There have been few attempts, so far, to document the history of artificial intelligence. It is argued that the “historical sociology of scientific knowledge” can provide a broad historiographical approach for the history of AI, particularly as it has proved fruitful within the history of science in recent years. The article shows how the sociology of knowledge can inform and enrich four types of project within the history of AI; organizational history; AI viewed as technology; (...) AI viewed as cognitive science and historical biography. In the latter area the historical treatments of Darwin and Turing are compared to warn against the pitfalls of “rational reconstructions” of the past. (shrink)

We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into (...) a history of the last quarter century of the field, and provide some insights into where it has come from, where it is now, and where it might go. (shrink)

This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

Artificial Intelligence (AI) techniques have become popular in architecture and design, and several studies have focused on using these technological advancements to solve various architectural problems. AI is used in various architectural design applications, from intelligent material composition to layout solutions, and it is also vital in supporting the architecture and design education mechanism. A comprehensive understanding of literature is necessary to use these powerful tools in education adequately. This is due to the large volume of research being created and (...) disseminated on this subject as well as the increasing application of AI techniques to address various education design-related questions. This article offers a comprehensive and critical assessment of the study of artificial intelligence applications in architecture and interior design education as a course application in the history of architecture and interior design. The study's conclusions indicate that AI's implications in architecture and design re-imagination are beneficial; however, it was concluded that AI- in its current phase- cannot replace human input and perspective. The students' feedback indicates that critical thinking skills cannot be replaced, and AI complements but doesn't replace their intellect. (shrink)

Scholars, policymakers and organizations in the EU, especially at the level of the European Commission, have turned their attention to the ethics of (trustworthy and human-centric) Artificial Intelligence (AI). However, there has been little reflexivity on (1) the history of the ethics of AI as an institutionalized phenomenon and (2) the comparison to similar episodes of “ethification” in other fields, to highlight common (unresolved) challenges.Contrary to some mainstream narratives, which stress how the increasing attention to ethical aspects of AI (...) is due to the fast pace and increasing risks of technological developments, Science and Technology Studies(STS)-informed perspectives highlight that the rise of institutionalized assessment methods indicates a need for governments to gain more control of scientific research and to bring EU institutions closer to the public on controversies related to emerging technologies.This article analyzes how different approaches of the recent past (i.e. bioethics, technology assessment (TA) and ethical, legal and social (ELS) research, Responsible Research and Innovation (RRI)) followed one another, often “in the name of ethics”, to address previous criticisms and/or to legitimate certain scientific and technological research programs. The focus is on how a brief history of the institutionalization of these approaches can provide insights into present challenges to the ethics of AI related to methodological issues, mobilization of expertise and public participation. (shrink)

This collection of quotes demonstrates the elegant simplicity of Ai Weiwei's thoughts on key aspects of his art, politics, and life. A master at communicating powerful ideas in astonishingly few words, Ai Weiwei is known for his innovative use of social media to disseminate his views. The book is organized into six categories: freedom of expression; art and activism; government, power, and moral choices; the digital world; history, the historical moment, and the future; and personal reflections. Together, these quotes (...) span some of the most revealing moments of Ai Weiwei's eventful career-from his risky investigation into student deaths in the 2008 Sichuan earthquake to his arbitrary arrest in 2011-providing a window into the mind of one of the world's most electrifying and courageous contemporary artists. Ai Weiwei is one of China's most influential and inspiring figures. Artist, architect, curator, and activist, he has been an outspoken critic of the Chinese government's stance on human rights and democracy. (shrink)

This is a proposal for the re-activation of the essentially stillborn automatic car project for which the cart was originally obtained, and presents a process through which this activation could be accomplished painlessly. The project would be financed from the lab's operating grant, and would interact strongly with, while being independent of, any Mars rover research initiated by Lynn Quam. Since I seem to be the only one, apart from John McCarthy, with an active interest in this aspect of things, (...) the following is written entirely from my point of view. (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.

Dans les débats classiques des xvie et xviie siècles, la représentation est considérée avant tout comme une question rhétorique et psychologique, mais à la fin du xviie siècle, elle devient une question épistémologique. Cet ouvrage explore le contexte de cette transformation et ses sources.

