Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said to (...) embody certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. (...) We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. (shrink)

Recent work in artificial intelligence has increasingly turned to argumentation as a rich, interdisciplinary area of research that can provide new methods related to evidence and reasoning in the area of law. Douglas Walton provides an introduction to basic concepts, tools and methods in argumentation theory and artificial intelligence as applied to the analysis and evaluation of witness testimony. He shows how witness testimony is by its nature inherently fallible and sometimes subject to disastrous failures. At the same (...) time such testimony can provide evidence that is not only necessary but inherently reasonable for logically guiding legal experts to accept or reject a claim. Walton shows how to overcome the traditional disdain for witness testimony as a type of evidence shown by logical positivists, and the views of trial sceptics who doubt that trial rules deal with witness testimony in a way that yields a rational decision-making process. (shrink)

Recent decades have witnessed tremendous progress in artificial intelligence and in the development of autonomous systems that rely on artificial intelligence. Critics, however, have pointed to the difficulty of allocating responsibility for the actions of an autonomous system, especially when the autonomous system causes harm or damage. The highly autonomous behavior of such systems, for which neither the programmer, the manufacturer, nor the operator seems to be responsible, has been suspected to generate responsibility gaps. This has been the (...) cause of much concern. In this article, I propose a more optimistic view on artificial intelligence, raising two challenges for responsibility gap pessimists. First, proponents of responsibility gaps must say more about when responsibility gaps occur. Once we accept a difficult-to-reject plausibility constraint on the emergence of such gaps, it becomes apparent that the situations in which responsibility gaps occur are unclear. Second, assuming that responsibility gaps occur, more must be said about why we should be concerned about such gaps in the first place. I proceed by defusing what I take to be the two most important concerns about responsibility gaps, one relating to the consequences of responsibility gaps and the other relating to violations of jus in bello. (shrink)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, (...) process, and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (shrink)

Under what circumstances if ever ought we to grant that Artificial Intelligences (AI) are persons? The question of whether AI could have the high degree of moral status that is attributed to human persons has received little attention. What little work there is employs western conceptions of personhood, while non-western approaches are neglected. In this article, I discuss African conceptions of personhood and their implications for the possibility of AI persons. I focus on an African account of personhood that is (...) prima facie inimical to the idea that AI could ever be ‘persons’ in the sense typically attributed to humans. I argue that despite its apparent anthropocentrism, this African account could admit AI as persons. (shrink)

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights (...) and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (shrink)

_Virtue as Social Intelligence: An Empirically Grounded Theory_ takes on the claims of philosophical situationism, the ethical theory that is skeptical about the possibility of human virtue. Influenced by social psychological studies, philosophical situationists argue that human personality is too fluid and fragmented to support a stable set of virtues. They claim that virtue cannot be grounded in empirical psychology. This book argues otherwise. Drawing on the work of psychologists Walter Mischel and Yuichi Shoda, Nancy E. Snow argues that (...) the social psychological experiments that philosophical situationists rely on look at the wrong kinds of situations to test for behavioral consistency. Rather than looking at situations that are objectively similar, researchers need to compare situations that have similar meanings _for the subject_. When this is done, subjects exhibit behavioral consistencies that warrant the attribution of enduring traits, and virtues are a subset of these traits. Virtue can therefore be empirically grounded and virtue ethics has nothing to fear from philosophical situationism. (shrink)

This interdisciplinary collection of classical and contemporary readings provides a clear and comprehensive guide to the many hotly-debated philosophical issues at the heart of artificial intelligence.

The rapid spread and development of artificial intelligence technologies has raised important questions that have an impact on laws and regulations related to intellectual property. In light of this, the research aims to explore the impact of artificial intelligence on intellectual property laws and regulations, and to examine the legal implications of the innovations generated by artificial intelligence on authorship, invention, ownership, infringement, and enforcement of intellectual property laws. In light of the great concerns about its impact (...) on intellectual property laws and regulations and the uncertainty and ambiguity in the application of intellectual property laws, the researcher considered it a problem of the study as it leads to potential risks and challenges for creators, inventors, and intellectual property rights holders. The research followed the comparative approach to provide a view of the different approaches regarding this topic, and to help shed light on the main difficulties faced in applying the law in such an evolving context. The study reached many conclusions, but the most important of them is that artificial intelligence threatens office jobs due to its ability to generate high-quality content quickly and at a low cost, and intellectual property laws will continue to be breached, which necessitates the need for the law to adapt to establish rules of conduct and limits of human work, and recommends engaging in an international dialogue to unify laws and manage disputes related to intellectual property across borders. (shrink)

