefulness as a guide for fairness and undermining its claim to define fairness; and (4) the incommensurability of relevant moral values makes similarity metrics impossible for many tasks. In light of these limitations, I suggest that individual fairness cannot be a definition of fairness, and instead should be seen as one tool among several for ameliorating algorithmic bias. (shrink)

In recent years, “Information Ethics” (IE) has come to mean different things to different researchers working in a variety of disciplines, including computer ethics, business ethics, medical ethics, computer science, the philosophy of information, social epistemology and library and information science. Using an ontocentric approach, this paper seeks to define the parameters of IE and thereby increase our understanding of the moral challenges associated with Information Communication Technologies.

The article provides an outline of the ontological interpretation of informational privacy based on information ethics. It is part of a larger project of research, in which I have developed the foundations of ideas presented here and their consequences. As an outline, it is meant to be self-sufficient and to provide enough information to enable the reader to assess how the approach fares with respect to other alternatives. However, those interested in a more detailed analysis, and especially in the reasons (...) offered in its favour, may wish to consult the other articles as well. (shrink)

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)

The use of language models in Web applications and other areas of computing and business have grown significantly over the last five years. One reason for this growth is the improvement in performance of language models on a number of benchmarks — but a side effect of these advances has been the adoption of a “bigger is always better” paradigm when it comes to the size of training, testing, and challenge datasets. Drawing on previous criticisms of this paradigm as applied (...) to large training datasets crawled from pre-existing text on the Web, we extend the critique to challenge datasets custom-created by crowdworkers. We present several sets of criticisms, where ethical and scientific issues in language model research reinforce each other: labour injustices in crowdwork, dataset quality and inscrutability, inequities in the research community, and centralized corporate control of the technology. We also present a new type of tool for researchers to use in examining large datasets when evaluating them for quality. (shrink)

While calls to integrate ethics into computer science education go back decades, recent high-profile ethical failures related to computing technology by large technology companies, governments, and academic institutions have accelerated the adoption of computer ethics education at all levels of instruction. Discussions of how to integrate ethics into existing computer science programmes often focus on the structure of the intervention—embedded modules or dedicated courses, humanists or computer scientists as ethics instructors—or on the specific content to be included—lists of case studies (...) and essential topics to cover. While proponents of computer ethics education often emphasize the importance of closely connecting ethical and technical content in these initiatives, most do not reflect in depth on the variety of ways in which the disciplines can be combined. In this paper, I deploy a framework from cross- disciplinary studies that categorizes academic projects that work across disciplines as multidisciplinary, interdisciplinary, or transdisciplinary, depending on the degree of integration. When applied to computer ethics education, this framework is orthogonal to the structure and content of the initiative, as I illustrate using examples of dedicated ethics courses and embedded modules. It therefore highlights additional features of cross-disciplinary teaching that need to be considered when planning a computer ethics programme. I argue that computer ethics education should aim to be at least interdisciplinary—multidisciplinary initiatives are less aligned with the pedagogical aims of computer ethics—and that computer ethics educators should experiment with fully transdisciplinary education that could transform computer science as a whole for the better. (shrink)

When a computer system causes harm, who is responsible? This question has renewed significance given the proliferation of autonomous systems enabled by modern artificial intelligence techniques. At the root of this problem is a philosophical difficulty known in the literature as the responsibility gap. That is to say, because of the causal distance between the designers of autonomous systems and the eventual outcomes of those systems, the dilution of agency within the large and complex teams that design autonomous systems, and (...) the impossibility of fully predicting how autonomous systems will behave once deployed, determining who is morally responsible for harms caused by autonomous systems is unclear at a conceptual level. I review past work on this topic, criticizing prior works for suggesting workarounds rather than philosophical answers to the conceptual problem presented by the responsibility gap. The view I develop, drawing on my earlier work on vicarious moral responsibility, explains why computing professionals are ethically required to take responsibility for the systems they design, despite not being blameworthy for the harms these systems may cause. (shrink)

Una difesa di una soluzione antirealista al paradosso del seguire una regola.