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis (...) to show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to _collective_ and _individual use_. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of ‘speeding up—to keep up’ with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered. (shrink)

Confucianism regarded mind-heart's nature with importance more than any other schools at all the time. Confucius was the first one to bring up the concept of mind-heart's nature in the history of chinese philosophy. Mencius was the first person to demonstrate reality of human nature's nature systematically and scientifically. Mencius was a protector to block heterodoxy after succeeding Confucius's the doctrine of mind-heart's nature. The mind-heart's nature provided by Mencius are 1) what distinguishes human beings from animals. 2) a (...) moral motivation of human beings. 3) comprised of benevolence(仁), righteousness(義), propriety(禮) and wisdom(智). T'oegye presented a The four & seven debate based Li-K with Gobong metaphysically. The four & seven debate was to present a moral motivation of human beings in their relation to metaphysical composition(Li-Ki). Li and Ki. human nature and particular with respect to metaphysical composition(Li-Ki). T'oegye introduced these of 'The four beginnings are the issuance of LI, and protected the human mind-heart's nature differed with other beings after succeeding Confucius-Mencius's the doctrine of mind-heart's nature. Such viewpoints about theory of mind-heart's nature plays an important role in the Age of AI. (shrink)

In the 1960s, without realizing it, AI researchers were hard at work finding the features, rules, and representations needed for turning rationalist philosophy into a research program, and by so doing AI researchers condemned their enterprise to failure. About the same time, a logician, Yehoshua Bar-Hillel, pointed out that AI optimism was based on what he called the “first step fallacy”. First step thinking has the idea of a successful last step built in. Limited early success, however, is not a (...) valid basis for predicting the ultimate success of one’s project. Climbing a hill should not give one any assurance that if he keeps going he will reach the sky. Perhaps one may have overlooked some serious problem lying ahead. There is, in fact, no reason to think that we are making progress towards AI or, indeed, that AI is even possible, in which case claiming incremental progress towards it would make no sense. In current excited waiting for the singularity, religion and technology converge. Hard headed materialists desperately yearn for a world where our bodies no longer have to grow old and die. They will be transformed into information, like Google digitizes old books, and we will achieve the promise of eternal life. As an existential philosopher, however, I suggest that we may have to overcome the desperate desire to digitalize our bodies so as to achieve immortality, and, instead, face up to and maybe even enjoy our embodied finitude. (Paper from PT-AI 2011 conference. Volume ed. Vincent C. Müller). (shrink)

Philosophy already has a long history of coming to terms with artificial intelligence. But if the future of the concept is indeed inseparable from artificial languages and ubiquitous computing...

Contribution to the History of the Wheeled Vehicle in India. By Jean Deloche. Collection Indologie, vol. 126. Pondicherry: institut Français de Pondichéry and École Française d’Extrême-orient, 2014. Pp. xiii + 145; 31 figures; 36 plates.

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 discussed in previous publications by this 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)

Greek, Indian and Arabic Logic marks the initial appearance of the multi-volume Handbook of the History of Logic. Additional volumes will be published when ready, rather than in strict chronological order. Soon to appear are The Rise of Modern Logic: From Leibniz to Frege. Also in preparation are Logic From Russell to Gödel, The Emergence of Classical Logic, Logic and the Modalities in the Twentieth Century, and The Many-Valued and Non-Monotonic Turn in Logic. Further volumes will follow, including Mediaeval (...) and Renaissance Logic and Logic: A History of its Central. In designing the Handbook of the History of Logic, the Editors have taken the view that the history of logic holds more than an antiquarian interest, and that a knowledge of logic's rich and sophisticated development is, in various respects, relevant to the research programmes of the present day. Ancient logic is no exception. The present volume attests to the distant origins of some of modern logic's most important features, such as can be found in the claim by the authors of the chapter on Aristotle's early logic that, from its infancy, the theory of the syllogism is an example of an intuitionistic, non-monotonic, relevantly paraconsistent logic. Similarly, in addition to its comparative earliness, what is striking about the best of the Megarian and Stoic traditions is their sophistication and originality. Logic is an indispensably important pivot of the Western intellectual tradition. But, as the chapters on Indian and Arabic logic make clear, logic's parentage extends more widely than any direct line from the Greek city states. It is hardly surprising, therefore, that for centuries logic has been an unfetteredly international enterprise, whose research programmes reach to every corner of the learned world. Like its companion volumes, Greek, Indian and Arabic Logic is the result of a design that gives to its distinguished authors as much space as would be needed to produce highly authoritative chapters, rich in detail and interpretative reach. The aim of the Editors is to have placed before the relevant intellectual communities a research tool of indispensable value. Together with the other volumes, Greek, Indian and Arabic Logic, will be essential reading for everyone with a curiosity about logic's long development, especially researchers, graduate and senior undergraduate students in logic in all its forms, argumentation theory, AI and computer science, cognitive psychology and neuroscience, linguistics, forensics, philosophy and the history of philosophy, and the history of ideas. (shrink)

