Transhumanists, like other elites in modernity, place great value on human creativity, and advances in human enhancement and AI form the basis of their propos- als for boosting it. However, there are problems with this perspective, due to the unique ways in which humans have evolved, procreated and socialized. I first describe how creativity is related to past evolution and developmental aspects in children, stressing pretend play and the ambivalent character of creativity. Then, I outline proposals for enhancing creativity, be (...) it in embodied humans on the way to a superior species, in AI- related beings (virtual reality, robotics), or even in any degree of mixture in human- machine interaction. In the final section, I describe intrinsic limits to these proposals, such as the absence of a good understanding of human psychology by the proponents of enhancement; the lack of interest in the subjective side of creativity (for one’s own sake); delayed maturation and the ambivalence of pretend play in childhood; and the contrariness typical of new human generations. As for the enhancement of creativity, it is argued that creativity in its social context may be the victim of its own past success. On the other hand, an asymmetry between virtual beings and children is described— the latter can behave in a nasty way, it is part of their growth and creativity, whereas the former are not supposed to cause any harm to human beings. In sum, despite impressive progress in several scientific and technological interventions in creativity, philosophical questions emerge that place many constraints on transhumanist dreams of endless creativity. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and (...) used by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Exploring an extension to Dick's "intelligence principle" Revisiting Dick’s “Intelligence Principle” in the light of recent technological developments, I present an argument for why one might consider a slight extension to the Principle and I explore some of the implications of the suggested modification.

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or (...) a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy. (shrink)

Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic landscape—such as therapeutic support for people with mental health problems and without access to care. The adoption of CAI poses many risks that need in-depth ethical scrutiny. The objective of this paper is to complement current research on the ethics of AI for mental health by proposing a holistic, ethical, and epistemic analysis of CAI adoption. First, we focus on the question of whether CAI is rather a tool or (...) an agent. This question serves as a framework for the subsequent ethical analysis of CAI focusing on topics of (self-) knowledge, (self-)understanding, and relationships. Second, we propose further conceptual and ethical analysis regarding human-AI interaction and argue that CAI cannot be considered as an equal partner in a conversation as is the case with a human therapist. Instead, CAI’s role in a conversation should be restricted to specific functions. (shrink)

The debate over the ethical repercussions of Artificial Intelligence (AI) cannot disregard the “sum total of ideas that bring into evidence a system of ethical reference that justifies that profound dimension of technology as a central element in the attainment of a ‘finalized’ perfection of man”(Galvan 2001). This implies an analysis of the ancient processes that might help to understand the complexities of contemporary society and the new challenges posed to human development. Being at the core of the dichotomy (...) between the human and the machine, biometrics will be central to the analysis carried out in this paper. Its measurement of physiological characteristics and behavioural patterns has politico-philosophical and legal consequences in terms of recognition and personal identity, as the use of artificial intelligence has shown. In information society, customs and traditions, cultural and communication processes, language and the self-determination of the individual have gradually acquired a stretched dimension that has led to a re-definition of the social structures within which the exchange of knowledge and data takes place, with AI-based technological devices playing a key role in such a scenario. The issue of biometric identity becomes highly complex when combined with the potential of digital services, as it is at this level that it shows the large number of interconnections deriving from social and political choices. The benefits of increased interconnection are limited by the risk of intrusion into the (social, personal or private) human sphere, which might pose a threat to both the physical, biological body, with its related freedoms (habeas corpus), and the digital body, in its multiple forms and media representations (habeas data). (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised (...) learning methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

This unique book clearly explains genetic and neuroimaging research on intelligence and how neuroscience findings may lead to enhancing it.

BackgroundArtificial intelligence has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following (...) question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective?MethodsEight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed.ResultsUpon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries.ConclusionsThe ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere. (shrink)

Emotional intelligence can be defined as the ability to identify, express, understand, manage, and use emotions. EI has been shown to have an important impact on health, relationships, and wor...

