Recent advancements in AI have prompted a large number of AI ethics guidelines published by governments and nonprofits. While many of these papers propose concrete or seemingly applicable ideas, few philosophically sound proposals are made. In particular, we observe that the line of questioning has often not been examined critically and underlying conceptual problems not always dealt with at the root. In this paper, we investigate the nature of ethical AI systems and what their moral status might be by first (...) turning to the notions of moral agency and patience. We find that their explication would come at a too high cost which is why we, second, articulate a different approach that avoids vague and ambiguous concepts or the problem of other minds. Third, we explore the impact of our philosophical and conceptual analysis on the regulatory landscape, make this link explicit, and finally propose a set of promising policy steps. (shrink)

100 years ago, the editors of the Journal of Educational Psychology conducted one of the most famous studies of experts' conceptions of human intelligence. Reason enough to prompt the question where we stand today with conceptualizing 'intelligence'. In this paper, I provide a synopsis of the latest research on human intelligence(s). I embrace the notion of intelligence as a non-unitary faculty with pluralistic forms. Even though I do not provide a definition of 'intelligence' of my own, I provide good reasons (...) for this reluctance. Nonetheless, I specify the term as complex, gradual, embedded, multidirectional, and dynamic. Furthermore, I argue for the special status of musical, not linguistic, intelligence. (shrink)

Recent findings about the capabilities of smart animals such as corvids or octopi and novel types of artificial intelligence, from social robots to cognitive assistants, are provoking the demand for new answers for meaningful comparison with other kinds of intelligence. This book fills this need by proposing a universal theory of intelligence which is based on causal learning as the central theme of intelligence. The goal is not just to describe, but mainly to explain queries like why one kind of (...) intelligence is more intelligent than another, whatsoever the intelligence. Shiny terms like "strong AI," "superintelligence," "singularity" or "artificial general intelligence" that have been coined by a Babylonian confusion of tongues are clarified on the way. (shrink)

100 years ago, the editors of the Journal of Educational Psychology conducted one of the most famous studies of experts’ conceptions of human intelligence. This was reason enough to prompt the question where we stand today with making sense of “intelligence”. In this paper, we argue that we should overcome our anthropocentrism and appreciate the wonders of intelligence in nonhuman and nonbiological animals instead. For that reason, we study two cases of octopus intelligence and intelligence in machine learning systems to (...) embrace the notion of intelligence as a non-unitary faculty with pluralistic forms. Furthermore, we derive lessons for advancing our human self-understanding. (shrink)

More intellectual modesty, but also conceptual clarity is urgently needed in AI, perhaps more than in many other disciplines. AI research has been coined by hypes and hubris since its early beginnings in the 1950s. For instance, the Nobel laureate Herbert Simon predicted after his participation in the Dartmouth workshop that “machines will be capable, within 20 years, of doing any work that a man can do”. And expectations are in some circles still high to overblown today. This paper addresses (...) the demand for conceptual clarity and introduces precise definitions of “strong AI”, “superintelligence”, the “technological singularity”, and “artificial general intelligence” which ground in the work by the computer scientist Judea Pearl and the psychologist Howard Gardner. These clarifications allow us to embed famous arguments from the philosophy of AI in a more analytic context. (shrink)

The Two Envelopes Problem is a beautiful and quite confusing problem in decision theory which is ca. 35 years old and has provoked at least 150 papers directly addressing the problem and displaying a surprising variety of different responses. This paper finds decisive progress in an approach of Priest and Restall in 2003, contends that the recent papers having appeared since did not really go beyond that paper, argues further that Priest’s and Restall’s solution is still not complete, and proposes (...) a completion of their solution. If the analysis is correct, this work has the potential of laying the Two Envelopes Problem at rest. (shrink)

How can a present or future event causally influence one in the past? Even though the case of such a relationship is often quickly dismissed as impossible, this paper suggests that this reaction is hasty and omits interesting as well as substantive arguments and considerations. In an introductory synopsis of the metaphysics of causality, we first present and discuss arguments for and against the possibility of backwards causation. On the other hand, we suggest that a probabilistic notion of causality according (...) to Suppes need not exclude that causes occur temporally after their effects. (shrink)