We are currently witnessing the emergence of a ‘third culture’, driven by unprecedented developments that are changing the playing field. These include advances in AI, big data analysis and robotics. The traditional ‘two cultures’ view (S. P. Snow) distinguishes between the sciences and the humanities. The wisdoms these two cultures offer are separated from each other, with little to no interaction or mutual comprehension. However, over the past two decades, and for the first time in human history, a new, (...) third culture has appeared. This new culture, rooted in new technologies, not only pursues its own form of rationality but also supports advances in the original two cultures, deepening and expanding our individual and collective consciousness so that we can see more and do better. It will eventually give rise to new forms of consciousness based not on biochemical signals, but on copper wires and lithium chips. These new machine intelligences will change the world and force us to realise: we are no longer alone. The human species’ position in the twenty-first century will be fundamentally redefined: not as a conductor leading the orchestra, but a single string player within it. (shrink)

Considering the technological development today, we are facing an emerging crisis. We are in the midst of a scientific revolution, which promises to radically change not only the way we live and work—but beyond that challenge the stability of the very foundations of our civilization and the international political order. All our attention and effort is thus focused on cushioning its impacts on life and society. Looking back in history, it would be pertinent to ask whether this process is (...) a “quasi” natural event destined to continue its path which forebodes severe ethical, social and political repercussions, or is it the outcome of a particular socio-cultural value system? What then are the different value systems and mind-sets? How do these impact on our perception of the world, our cognition systems and our self-perception? At the core of this revolution are the recent technological developments in information and data processing and the creation of AI and the role of algorithms. Are algorithms quasi “independent” artificial languages for assessing situations, solving problems and taking decisions on fundamental social issues? Or do they rest on the fundament of natural language? What ethical and moral code do they follow? What drivers underlie this technological process? Are these culture specific or universal? Could a change of “cultural perspective” provide us with new insights to steer the process and change its course? (shrink)

This treatise covers the history, now more than 170 years long, of researches and debates concerning the biblical city of Ai. This archetypical chapter in the evolution of biblical archaeology and historiography was never presented in full. I use the historical data as a case study to explore a number of epistemological issues, such as the creation and revision of scientific knowledge, the formation and change of consensus, the Kuhnian model of paradigm shift, several models of discrimination between hypotheses (...) about the past, the interplay between scientists' values and their epistemic beliefs, and the truth-bearing of historiographic reconstruction. I show, in particular, that when scientists share common epistemic values they can modify their beliefs even when such changes go against deeply entrenched biases and preconceptions. Considerations of coherence usually constrain such modifications, and when sufficient data is available the result can be a profound change of beliefs. Several episodes of the "Ai debates" demonstrate, however, that similar change of beliefs will not occur when non-epistemic values take precedence. (shrink)

This paper presents a review and an historical perspective on the architectural metaphor. It identifies common characteristics and peculiarities—as they apply to given historical periods—and analyses the similarities and divergences. The review provides a vocabulary, which will facilitate an appreciation of existing and new metaphors.