Fueled by ever-growing amounts of (digital) data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, (public) health, and (...) judicial contexts. Data from a scenario-based survey experiment with a national sample (N = 958) show that people are by and large concerned about risks and have mixed opinions about fairness and usefulness of automated decision-making at a societal level, with general attitudes influenced by individual characteristics. Interestingly, decisions taken automatically by AI were often evaluated on par or even better than human experts for specific decisions. Theoretical and societal implications about these findings are discussed. (shrink)

AI, especially in the case of Deepfakes, has the capacity to undermine our confidence in the original, genuine, authentic nature of what we see and hear. And yet digital technologies, in the form of databases and other detection tools also make it easier to spot forgeries and to establish the authenticity of a work. Using the notion of ectypes, this paper discusses current conceptions of authenticity and reproduction and examines how, in the future, these might be adapted for use in (...) the digital sphere. (shrink)

Michael Hand's interesting analysis of the concept of intelligence crucially depends upon three assumptions: firstly, that there is an ordinary use of the term which, when applied to an individual is perfectly general and not context dependent. Secondly, that this use is best cashed in terms of aptitude. Thirdly, that the aptitude in question is to be explained in terms of theorizing. I shall argue in what follows that the first assumption may be true, but, if it is true, (...) this presents a problem for Hand's analysis and not a path to a solution. That the second assumption is false but, even if it were true, it would sit badly with assumption one. And, finally, that the third assumption runs into too many difficulties to be acceptable. (shrink)

What occurs in the mind of an expert who is performing at their very best? In this paper, I survey the history of debate concerning this question. I suggest that expertise is neither solely a mastery of the automatic nor solely a mastery of intelligence in skilled action control. Experts are also capable of performing automatic actions intelligently. Following this, I argue that unconscious-thought theory (UTT) is a powerful tool in coming to understand the role of executive, intelligent action (...) control in the fluidly automatic performance of expertise. Relying on a body of empirical evidence concerning the cognitive structures and perceptual strategies employed by experts, I show that the realm of skilled action is an ideal environment within which the powers of unconscious cognitive processing can have positive effects on action. I conclude that experts rely upon unconscious thinking in the production of intelligently automatic skilled actions. (shrink)

Acute stress has been linked with prosocial behavior, yet it is entirely unexplored how different types of stressors may affect individuals’ willingness to help: This is particularly relevant while people is experiencing multiple sources of stress due to the COVID-19 pandemic. Here we explore whether different types of stress influence peoples’ giving behavior and the moderating role of emotional intelligence. Undergraduate students were exposed to experimentally induced social, cognitive, or emotional stress and were asked to self-report on their willingness (...) to help and donate to a charity raising funds for COVID-19 and flu patients. Results showed that when compared to a control condition, after being exposed to a social stress, participants were more willing to help a person in need. Our results also provide evidence that, after experiencing a social stress, participants with high trait EI were more willing to help, and, as a result, donated more. Findings indicate that moderate levels of distress are associated with increased donations. Interestingly, when stress is not too threatening, high EI can regulate it and promote prosocial behaviors. (shrink)

This empirical study explores the effect of cultural intelligence (CQ) on migrant workers’ innovative behavior, as well as the mediating role of knowledge sharing on the CQ-innovative behavior relationship. Besides, it also examines the extent to which the mediating process is moderated by climate for inclusion. Using survey data collected from Chinese migrant workers and their supervisors working in South Korea (n = 386), migrant workers’ CQ is found to positively impact their innovative behavior through enhanced knowledge sharing. However, (...) it is observed that this indirect relationship is significant, only for migrant workers in a strong climate for inclusion. Thus, these findings reveal the underlying mediation and moderation mechanism and consequently unveil the important role of migrant workers’ CQ in shaping their behavior. This study provides insightful and practical implications to a multicultural organization, where culturally diverse migrant workers work together. (shrink)

Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages (...) 317-342 - - - The path to more general artificial intelligence - Ted Goertzel - pages 343-354 - - - Limitations and risks of machine ethics - Miles Brundage - pages 355-372 - - - Utility function security in artificially intelligent agents - Roman V. Yampolskiy - pages 373-389 - - - GOLEM: towards an AGI meta-architecture enabling both goal preservation and radical self-improvement - Ben Goertzel - pages 391-403 - - - Universal empathy and ethical bias for artificial general intelligence - Alexey Potapov & Sergey Rodionov - pages 405-416 - - - Bounding the impact of AGI - András Kornai - pages 417-438 - - - Ethics of brain emulations - Anders Sandberg - pages 439-457. (shrink)

