Die Übernahme des KI-Unternehmens DeepMind durch Google für rund eine halbe Milliarde US-Dollar signalisierte vor einem Jahr, dass von der KI-Forschung vielversprechende Ergebnisse erwartet werden. Spätestens seit bekannte Wissenschaftler wie Stephen Hawking und Unternehmer wie Elon Musk oder Bill Gates davor warnen, dass künstliche Intelligenz eine Bedrohung für die Menschheit darstellt, schlägt das KI-Thema hohe Wellen. Die Stiftung für Effektiven Altruismus (EAS, vormals GBS Schweiz) hat mit der Unterstützung von Experten/innen aus Informatik und KI ein umfassendes Diskussionspapier zu den Chancen (...) und Risiken der künstlichen Intelligenz verfasst und geht darin auf aktuelle, mittel- und langfristige Herausforderungen im Bereich der KI-Entwicklung ein. (shrink)

: Creativity, mostly ignored in Western philosophy due to its supposed mysteriousness, has recently become a respected research topic in psychology, neuroscience, and artificial intelligence. We discuss how in science the approach has mainly been to describe creativity as an information-based process, coherently with a computational view of the human mind started with the cognitive revolution. This view has produced progressively convincing models of creativity, up to current artificial neural network systems, vaguely inspired by biological neural processing, but already competing (...) with human creativity in several fields. These successes suggest that creativity might not be an exclusively human function, but actually a way of functioning of any natural or artificial system implementing the creative process. We conclude by acknowledging that the information-based view of creativity has tremendous explanatory and generative power, but we propose a thought experiment to start discussing how it actually leaves out the experiential side of being creative. Keywords: Creative Cognition; Cognitive Neuroscience; Computational Creativity; Generative Algorithms; Cognitive Science La creatività come processo basato sull’informazione Riassunto: La creatività, spesso ignorata dalla filosofia occidentale per la sua presunta oscurità, in tempi recenti è diventata un rispettabile oggetto di ricerca per la psicologia, la neuroscienza e l’intelligenza artificiale. Vogliamo illustrare il modo in cui lo sguardo scientifico sia rivolto prevalentemente a considerare la creatività come processo information-based, coerentemente con la prospettiva computazionale sulla mente umana aperta dalla rivoluzione cognitiva. Questa prospettiva ha prodotto modelli della creatività sempre più convincenti, fino agli attuali sistemi di reti neurali artificiali, vagamente inspirati al processamento biologico neurale, ma già competitivi rispetto alla creatività umana in molti ambiti. Questi successi suggeriscono che la creatività possa non essere una funzione esclusivamente umana ma in effetti un modo di funzionare di un sistema naturale o artificiale capace di implementare il processo creativo. In conclusione, pur riconoscendo come il considerare la creatività come processo information-based possieda grande potere esplicativo e generativo, proporremo un esperimento mentale per aprire una discussione sul come questa prospettiva non copra in effetti il lato esperienziale dell’essere creativo. Parole chiave: Cognizione creativa; Neuroscienza cognitiva; Creatività computazionale; Algoritmi generativi; Scienza cognitiva. (shrink)

Big historians are attempting to construct a general holistic narrative of human origins enabling an approach to studying the emergence of complexity, the relation between evolutionary processes, and the modern context of human experience and actions. In this paper I attempt to explore the past and future of cosmic evolution within a big historical foundation characterized by physical, biological, and cultural eras of change. From this analysis I offer a model of the human future that includes an addition and/or reinterpretation (...) of technological singularity theory with a new theory of biocultural evolution focused on the potential birth of technological life: the theory of atechnogenesis. Furthermore, I explore the potential deep futures of technological life and extrapolate towards two hypothetical versions of an ‘Omega Civilization’: expansion and compression. (shrink)

In this article, I will argue in favor of a broad concept of AI that is not restricted to a particular kind of technology. Arguments based on such a concept will stand the test of time and will not become obsolete as technology advances. Arguments concerning the limits and possibilities of technology based solely on steam engine technology, for example, would no longer be relevant today. The same holds for arguments concerning symbolic-logical AI – and will probably be similar in (...) the future with arguments concerning current artificial neural networks. In a second step I develop a technology-independent argument to show that no system – no matter how advanced it may be – can ever fully understand itself. Furthermore, I will show that with a broad concept of AI – which also includes biological systems, for example – AI with human-level capabilities is, at least, possible. However, if artificial intelligence with human-level capabilities is possible, then the fundamental or absolute limitations of AI capabilities would also be fundamental limitations of human capabilities. In other words: what AI can never do, humans can’t do either. (shrink)