One of the most common contemporary approaches for developing an ethics of artificial intelligence (AI) involves elaborating guiding principles. This essay explores the limitations of this approach, using the history of bioethics as a comparative case. The examples of bioethics and recent AI ethics suggest that principles are difficult to implement in everyday practice, fail to direct individual action, and can frequently result in a pure proceduralism. The essay encourages an additional attention to virtue, which forms the dispositions of (...) actors, directs them to valued ends, and encourages right action in particular situation to complement principles. Practices and professions like medicine or warfighting that already have rich traditions of reflection on virtue ethics will be especially fruitful fields for developing an AI ethics of virtue. (shrink)

Developing and implementing artificial intelligence (AI) systems in an ethical manner faces several challenges specific to the kind of technology at hand, including ensuring that decision-making systems making use of machine learning are just, fair, and intelligible, and are aligned with our human values. Given that values vary across cultures, an additional ethical challenge is to ensure that these AI systems are not developed according to some unquestioned but questionable assumption of universal norms but are in fact compatible with the (...) societies in which they operate. This is particularly pertinent for AI research and implementation across Africa, a ground where AI systems are and will be used but also a place with a history of imposition of outside values. In this paper, we thus critically examine one proposal for ensuring that decision-making systems are just, fair, and intelligible—that we adopt a principle of explicability to generate specific recommendations—to assess whether the principle should be adopted in an African research context. We argue that a principle of explicability not only can contribute to responsible and thoughtful development of AI that is sensitive to African interests and values, but can also advance tackling some of the computational challenges in machine learning research. In this way, the motivation for ensuring that a machine learning-based system is just, fair, and intelligible is not only to meet ethical requirements, but also to make effective progress in the field itself. (shrink)

This paper explores the history of ELIZA, a computer programme approximating a Rogerian therapist, developed by Jospeh Weizenbaum at MIT in the 1970s, as an early AI experiment. ELIZA’s reception provoked Weizenbaum to re-appraise the relationship between ‘computer power and human reason’ and to attack the ‘powerful delusional thinking’ about computers and their intelligence that he understood to be widespread in the general public and also amongst experts. The root issue for Weizenbaum was whether human thought could be ‘entirely (...) computable’. This also provoked him to re-consider the nature of machine intelligence and to question the instantiation of its logics in the social world, which would come to operate, he said, as a ‘slow acting poison’. Exploring Weizenbaum’s 20th Century apostasy, in the light of ELIZA, illustrates ways in which contemporary anxieties and debates over machine smartness connect to earlier formations. In particular, this article argues that it is in its designation as a computational therapist that ELIZA is most significant today. ELIZA points towards a form of human–machine relationship now pervasive, a precursor of the ‘machinic therapeutic’ condition we find ourselves in, and thus speaks very directly to questions concerning modulation, autonomy, and the new behaviorism that are currently arising. (shrink)

Fear and concerns regarding AI and robots have existed for a long time, and the emergence of strong artificial intelligence, on par with human intelligence, is likely just a few decades away. The primary purpose of this article is to establish a theoretical framework for navigating the relationship between humans and this advanced form of artificial intelligence. This article first points out that the most fundamental characteristic of life is its continuous process of evolution and iteration. By analyzing the developmental (...) history of intelligence in different species, it can be observed that intelligence also exhibits a similar evolutionary phenomenon. Therefore, from this perspective, intelligence can be defined as a new form of information life. Under this premise, similarities and differences between information life forms and conventional biological life become apparent. The most significant distinction lies in the fact that the survival of biological life is based on non-replicable matter and energy, leading to extensive competition and food chain phenomena within ecosystems. In contrast, the survival of information life relies more on replicable information, fostering tendencies towards peace and communication. Based on this theoretical premise, there is a potential for a harmonious coexistence between humans and AI. This theory also provides guidance for the positive development of human society. (shrink)

According to the standard (recent) history of connectionism (see for example the accounts offered by Hecht-Nielsen (1990: pp. 14-19) and Dreyfus and Dreyfus (1988), or Papert's (1988: pp. 3-4) somewhat whimsical description), in the early days of Classical Computational Theory of Mind (CCTM) based AI research, there was also another allegedly distinct approach, one based upon network models. The work on network models seems to fall broadly within the scope of the term 'connectionist' (see Aizawa 1992), although the term (...) had yet to be coined at the time. These two approaches were "two daughter sciences" according to Papert (1988: p. 3). The fundamental difference between these two 'daughters', lay (according to Dreyfus and Dreyfus (1988: p. 16)) in what they took to be the paradigm of intelligence. Whereas the early connectionists took learning to be fundamental, the traditional school concentrated upon problem solving. (shrink)