This paper explores aspects of GPT-3 that have been discussed as harbingers of artificial general intelligence and, in particular, linguistic intelligence. After introducing key features of GPT-3 and assessing its performance in the light of the conversational standards set by Alan Turing in his seminal paper from 1950, the paper elucidates the difference between clever automation and genuine linguistic intelligence. A central theme of this discussion on genuine conversational intelligence is that members of a linguistic community (...) never merely respond “algorithmically” to queries through a selective kind of pattern recognition, because they must also jointly attend and act with other speakers in order to count as genuinely intelligent and trustworthy. This presents a challenge for systems like GPT-3, because representing the world in a way that makes conversational common ground salient is an essentially collective task that we can only achieve jointly with other speakers. Thus, the main difficulty for any artificially intelligent model of conversation is to account for the communicational intentions and motivations of a speaker through joint attention. These joint motivations and intentions seem to be completely absent from the standard way in which systems like GPT-3 and other artificial intelligent systems work. This is not merely a theoretical issue. Since GPT-3 and future iterations of similar systems will likely be available for commercial use through application programming interfaces, caution is needed regarding the risks created by these systems, which pass for “intelligent” but have no genuine communicational intentions, and can thereby produce fake and unreliable linguistic exchanges. (shrink)

BackgroundAdvances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementation of AI could mean such corporations, clinics and public bodies will have a greater than typical role in obtaining, utilizing and protecting patient health information. This raises privacy issues relating to implementation and data security. Main bodyThe first set of concerns includes access, use and (...) control of patient data in private hands. Some recent public–private partnerships for implementing AI have resulted in poor protection of privacy. As such, there have been calls for greater systemic oversight of big data health research. Appropriate safeguards must be in place to maintain privacy and patient agency. Private custodians of data can be impacted by competing goals and should be structurally encouraged to ensure data protection and to deter alternative use thereof. Another set of concerns relates to the external risk of privacy breaches through AI-driven methods. The ability to deidentify or anonymize patient health data may be compromised or even nullified in light of new algorithms that have successfully reidentified such data. This could increase the risk to patient data under private custodianship.ConclusionsWe are currently in a familiar situation in which regulation and oversight risk falling behind the technologies they govern. Regulation should emphasize patient agency and consent, and should encourage increasingly sophisticated methods of data anonymization and protection. (shrink)

Feasting on a plethora of social media platforms, news aggregators, and online marketplaces, recommender systems (RSs) are spreading pervasively throughout our daily online activities. Over the years, a host of ethical issues have been associated with the diffusion of RSs and the tracking and monitoring of users’ data. Here, we focus on the impact RSs may have on personal autonomy as the most elusive among the often-cited sources of grievance and public outcry. On the grounds of a philosophically nuanced notion (...) of autonomy, we illustrate three specific reasons why RSs may limit or compromise it: the threat of manipulation and deception associated with RSs; the RSs’ power to reshape users’ personal identity; the impact of RSs on knowledge and critical thinking. In our view, however, notwithstanding these legitimate concerns, RSs may effectively help users to navigate an otherwise overwhelming landscape. Our perspective, therefore, is not to be intended as a bulwark to protect the _status quo_ but as an invitation to carefully weigh these aspects in the design of ethically oriented RSs. (shrink)

Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. (...) To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being. (shrink)

Research on the antecedents of consumers’ ethical beliefs has mainly examined cognitive variables and has neglected the relationships among affective variables and consumer ethics. However, research in moral psychology indicates that moral emotions have a significant role in ethical decision-making. Thus, the ability to experience, perceive and regulate emotions should influence consumers’ ethical decision-making. These abilities, which are components of emotional intelligence, are examined as antecedents to consumers’ ethical beliefs in this study. Five hundred Australian consumers participated in this (...) study by completing an online questionnaire that included measures of emotional intelligence, consumers’ ethical beliefs and personal moral philosophies. Results demonstrate that the ability to appraise and express emotions in oneself is directly negatively related to beliefs regarding actively benefiting from illegal actions as a consumer, passively benefiting at the expense of the seller and actively benefiting from questionable but legal actions as a consumer. The ability to appraise and express emotions in oneself is directly positively related to beliefs regarding ‘doing-good’ actions. The ability to appraise and recognise emotions in others is also directly positively related to beliefs regarding ‘doing-good’ actions as well as pro-environmental buying actions. The effects of the different components of emotional intelligence on consumers’ ethical beliefs are mediated by personal moral philosophies. This study demonstrates the relationship between emotional intelligence and consumer ethics and highlights the interplay of affect and cognition in consumers’ ethical decision-making. (shrink)