The artificial intelligence models with machine learning that exhibit the best predictive accuracy, and therefore, the most powerful ones, are, paradoxically, those with the most opaque black-box architectures. At the same time, the unstoppable computerization of advanced industrial societies demands the use of these machines in a growing number of domains. The conjunction of both phenomena gives rise to a control problem on AI that in this paper we analyze by dividing the issue into two. First, we carry out (...) an epistemological examination of the AI’s opacity in light of the latest techniques to remedy it. And second, we evaluate the rationality of delegating tasks in opaque agents. (shrink)

Trait emotional intelligence concerns our perceptions of our emotional abilities, that is, how good we believe we are in terms of understanding, regulating, and expressing emotions in order to adapt to our environment and maintain well-being. In this article, we present succinct summaries of selected findings from research on the location of trait EI in personality factor space, the biological underpinnings of the construct, indicative applications in the areas of clinical, health, social, educational, organizational, and developmental psychology, and trait (...) EI training. Findings to date suggest that individual differences in trait EI are a consistent predictor of human behavior across the life span. (shrink)

January 6th, 2013 at Kyoto University. Organizer: Hisashi Nakao.

This is the lightly revised text of my commentary/response to David Carr’s keynote address, “Phenomenology of Crisis,” at the 2024 meeting of the Husserl Circle.

Artificial Intelligence technology presents a multitude of ethical concerns, many of which are being actively considered by organizations ranging from small groups in civil society to large corporations and governments. However, it also presents ethical concerns which are not being actively considered. This paper presents a broad overview of twelve topics in ethics in AI, including function, transparency, evil use, good use, bias, unemployment, socio-economic inequality, moral automation and human de-skilling, robot consciousness and rights, dependency, social-psychological effects, and spiritual (...) effects. Each of these topics will be given a brief discussion, though each deserves much deeper consideration. (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)

Abstract: In this article I argue that the best way to understand the information turn is in terms of a fourth revolution in the long process of reassessing humanity's fundamental nature and role in the universe. We are not immobile, at the centre of the universe (Copernicus); we are not unnaturally distinct and different from the rest of the animal world (Darwin); and we are far from being entirely transparent to ourselves (Freud). We are now slowly accepting the idea that (...) we might be informational organisms among many agents (Turing), inforgs not so dramatically different from clever, engineered artefacts, but sharing with them a global environment that is ultimately made of information, the infosphere. (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)

The study relevance lies in understanding strategic objectives' content concerning intelligent technologies’ application. The development and application of artificial intelligence in various branches of human activity carry the potential for global changes in society, which, in methodological terms, increases the relevance of considering these problems. The study of ethical problems of artificial intelligence in the concept of sustainable development of society is connected with the dynamic development of innovative artificial intelligence (AI) technologies, which are considered a process (...) of becoming a new technosubject in the context of neuroscience development. The article emphasizes that the development of artificial intelligence acts as an innovative form of technology development when a new kind of human-machine technosubject is formed. The authors identify social problems of artificial intelligence application as the digitalization of life becomes a global anthropological challenge. Innovations of artificial intelligence are directly related to a number of ethical problems, as they contribute not only to the sustainable development of society but also cause dehumanization of relations between people and society. Based on the analysis of qualitative changes in scientific and technological research, using human-machine devices is becoming inevitable. Humankind must develop ethical guidelines for the application of AI systems. (shrink)

Artificial intelligence receives attention in media as well as in academe and business. In media coverage and reporting, AI is predominantly described in contrasted terms, either as the ultimate solution to all human problems or the ultimate threat to all human existence. In academe, the focus of computer scientists is on developing systems that function, whereas philosophy scholars theorize about the implications of this functionality for human life. In the interface between technology and philosophy there is, however, one imperative (...) aspect of AI yet to be articulated: how do intelligent systems make inferences? We use the overarching concept “Artificial Intelligent Behaviour” which would include both cognition/processing and judgment/behaviour. We argue that due to the complexity and opacity of artificial inference, one needs to initiate systematic empirical studies of artificial intelligent behavior similar to what has previously been done to study human cognition, judgment and decision making. This will provide valid knowledge, outside of what current computer science methods can offer, about the judgments and decisions made by intelligent systems. Moreover, outside academe—in the public as well as the private sector—expertise in epistemology, critical thinking and reasoning are crucial to ensure human oversight of the artificial intelligent judgments and decisions that are made, because only competent human insight into AI-inference processes will ensure accountability. Such insights require systematic studies of AI-behaviour founded on the natural sciences and philosophy, as well as the employment of methodologies from the cognitive and behavioral sciences. (shrink)