In this study, we analyzed the blinking behavior of players in a video game tournament. Our aim was to test whether spontaneous blink patterns differ across levels of expertise. We used blink rate, blink duration, blink frequency, and eyelid movements represented by the Eye Aspect Ratio (EAR) to train a machine learning classifier to discriminate between different levels of expertise. Classifier performance was highly influenced by features such as the mean, standard deviation and median EAR. Moreover, further analysis suggests that (...) blinking rate and blink duration are likely to increase along with the level of expertise. We speculate this may be indicative of a reduction in cognitive load and lowered stress of expert players. In general, our results suggest that EAR and blink patterns can be used to identify different levels of expertise of video game players. (shrink)

Humans and AI systems are usually portrayed as separate sys- tems that we need to align in values and goals. However, there is a great deal of AI technology found in non-autonomous systems that are used as cognitive tools by humans. Under the extended mind thesis, the functional contributions of these tools become as essential to our cognition as our brains. But AI can take cognitive extension towards totally new capabil- ities, posing new philosophical, ethical and technical chal- lenges. To (...) analyse these challenges better, we define and place AI extenders in a continuum between fully-externalized systems, loosely coupled with humans, and fully-internalized processes, with operations ultimately performed by the brain, making the tool redundant. We dissect the landscape of cog- nitive capabilities that can foreseeably be extended by AI and examine their ethical implications. We suggest that cognitive extenders using AI be treated as distinct from other cognitive enhancers by all relevant stakeholders, including developers, policy makers, and human users. (shrink)

While many bibliometric techniques have been employed to represent the structure of academic research communities over the years, much of this work has been conducted on scientific fields as opposed to those in the humanities. Here we use graphing techniques to present two networks that allow us to explore the structure of a subset of the philosophy community by mapping the citations between philosophical texts on the topic of ontology (the study of what exists). We find a citation gap between (...) philosophers studying material and abstract objects, and between analytic and continental ontologists, but other predictions were not confirmed by this method. We conclude by considering several additional methods for further exploring both the structure of philosophy and other disciplines in the humanities. (shrink)

Data-driven predictive algorithms are widely used to automate and guide high-stake decision making such as bail and parole recommendation, medical resource distribution, and mortgage allocation. Nevertheless, harmful outcomes biased against vulnerable groups have been reported. The growing research field known as 'algorithmic fairness' aims to mitigate these harmful biases. Its primary methodology consists in proposing mathematical metrics to address the social harms resulting from an algorithm's biased outputs. The metrics are typically motivated by -- or substantively rooted in -- ideals (...) of distributive justice, as formulated by political and legal philosophers. The perspectives of feminist political philosophers on social justice, by contrast, have been largely neglected. Some feminist philosophers have criticized the local scope of the paradigm of distributive justice and have proposed corrective amendments to surmount its limitations. The present paper brings some key insights of feminist political philosophy to algorithmic fairness. The paper has three goals. First, I show that algorithmic fairness does not accommodate structural injustices in its current scope. Second, I defend the relevance of structural injustices -- as pioneered in the contemporary philosophical literature by Iris Marion Young -- to algorithmic fairness. Third, I take some steps in developing the paradigm of 'responsible algorithmic fairness' to correct for errors in the current scope and implementation of algorithmic fairness. I close by some reflections of directions for future research. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not ameliorate more (...) general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can (...) require an incoherent theory of what social categories are. Our findings suggest that most often the social categories may not admit counterfactual manipulation, and hence may not appropriately satisfy the demands for evaluating the truth or falsity of counterfactuals. This is important because the wide- spread use of counterfactuals in machine learning can lead to misleading results when applied in high-stakes domains. Accordingly, we argue that even though counterfactuals play an essential part in some causal inferences, their use for questions of algorithmic fairness and social explanations can create more problems than they resolve. Our positive result is a set of tenets about using counterfactuals for fairness and explanations in machine learning. (shrink)

The recent wave of generative AI (GAI) systems like Stable Diffusion that can produce images from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GAI? Existing views on creatorship are mixed: some insist that GAI systems are mere tools, and human prompters are creators proper; others are more open to acknowledging more significant roles for GAI, but most conceive (...) of creatorship in an all-or-nothing fashion. We develop a novel view, called CCC (collective-centered creation), that improves on these existing positions. On CCC, GAI outputs are created by collectives in the first instance. Claims to creatorship come in degrees and depend on the nature and significance of individual contributions made by the various agents and entities involved, including users, GAI systems, developers, producers of training data and others. Importantly, CCC maintains that GAI systems can sometimes be part of a co-creating collective. We detail how CCC can advance existing debates and resolve controversies around creatorship involving GAI. (shrink)