The Lisp programming language is often described as the first functional programming language and also as an important early AI language. In the history of functional programming, however, it occupies a rather anomalous position, as the circumstances of its development do not fit well with the widely accepted view that functional languages have been developed through a theoretically-inspired project of deriving practical programming languages from the lambda calculus. This paper examines the origins of Lisp in the early AI programming (...) work of the mid-to-late 1950s, and in particular in the work of Allen Newell, Cliff Shaw and Herbert Simon. Their 1956 program, the Logic Theory Machine, introduced new ideas about data and program structures that were articulated in response to perceived limitations in existing programming technique. Later writers, notably John Backus, have described these features as constituting a “programming language style” distinct from the traditional style that preceded it. The paper examines the origins of the earlier style in practices of manual computation, analyses the key technical differences between it and the style first manifested in the Logic Theory Machine, and concludes that programming practice and experience play a large and underappreciated role in the development of programming styles and languages. (shrink)

Artificial insemination has a considerable cultural significance in addition to its economic and technical impact. This study is the first to examine the history of its application to pigs, and uses evidence provided directly by both the scientists involved in its development, and some of the farmers who were among the first to use it, in addition to archival and published sources, to show how the scientific studies of the 1950s evolved into a widely available commercial product by the (...) 1980s. It describes the initial scientific work and quantifies the extent to which the technique was used at various points in time, showing that by 1990 nearly one half of UK pig herds were using AI for more than 25% of all services. It traces changes in the techniques employed and argues that these were the result of a multi-dimensional process of contemporaneous change. The various dimensions are identified firstly as authorities, meaning the people and organisations controlling the perception, administration, control, and so on, of the technique; secondly the discourses employed by the authorities; and thirdly the media by which the discourses were disseminated. Finally, it is suggested that this approach might be used more widely to examine the construction of other technologies. (shrink)

The paper describes a highly specific Italian action research experience, connected with the trade unions, going through different phases from the 1970s to the present day. The journey is not only a journey through time but also through different approaches. It ranges from the initial experience focusing on health and safety problems at the workplace involving the workers as co-designers of new working environments to today’s search conference experience. For each phase there is a full description and comment on the (...) methods utilised by the research group. The main methodological shift described in the paper is the one from discussion groups, based on Bion’s thinking, to the search conferences, based on Emery’s line of thinking. Both are oriented to the subjectivity of the people involved, although in the discussion group experience the research groups considered the subjectivity of the people involved as the subject of the observation. The researchers’ aim of was to acquire a reliable knowledge of what was at stake and to pass it on to the union that organised the research in order to promote actions. Hence, the action-research circuit is based upon different actors and the process is integrated only from the point of view of the union. In the search conference experience the researchers are involved in a co-design process and so the action-research circuit is really integrated from the researchers’ perspective; there are, of course, multiple perspectives in this case and this opens up epistemological problems that are not discussed in the paper. (shrink)

Some enlightenment regarding the project to mechanise reason. The assembly line of machine learning: data, algorithm, model. The training dataset: the social origins of machine intelligence. The history of AI as the automation of perception. The learning algorithm: compressing the world into a statistical model. All models are wrong, but some are useful. World to vector: the society of classification and prediction bots. Faults of a statistical instrument: the undetection of the new. Adversarial intelligence vs. statistical intelligence: labour in (...) the age of AI. (shrink)

This paper reviews the history of AI & Law research from the perspective of argument schemes. It starts with the observation that logic, although very well applicable to legal reasoning when there is uncertainty, vagueness and disagreement, is too abstract to give a fully satisfactory classification of legal argument types. It therefore needs to be supplemented with an argument-scheme approach, which classifies arguments not according to their logical form but according to their content, in particular, according to the roles (...) that the various elements of an argument can play. This approach is then applied to legal reasoning, to identify some of the main legal argument schemes. It is also argued that much AI & Law research in fact employs the argument-scheme approach, although it usually is not presented as such. Finally, it is argued that the argument-scheme approach and the way it has been employed in AI & Law respects some of the main lessons to be learnt from Toulmin’s The Uses of Argument. (shrink)