Algorithms are used across a wide range of societal sectors such as banking, administration, and healthcare to make predictions that impact on our lives. While the predictions can be incredibly accurate about our present and future behavior, there is an important question about how these algorithms in fact represent human identity. In this paper, we explore this question and argue that machine learning algorithms represent human identity in terms of what we shall call the statistical individual. This statisticalized representation of (...) individuals, we shall argue, differs significantly from our ordinary conception of human identity, which is tightly intertwined with considerations about biological, psychological, and narrative continuity—as witnessed by our most well-established philosophical views on personal identity. Indeed, algorithmic representations of individuals give no special attention to biological, psychological, and narrative continuity and instead rely on predictive properties that significantly exceed and diverge from those that we would ordinarily take to be relevant for questions about how we are. (shrink)

Reference to security and intelligence in education today will undoubtedly elicit concerns over terrorism, radicalisation and, in the UK, counter-terrorism measures such as Channel and Prevent (UK...

Artificial intelligence experts are currently divided into “presentist” and “futurist” factions that call for attention to near-term and long-term AI, respectively. This paper argues that the presentist–futurist dispute is not the best focus of attention. Instead, the paper proposes a reconciliation between the two factions based on a mutual interest in AI. The paper further proposes realignment to two new factions: an “intellectualist” faction that seeks to develop AI for intellectual reasons and a “societalist faction” that seeks to develop (...) AI for the benefit of society. The paper argues in favor of societalism and offers three means of concurrently addressing societal impacts from near-term and long-term AI: advancing societalist social norms, thereby increasing the portion of AI researchers who seek to benefit society; technical research on how to make any AI more beneficial to society; and policy to improve the societal benefits of all AI. In practice, it will often be advantageous to emphasize near-term AI due to the greater interest in near-term AI among AI and policy communities alike. However, presentist and futurist societalists alike can benefit from each others’ advocacy for attention to the societal impacts of AI. The reconciliation between the presentist and futurist factions can improve both near-term and long-term societal impacts of AI. (shrink)

Research into artificial intelligence has increased significantly in recent years. However, the fundamental question of what intelligence is and how it works remains open to some extent. Traditional definitions of intelligence are broad and lack clarity regarding its nature and mechanisms. The nature of consciousness is another matter that has been widely explored with multiple theories but for which we do not have a final agreed theory, especially in terms of its relation to intelligence. In this (...) work, we present a preliminary theory of the nature of intelligence and its working mechanisms. We contrast it against observations to show that our theory is consistent with observed reality. We also use our theory of intelligence to offer a theory on the nature of consciousness, as well as its relation to human understanding and intent. We then show that our theories can be consistent with the theory of evolution. Similarly, we explore examples of how our theory applies to specific cases to show its consistency across applications. Lastly, we outline how our theory can pave the way towards artificial general intelligence. Our theory is unproven. (shrink)

Our society is in the middle of the AI revolution. We discuss several applications of AI, in particular medical causality, where deep-learning neural networks screen through big data bases, extracting associations between a patient’s condition and possible causes. While beneficial in medicine, several questionable AI trading strategies have emerged in finance. Though advantages in many aspects of our lives, serious threats of AI exist. We suggest several regulatory measures to reduce these threats. We further discuss whether ‘full AI robots’ should (...) be programmed with a virtual consciousness and conscience. While this would reduce AI threats via motivational control, other threats such as the desire for AI—human socioeconomic equality could prove detrimental. (shrink)

The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with (...) non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed. (shrink)

Emotional intelligence can be comprehensively redefined based on the componential emotion approach. The componential emotion approach defines emotions as processes that are elicited by goal-relevant situations and that consist of an interplay between appraisals, action tendencies, bodily reactions, expressions, and feelings. Within the componential emotion approach, emotional intelligence can be redefined as the ability to identify emotions based on information from one or more of the five emotion components, to understand emotions in terms of the likely appraisals, action (...) tendencies, bodily reactions, expressions, and feelings that are elicited by goal-relevant situations, and to know how to regulate emotions by modifying one or more of these five components. (shrink)