We discuss, first, TUring's role in the development of the computer; second, the early history of Artificial Intelligence (to 1956); and third, TUring's fa- mous imitation game, now universally known as the TUring test, which he proposed in cameo form in 1948 and then more fully in 1950 and 1952. Various objections have been raised to Turing's test: we describe some of the most prominent and explain why, in our view, they fail.

AI and people do not compete on a level-playing field. Self-driving vehicles may be safer than human drivers, but laws often penalize such technology. People may provide superior customer service, but businesses are automating to reduce their taxes. AI may innovate more effectively, but an antiquated legal framework constrains inventive AI. In The Reasonable Robot, Ryan Abbott argues that the law should not discriminate between AI and human behavior and proposes a new legal principle that will ultimately improve human well-being. (...) This work should be read by anyone interested in the rapidly evolving relationship between AI and the law. (shrink)

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John (...) Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

In recent years there has been a substantial amount of research on emotional intelligence (EI) across a wide range of disciplines. Also, this term has been receiving increasing attention in the popular business press. This article extends previous research by seeking to determine whether there is a relationship between emotional intelligence and ethical judgment among practicing managers with respect to questions of ethical nature that can arise in their professional activity. It analyzes the results of a survey of (...) 324 managers enrolled in executive MBA programs from five universities in the southeastern and northeastern United States. This study is based on a model presented by Forsyth showing two dimensions that play an important role in ethical evaluation and behavior. Respondents were classified into one of four groups according to their idealism and relativism levels—situationists, subjectivists, absolutists, and exceptionists. The four ideological group’s scores were compared. The results indicate significant differences between the situationists and absolutists on the one hand, and subjectivists and exceptionists on the other. The former’s emotional intelligence scores were significantly higher thus demonstrating a strong relationship between emotional intelligence and ethical ideology. The results raise important implications for practitioners and educators. (shrink)

This paper will analyze how and to what extent terrorists and violent extremistshave interacted with generative artificial intelligence so far and identify potentialways in which they could misuse generative AI in the future. It is therefore necessaryto question assumptions that terrorist and violent extremist actors will quickly adoptgenerative AI solely based on an assessment of the capabilities it may offer. Althoughresearch has shown that technological capability and availability are key drivers of terroristinnovation, terrorist and violent extremist actors also assess (...) any new technologyon its compatibility (with both their modus operandi and ideology), relative complexity,cost, and the context in which they are operating. Understanding these factors, both inisolation and in relation to one another, will be a key aspect in monitoring the extent towhich terrorists and violent extremists adopt generative AI tools. In doing so, the paperwill seek to identify a likely trajectory for the abuse of this technology by terrorist actorsas well as conclude with some initial recommendations for policymakers. (shrink)

The ML community recognizes the importance of anticipating and mitigating the potential negative impacts of benchmark research. In this position paper, we argue that more attention needs to be paid to areas of ethical risk that lie at the technical and scientific core of ML benchmarks. We identify overlooked structural similarities between human IQ and ML benchmarks. Human intelligence and ML benchmarks share similarities in setting standards for describing, evaluating and comparing performance on tasks relevant to intelligence. This (...) enables us to unlock lessons from feminist philosophy of science scholarship that need to be considered by the ML benchmark community. Finally, we outline practical recommendations for benchmark research ethics and ethics review. (shrink)

Use of argumentation methods applied to legal reasoning is a relatively new field of study. The book provides a survey of the leading problems, and outlines how future research using argumentation-based methods show great promise of leading to useful solutions. The problems studied include not only these of argument evaluation and argument invention, but also analysis of specific kinds of evidence commonly used in law, like witness testimony, circumstantial evidence, forensic evidence and character evidence. New tools for analyzing these kinds (...) of evidence are introduced. (shrink)

