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)

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.

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)

本书简要介绍了从明中叶至辛亥革命这一历史时期中国文化史上的主流思潮。全书按历史顺序分别评介了晚明人文主义思潮、明清之际启蒙主义思潮、嘉道之际实学思潮和19世纪末—20世纪初的新民思潮。.

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)

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)

In its forty years of existence, Artificial Intelligence has suffered both from the exaggerated claims of those who saw it as the definitive solution of an ancestral dream — that of constructing an intelligent machine-and from its detractors, who described it as the latest fad worthy of quacks. Yet AI is still alive, well and blossoming, and has left a legacy of tools and applications almost unequalled by any other field-probably because, as the heir of Renaissance thought, it represents a (...) possible bridge between the humanities and the natural sciences, philosophy and neurophysiology, psychology and integrated circuits-including systems that today are taken for granted, such as the computer interface with mouse pointer and windows. This writing describes a few results of AI that have modified the scientific world, as well as the way a layman sees computers: thetechnology of programming languages, such asLISP-witness the unique excellence of academic departments that have contributed to them-thecomputing workstations-of which our modern PC is but a vulgarised descendant-theapplications to the educational field-e.g., the realisation of some ideas of genetic epistemology-and tointerdisciplinary philosophy-such as Hofstadter's associations between the arts and mathematics-and the use ofAI techniques in music and musicology. All this has led to a generalisation of AI towards Negrotti's overallTheory of the Artificial, which encompasses further specialisation such asartificial reality, artificial life, and applications ofneural networks among others. (shrink)

AI-based algorithms are used extensively by public institutions. Thus, for instance, AI algorithms have been used in making decisions concerning punishment providing welfare payments, making decisions concerning parole, and many other tasks which have traditionally been assigned to public officials and/or public entities. We develop a novel argument against the use of AI algorithms, in particular with respect to decisions made by public officials and public entities. We argue that decisions made by AI algorithms cannot count as public decisions, namely (...) decisions that are made in the name of citizens and that this fact should be taken into consideration when utilizing AI to replace public officials. (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)

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)

In Ai Ssu-ch'i is exemplified and substantiated the Soviet influence on the official definition of philosophy in the history of Communist Party of China, i.e., the assertion about and the method for knowledge of the world. Such a philosophical knowledge has as its formal object the most fundamental laws of the universe.In order to acquire such a genuine philosophical knowledge, one needs a desire to change the world and a proletarian point of view. For only by aiming at changing (...) the world is inevitability reflected; only in the proletarian viewpoint are the objective laws reflected. In order to substantiate these assertions, one has to point out that, first, man's thinking is determined by his social relations and, secondly, social relations are determined by practice. Since the proletariat is in the right kind of practice, it is both in the proper locus of social relations and, therefore, it perceives both inevitability and objectivity. Yet, due to man's subjective dynamism, it is possible for other classes to adopt the standpoint of the proletariat. (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)

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)

Against the backdrop of a recent history of ongoing efforts to institutionalize ethics in ways that also target corporate environments, we asked ourselves: How do company representatives at the automatica 2022 trade fair in Munich respond to questions around ethics? To this end, we started an exploratory survey at the automatica 2022 in Munich, asking 22 company representatives at various booths from various industrial sectors the basic question: “Is there somebody in your company working on ethics?” Most representatives were (...) responding positively and tried to connect the term to pre-existing practices, processes, or organizational entities in their respective companies. Mostly, they either located ethics as being relevant to their organization on an institutional level, on a cultural level, on an inter-company level, or on a product level. This exploratory investigation has also shown that the ongoing debates and regulatory efforts about ethics in AI have not yet become a major selling point for company representatives at the trade fair. (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)

Can an Artificial Intelligence make distinctions among major works of politics, philosophy, and fiction without human assistance? In this paper, latent semantic analysis is used to find patterns in a relatively small sample of notable works archived by Project Gutenberg. It is shown that an LSA-equipped AI can distinguish quite sharply between fiction and non-fiction works, and can detect some differences between political philosophy and history, and between conventional fiction and fantasy/science fiction. It is conjectured that this capability is (...) a step in the direction of “M-comprehension” by AIs. (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.