Faith has been shown to serve a protective role in the mental health of African Americans and European Americans. However, little research has examined whether any association exists in Asian Americans. Using the National Latino and Asian American Study dataset, we examined the effect of religious attendance on the mental health of Asian Americans in the United States. The present study focused on Chinese Americans because they are the largest Asian American group. The results revealed that almost 80% of the (...) respondents were foreign-born and that their English proficiency had a positive association with their self-rated mental health. Being male correlated significantly to higher levels of mental health self-rating. After controlling for known predictive variables, such as demographics, cultural and immigration variables, more frequent religious attendance significantly predicted higher self-rating of mental health. These findings suggest that faith may have a unique protective role in Chinese Americans’ mental health. (shrink)

In this paper, we analyze two key claims offered by recruitment AI companies in relation to the development and deployment of AI-powered HR tools: (1) recruitment AI can objectively assess candidates by removing gender and race from their systems, and (2) this removal of gender and race will make recruitment fairer, help customers attain their DEI goals, and lay the foundations for a truly meritocratic culture to thrive within an organization. We argue that these claims are misleading for four reasons: (...) First, attempts to “strip” gender and race from AI systems often misunderstand what gender and race are, casting them as isolatable attributes rather than broader systems of power. Second, the attempted outsourcing of “diversity work” to AI-powered hiring tools may unintentionally entrench cultures of inequality and discrimination by failing to address the systemic problems within organizations. Third, AI hiring tools’ supposedly neutral assessment of candidates’ traits belie the power relationship between the observer and the observed. Specifically, the racialized history of character analysis and its associated processes of classification and categorization play into longer histories of taxonomical sorting and reflect the current demands and desires of the job market, even when not explicitly conducted along the lines of gender and race. Fourth, recruitment AI tools help produce the “ideal candidate” that they supposedly identify through by constructing associations between words and people’s bodies. From these four conclusions outlined above, we offer three key recommendations to AI HR firms, their customers, and policy makers going forward. (shrink)

AI for social good is a thriving research topic and a frequently declared goal of AI strategies and regulation. This article investigates the requirements necessary in order for AI to actually serve a public interest, and hence be socially good. The authors propose shifting the focus of the discourse towards democratic governance processes when developing and deploying AI systems. The article draws from the rich history of public interest theory in political philosophy and law, and develops a framework for (...) ‘public interest AI’. The framework consists of (1) public justification for the AI system, (2) an emphasis on equality, (3) deliberation/ co-design process, (4) technical safeguards, and (5) openness to validation. This framework is then applied to two case studies, namely SyRI, the Dutch welfare fraud detection project, and UNICEF’s Project Connect, that maps schools worldwide. Through the analysis of these cases, the authors conclude that public interest is a helpful and practical guide for the development and governance of AI for the people. (shrink)

The expression ‘‘artificial intelligence’’ (AI) was introduced by John McCarthy, and the official birth of AI is unanimously considered to be the 1956 Dartmouth Conference. Thus, AI turned fifty in 2006. How did AI begin? Several differently motivated analyses have been proposed as to its origins. In this paper a brief look at those that might be considered steps towards Dartmouth is attempted, with the aim of showing how a number of research topics and controversies that marked the short (...) class='Hi'>history of AI were touched on, or fairly well stated, during the year immediately preceding Dartmouth. The framework within which those steps were taken was the development of digital computers. Earlier computer applications in areas such as complex decision making and management, at that time dealt with by operations research techniques, were important in this story. The time was ripe for AI’s intriguingly tumultuous development, marked as it has been by hopes and defeats, successes and difficulties. (shrink)

Concern over the nature of AI is, for the tastes many AI scientists, probably overdone. In this they are like all other scientists. Working scientists worry about experiments, data, and theories, not foundational issues such as what their work is really about or whether their discipline is methodologically healthy. However, most scientists aren’t in a field that is approximately fifty years old. Even relatively new fields such as nonlinear dynamics or branches of biochemistry are in fact advances in older established (...) sciences and are therefore much more settled. Of course, by stretching things, AI can be said to have a history reaching back t o Charles Babbage, and possibly back beyond that to Leibnitz. However, all of that is best viewed as prelude. AI’s history is punctuated with the invention of the computer (and, if one wants t o stretch our history back to the 1930s, the development of the notion of computation by Turing, Church, and others). Hence, AI really began (or began in earnest) sometime in the late 1940s or early 1950s (some mark the conference a t Dartmouth in the summer of 1957 as the moment of our birth). And since those years we simply have not had time to settle into a routine science attacking reasonably well understood questions (for example, many of the questions some of us regard as supreme are regarded by others as inconsequential or mere excursions). (shrink)