Over the past ten years, we have worked in a collaboration between educators and computer scientists at the University of Illinois to imagine futures for education in the context of what is loosely called “artificial intelligence.” Unhappy with the first generation of digital learning environments, our agenda has been to design alternatives and research their implementation. Our starting point has been to ask, what is the nature of machine intelligence, and what are its limits and potentials in education? (...) This paper offers some tentative answers, first conceptually, and then practically in an overview of the results of a number of experimental implementations documented in greater detail elsewhere. Our key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence. However, within the limits that we describe in this paper, it offers the potential to transform education in ways that—counterintuitively perhaps—make education more human, not less. (shrink)

As artificial intelligence (AI) continues to advance, one key challenge is ensuring that AI aligns with certain values. However, in the current diverse and democratic society, reaching a normative consensus is complex. This paper delves into the methodological aspect of how AI ethicists can effectively determine which values AI should uphold. After reviewing the most influential methodologies, we detail an intuitionist research agenda that offers guidelines for aligning AI applications with a limited set of reliable moral intuitions, each underlying (...) a refined cooperative view of AI. We discuss appropriate epistemic tools for collecting, filtering, and justifying moral intuitions with the aim of reducing cognitive and social biases. The proposed methodology facilitates a large collective participation in AI alignment, while ensuring the reliability of the considered moral judgments. (shrink)

The question 'What is intelligence?' may seem simple to answer, but the study and measurement of human intelligence is one of the most controversial subjects in psychology. For much of its history, the focus has been on differences between people, on what it means for one person to be more intelligent than another, and how such differences might have arisen, obscuring efforts to understand the general nature of intelligence. These are obviously fundamental questions, still widely debated and (...) misunderstood. New definitions of intelligence and new factors affecting intelligence are frequently being described, while psychometric testing is applied in most large industries.IQ and Human Intelligence provides a clear, authoritative overview of the main issues surrounding this fascinating area, including the development of IQ tests, the heritability of intelligence, theories of intelligence, environmental effects on IQ, factor analysis, relationship of cognitive psychology to measuring IQ, and intelligence in the social context. The clear, accessible style and numerous explanatory boxes make this the ideal text for advanced undergraduate and graduate students in psychology. Online Resource CentreThe Online Resource Centre to accompany IQ and Human Intelligence features the following resources:For registered adopters of the text:- Figures from the book, available to downloadFor students:- Hyperlinks to primary literature articles cited in the and 'Further Reading' sections of the book. (shrink)

In this paper, we argue that because of the advent of Artificial Intelligence, the secret ballot is now much less effective at protecting voters from voting related instances of social ostracism and social punishment. If one has access to vast amounts of data about specific electors, then it is possible, at least with respect to a significant subset of electors, to infer with high levels of accuracy how they voted in a past election. Since the accuracy levels of Artificial (...) Intelligence are so high, the practical consequences of someone inferring one’s vote are identical to the practical consequences of having one’s vote revealed directly under an open voting regime. Therefore, if one thinks that the secret ballot is at least partly justified because it protects electors against voting related social ostracism and social punishment, one should be morally troubled by how Artificial Intelligence today can be used to infer individual electors’ past voting behaviour. (shrink)

21st Century society could be defined with the term of 4thIndustrial Revolution (4IR), which means various kinds of technology are amalgamated with ICT technology. Since a little bit ago, Genetics, Nanotechnology, Artificial Intelligence and Robotics are changing people’s everyday life. These technologies are accelerating another form of digital convergence to Information Technology and that affects future of human being, especially morality and human nature. The speed and ability of technological development excesses human understanding and it challenges human existences. In (...) the discussion on Artificial Intelligence, Strong AI and Super AI are in the center of the issues for fear that those technologies could be threaten the nature of human being, e.g. humanity or morality which makes the real identity of human nature. With these discussions, corresponding measures of the Ethics Education is closely connected with philosophical perspectives on technological singularity and artificial intelligence. In the Age of technology, the direction of Education should aim at enhancing and supporting morality and forming desirable character for the purpose of recovery and building up the human nature, which controls the direction of the development of the technology. (shrink)

The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This special issue marks the 30th anniversary of the journal by reviewing the progress of the field through thirty commentaries on landmark papers and groups of papers from that journal.