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)

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)

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)

There is a history of thinking that photographs provide a special kind of access to the objects depicted in them, beyond the access that would be provided by a painting or drawing. What is included in the photograph does not depend on the photographer’s beliefs about what is in front of the camera. This feature leads Kendall Walton to argue that photographs literally allow us to see the objects which appear in them. Current generative algorithms produce images in response (...) to users’ text prompts. Depending on the parameters, the output can resemble specific people or things which are named in the prompt. This resemblance does not depend on the user’s beliefs, so generated images are in this sense like photographs. Given this parallel, how should we think about AI-generated images? (shrink)

This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy (...) meets science, and the role of philosophy in the culture in which it is embedded. -/- Organising the arguments into four core topics - 'Is AI possible', 'Architectures of the Mind', 'Mental Semantics and Mental Symbols' and 'Rationality and Creativity' - this book shows the debate that played out between the philosophers on both sides of the question, and, as well, the debate between philosophers and AI scientists and engineers building AI systems. Up-to-date and forward-looking, the book is packed with fresh insights and supporting material, including: -/- - Accessible introductions to each war, explaining the background behind the main arguments against AI - Each chapter details what happened in the AI wars, the legacy of the attacks, and what new controversies are on the horizon. - Extensive bibliography of key readings. (shrink)

This paper presents an overview of the risks and benefits of Social AI, understood as conversational AI systems that cater to human social needs like romance, companionship, or entertainment. Section 1 of the paper provides a brief history of conversational AI systems and introduces conceptual distinctions to help distinguish varieties of Social AI and pathways to their deployment. Section 2 of the paper adds further context via a brief discussion of anthropomorphism and its relevance to assessment of human-chatbot relationships. (...) Section 3 of the paper provides a survey of potential and in some cases demonstrated harms associated with user interactions with Social AI systems. Finally, Section 4 discusses how the benefits and harms of Social AI can best be addressed, with a primary focus on how frameworks from AI ethics can inform their development. (shrink)

This article considers current advances in tattooing that are challenging community-held views of authorship and ownership, and the need to address this tension. The key challenge is from AI-generated artworks being used as tattoo designs, but the authorial role of the tattooist is also challenged by body art projects such as tattoo collection. Legal clarity for tattooing is lacking, and in addressing this, this article advocates for an open, community-based form of shared copyright ownership and authorship for projects as tattoo (...) collecting, drawing on Dusollier’s and Mendis’ work. This article contributes to both copyright and cultural heritage legal scholarship, and to tattooing scholarship and the tattooing community. AI-generated art being tattooed on people has not been explored in the literature to date, and this article fills this gap. Furthermore, this article contributes a pilot study of the tattoo community’s views on AI-generated tattoos, which is currently lacking from the scholarly debate on AI-generated art. This article argues that the debate within the tattoo community about AI-generated art being used in tattoos needs to be addressed within the community through agreed extra-legal norms, which may well depart from how copyright law decides to approach AI-generated art globally. This article also asserts that AI should _not_ be regarded as the “author” of tattoo works in the traditional copyright sense, as only a human tattooist can draw from a number of cultural, textual, audiovisual and visual, cultural folklore, history and mythical references in creating their tattoo designs, as well as drawing on the client’s personal stories. This article explores the following: (i) an understanding of tattooing as an artform; (ii) tattoos in UK copyright law; (iii) an exploration of the authorial role of the tattooist within tattooing; (iv) the authorial role of the tattooist within tattoo collecting; (v) AI-generated tattoos—perspectives from the tattoo community, through a pilot study of YouTube videos and viewer comments about this; and (vi) a consideration of whether copyright legal reform is the solution for the tattooing community. (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)

Everything we do in life involves a connection with information, experience and know-how: together these represent the most valuable of intangible human assets encompassing our history, cultures and wisdom. However, the more easily new technologies gather information, the more we are confronted with our limited capacity to distinguish between what is essential, important or merely ‘nice-to-have’. This article presents the case study of a multilingual Knowledge Management System, the Business enabling e-Platform that gathers and protects tacit knowledge, as the (...) key to developing structured intellectual capital, while acknowledging the urgent need here to integrate Ethics-by-design alongside AI-by-design, in view of the far-reaching consequences involved, for good or ill. It also explains how a beneficial Circular Economy of Knowledge depends on evidence-based answers, and how harmonising taxonomies, terminology and standards promotes global trust as the basis for the unhindered transfer of tacit knowledge between generations in a way that benefits everyone. (shrink)