Theories related to cognitive sciences, Human-in-the-loop Cyber-physical systems, data analysis for decision-making, and computational ethics make clear the need to create transdisciplinary learning, research, and application strategies to bring coherence to the paradigm of a truly human-oriented technology. Autonomous objects assume more responsibilities for individual and collective phenomena, they have gradually filtered into routines and require the incorporation of ethical practice into the professions related to the development, modeling, and design of algorithms. To make this possible, it is pertinent and (...) urgent to bring them closer to the problems and approaches of the humanities. Increasingly transdisciplinary research must be part of the construction of systems that provide developers and scientists with the necessary bases to understand the ethical debate and therefore their commitment to society. This article considers two theories as articulating axes: Blumenberg’s, coming from the field of philosophy, for whom the process of technification and especially the implementation of mathematical models in their algorithmic form leads to an emptying of meaning and therefore makes programmers who implement their functions to be alien to the concerns that gave them origin; Daston’s, belonging to the field of the history of science and according to which the division of labor in the processes of technification of the calculation implies a kind of subordination in which those who implement the inventions of a small group of privileged mathematicians ignore the procedures that put them into operation. Given these two theories, the black box models prevalent in AI development, and the urgency of establishing explanatory frameworks for the development of computational ethics, this article exposes the need to give a voice to the cultural history of consciousness for promoting the discussions around the implementation of mathematical algorithms. The paper takes as a reference the different points of view that have emerged around the study of technological ethics, its applicability, management, and design. It criticizes the current state of studies from a humanistic perspective and explains how the historical perspective allows promoting the training of software engineers, developers and creators so that they assume intuitions and moral values in the development of their work. Specifically, it aims to expose how cultural history, applied to the study of consciousness and its phenomena, makes those involved in this technological revolution aware of the effect that they, through their algorithms, have on society in general and on human beings in particular. (shrink)

Recent narratives and debates surrounding long-term AI concerns—the prospect of artificial general intelligence in particular—are fraught with hidden assumptions, priorities, and values. This paper employs a humanistic, narrative-centered approach to analyze the works of two vocal, and opposing, thinkers in the field—Luciano Floridi and Nick Bostrom—to ask how the representational, descriptive differences in their works reveal the high stakes of narrative choices for how we form ideas about humanity, urgency, risk, harm, and possibility in relation to AI. This paper closely (...) reads Floridi and Bostrom using different representational models and historical narratives from works in the environmental humanities, literary theory, bioethics, and the history of technology to uncover the imaginative terrain of recent long-term AI discourse and reveal the complexity and limitations of the messaging underlying the works of different authors. (shrink)

Critics of the computational connectionism of the last decade suggest that it shares undesirable features with earlier empiricist or associationist approaches, and with behaviourist theories of learning. To assess the accuracy of this charge the works of earlier writers are examined for the presence of such features, and brief accounts of those found are given for Herbert Spencer, William James and the learning theorists Thorndike, Pavlov and Hull. The idea that cognition depends on associative connections among large networks of neurons (...) is indeed one with precedents, although the implications of this for psychological issues have been interpreted variously — not all versions of connectionism are alike. (shrink)

This paper critically investigates the explainable artificial intelligence (XAI) project. I analyze the word “explain” in XAI and the theory of explanation and identify the discrepancy between the meaning of the explanation claimed to be necessary and that which is actually presented. After summarizing the history of AI related to explainability, I argue that American philosophy in the 1900s operated in the background of said history. I then extract the meaning of explanation in view of XAI, to elucidate (...) the relationship among AI, logic, and the theory of explanation. In so doing, I aim to reveal DARPA’s surreptitious definitional retreat in terms of its contents and formal fallacy of sophisma figurae dictionis, drawing from Kant’s paralogism. I conclude that this intentional fallacy preexists the XAI project and that presumptuous use of reason, which Kant criticizes, is underlying. (shrink)