We are quickly passing through the historical moment when people work in front of a single computer, dominated by a small CRT and focused on tasks involving only local information. Networked computers are becoming ubiquitous and are playing increasingly significant roles in our lives and in the basic infrastructure of science, business, and social interaction. For human-computer interaction o advance in the new millennium we need to better understand the emerging dynamic of interaction in which the focus task is no (...) longer confined to the desktop but reaches into a complex networked world of information and computer-mediated interactions. We think the theory of distributed cognition has a special role to play in understanding interactions between people and technologies, for its focus has always been on whole environments: what we really do in them and how we coordinate our activity in them. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human-computer interaction, sketch an integrated research framework, and use selections from our earlier work to suggest how this framework can provide new opportunities in the design of digital work materials. (shrink)

The theory of embodied cognition can provide HCI practitioners and theorists with new ideas about interac-tion and new principles for better designs. I support this claim with four ideas about cognition: (1) interacting with tools changes the way we think and perceive – tools, when manipulated, are soon absorbed into the body schema, and this absorption leads to fundamental changes in the way we perceive and conceive of our environments; (2) we think with our bodies not just with our brains; (...) (3) we know more by doing than by seeing – there are times when physically performing an activity is better than watching someone else perform the activity, even though our motor resonance system fires strongly during other person observa-tion; (4) there are times when we literally think with things. These four ideas have major implications for interaction design, especially the design of tangible, physical, context aware, and telepresence systems. (shrink)

Recent research shows – somewhat astonishingly – that people are willing to ascribe moral blame to AI-driven systems when they cause harm [1]–[4]. In this paper, we explore the moral- psychological underpinnings of these findings. Our hypothesis was that the reason why people ascribe moral blame to AI systems is that they consider them capable of entertaining inculpating mental states (what is called mens rea in the law). To explore this hypothesis, we created a scenario in which an AI system (...) runs a risk of poisoning people by using a novel type of fertilizer. Manipulating the computational (or quasi-cognitive) abilities of the AI system in a between-subjects design, we tested whether people’s willingness to ascribe knowledge of a substantial risk of harm (i.e., recklessness) and blame to the AI system. Furthermore, we investigated whether the ascription of recklessness and blame to the AI system would influence the perceived blameworthiness of the system’s user (or owner). In an experiment with 347 participants, we found (i) that people are willing to ascribe blame to AI systems in contexts of recklessness, (ii) that blame ascriptions depend strongly on the willingness to attribute recklessness and (iii) that the latter, in turn, depends on the perceived “cognitive” capacities of the system. Furthermore, our results suggest (iv) that the higher the computational sophistication of the AI system, the more blame is shifted from the human user to the AI system. (shrink)

An increasing number of regulations propose the notion of ‘AI audits’ as an enforcement mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the purpose of compliance and assurance currently have little to no agreed upon practices, procedures, taxonomies, and standards. We propose the ‘criterion audit’ as an operationalizable compliance and assurance external audit framework. We model elements of this approach after financial auditing practices, and argue (...) that AI audits should similarly provide assurance to their stakeholders about AI organizations’ ability to govern their algorithms in ways that mitigate harms and uphold human values. We discuss the necessary conditions for the criterion audit, and provide a procedural blueprint for performing an audit engagement in practice. We illustrate how this framework can be adapted to current regulations by deriving the criteria on which ‘bias audits’ for hiring algorithms can be performed, as required by the recently effective New York City Local Law 144 of 2021. We conclude by offering critical discussion on the benefits, inherent limitations, and implementation challenges of applying practices of the more mature financial auditing industry to AI auditing where robust guardrails against quality assurance issues are only starting to emerge. Our discussion as informed by experiences in performing these audits in practice highlights the critical role that an audit ecosystem plays in ensuring the effectiveness of such methodology. (shrink)

In the last decades Human-Computer Interaction (HCI) has started to focus attention on “persuasive technologies” having the goal of changing users’ behavior and attitudes according to a predefined direction. In this talk we show how some of the techniques employed in such technologies trigger some well known cognitive biases by adopting a strategy relying on logical fallacies (i.e. forms of reasoning which are logically invalid but psychologically persuasive). In particular, we will show how the mechanisms reducible to logical fallacies are (...) used to design web and mobile interfaces in domains ranging from the e-commerce to the jihadist propaganda. The final part of the talk will be devoted to point out the potential ethical dangers related to the misuse of these techniques in the design of persuasive technologies. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense categorization and knowledge (...) invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)