Drawing on the analytic of the “colonial matrix of power” developed by Aníbal Quijano within the Latin American modernity/coloniality research program, this article theorises how a system of coloniality underpins the structuring logic of artificial intelligence (AI) systems. We develop a framework for critiquing the regimes of global labour exploitation and knowledge extraction that are rendered invisible through discourses of the purported universality and objectivity of AI. ​​Through bringing the political economy literature on AI production into conversation with scholarly (...) work on decolonial AI and the modernity/coloniality research program, we advance three main arguments. First, the global economic and political power imbalances in AI production are inextricably linked to the continuities of historical colonialism, constituting the colonial supply chain of AI. Second, this is produced through an international division of digital labour that extracts value from majority world labour for the benefit of Western technology companies. Third, this perpetuates hegemonic knowledge production through Western values and knowledge that marginalises non-Western alternatives within AI’s production and limits the possibilities for decolonising AI. By locating the production of AI systems within the colonial matrix of power, we contribute to critical and decolonial literature on the legacies of colonialism in AI and the hierarchies of power and extraction that shape the development of AI today. (shrink)

This paper considers the question: In what ways can artificial intelligence assist with interdisciplinary research for addressing complex societal problems and advancing the social good? Problems such as environmental protection, public health, and emerging technology governance do not fit neatly within traditional academic disciplines and therefore require an interdisciplinary approach. However, interdisciplinary research poses large cognitive challenges for human researchers that go beyond the substantial challenges of narrow disciplinary research. The challenges include epistemic divides between disciplines, the massive bodies (...) of relevant literature, the peer review of work that integrates an eclectic mix of topics, and the transfer of interdisciplinary research insights from one problem to another. Artificial interdisciplinarity already helps with these challenges via search engines, recommendation engines, and automated content analysis. Future “strong artificial interdisciplinarity” based on human-level artificial general intelligence could excel at interdisciplinary research, but it may take a long time to develop and could pose major safety and ethical issues. Therefore, there is an important role for intermediate-term artificial interdisciplinarity systems that could make major contributions to addressing societal problems without the concerns associated with artificial general intelligence. (shrink)

Since the inception of recorded music there has been a need for standards and reliability across sound formats and listening environments. The role of the audio mastering engineer is prestigious and akin to a craft expert combining scientific knowledge, musical learning, manual precision and skill, and an awareness of cultural fashions and creative labour. With the advent of algorithms, big data and machine learning, loosely termed artificial intelligence in this creative sector, there is now the possibility of automating human (...) audio mastering processes and radically disrupting mastering careers. The emergence of dedicated products and services in artificial intelligence-driven audio mastering poses profound questions for the future of the music industry, already having faced significant challenges due to the digitalization of music over the past decades. The research reports on qualitative and ethnographic inquiry with audio mastering engineers on the automation of their expertise and the potential for artificial intelligence to augment or replace aspects of their workflows. Investigating audio mastering engineers' awareness of artificial intelligence, the research probes the importance of criticality in their labour. The research identifies intuitive performance and critical listening as areas where human ingenuity and communication pose problems for simulation. Affective labour disrupts speculation of algorithmic domination by highlighting the pragmatic strategies available for humans to adapt and augment digital technologies. (shrink)

An important but easily forgotten moment in the history of film-philosophy is Jean Epstein's assertion that cinema, more than merely thinking, has a kind of intelligence. If it is a newfound conception of rationality that is needed for any contemporary ethical relation to the world, as thinkers from Reza Negarestani and Pete Wolfendale to feminist collective Laboria Cuboniks have espoused in their respective neo-rationalist projects, then cinema as a thinking thing must be interrogated in its relation to reason. A (...) somatophilia of purely affective and phenomenological approaches in film theory alongside micropolitical injunctions to undermine common-sense and liberate one's desire in extremity can fall limp in view of such calls for universal thinking around rationality. To understand cinema's specific form of intelligence, this article will explore Luc Besson's Lucy as an instance of how film is able to represent intelligence. Besson's film provides a site where Western cultural anxieties and assumptions around intelligence are manifested. This will allow an explication of contemporary approaches to intelligence in philosophy whilst confronting these discourses with the insidious problematics of gender and race that undergird the film. I argue that Lucy shares many of its ambitions with the emerging vectors of thought associated with the neo-rationalist perspective in its engaging with a rethinking of universal values and the Promethean possibilities of human action. Reading the film through these philosophies will help position the ethical stakes it sets up, but also to distinguish it from a trend of contemporary “posthuman” films that it finds itself in company with. While it is certainly true that posthuman themes, as well as transhumanist fantasies, seem to permeate Besson's film, this article will incorporate another neologism, taken from neo-rationalist thinkers, in order to emphasise moments that can be productive from the standpoint of a philosophical account of intelligence: “rationalist inhumanism.”. (shrink)