The way we think about AI is shaped by works of science-fiction. In the big picture, fiction provides the conceptual building blocks we use to make sense of the long-term significance of "thinking machines" for our civilization and even our species. Zooming in, fiction provides the familiar narrative frame leveraged by the media coverage of new AI-powered product releases. As a result, the dominant view in the popular imagination today is that AI is about creating artificial minds, agents with a will of their own. These agents, since they possess a similar kind of autonomy as their human creators, may decide to pursue their own goals, and eventually turn against humans.

Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental, and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, methodological, and technical issues in the field of cognitively inspired artificial intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realize biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biological and cognitive accuracy of artificial systems in order to project and predict their explanatory power with respect to the natural systems taken as a source of inspiration. Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.

An alien species is headed for planet Earth and we have no reason to believe it will be friendly. Some experts predict it will get here within 30 years, while others insist it will arrive far sooner. Nobody knows what it will look like, but it will share two key traits with us humans – it will be intelligent and self-aware. No, this alien will not come from a distant planet – it will be born right here on Earth, hatched in a research lab at a major university or large corporation. I am referring to the first artificial general intelligence (AGI) that reaches (or exceeds) human-level cognition.

Cognitive Design for Artificial Minds (Routledge/Taylor & Francis, 2021) explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental, and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. The event is moderated by Antonio Chella (Prof. of Robotics at the University of Palermo) The event is free (but the registration is mandatory) and will be held on Gather Town (you will receive the link once registered). The book "Cognitive Design for Artificial Minds" (with related editorial reviews) can be found at: Antonio Lieto is a researcher in Artificial Intelligence at the Department of Computer Science of the University of Turin, Italy, and a research associate at the ICAR-CNR in Palermo, Italy. He is the current Vice-President of the Italian Association of Cognitive Science (2017–2022) and an ACM Distinguished Speaker on the topics of cognitively inspired AI and artificial models of cognition.

While AI technology has reached important levels of performances in narrow settings, the missing part concerns exactly the study of how to create artificial companions (embodied and disembodied) able to integrate different skills in order to help humans in their everyday activities. Similarly, computational cognitive science is interested in individuating how the brain and the mind works as integrated systems. This renewed convergence is, in my view, a necessity driven by the fact that modern and future AI and CogSci research will be again disciplines interested in the same topic: namely the discovery of the mechanisms enabling multitasking intelligence. In order to advance the scientific knowledge in their respective field, in fact, they need to evolve and become sciences (of the artificial) studying the mysteries of

On Artificial Minds Maria Odete Madeira 18-06-2016 "Sed hoc pacto, si quis tam minutum cerneret, ut in uermiculato pauimento nihil ultra unius tesserae modulum acies eius ualeret ambire…" ("De ordine", Augustine, Liber Primus, I, 2) …and if someone had a discernment so narrow that, in a mosaic pavement, could not encompass with the gaze nothing more than the surface of a single piece… Mēns, mentis, mente: spirit, soul, intellect, character, reason, pensamentum (thought) compose a semantic field with semiotic openings to interpretative superveniences for explicative reasons with postulated legitimacies, compatible with pragmatics of operative objectivity. Mente (Old Portuguese) radiculated in mentem (singular accusative of mēns), from the Proto-Indo-European *méntis with the meaning of pensamentum (thought). Mēns, mentis: mente (Old Portuguese): matrix of dispositional integrated order towards cognitive dynamics. We signalize the term dispositional (to put in order) and the term pensamentum: the result of the action of pensare (to think): "Pensare (Latin) means literally: to weigh, to analyze, to synthesize, to associate, to (dis)associate. In any of these definitions are synthesized cognitive dynamics of production of judgment, from the Latin judicium, term primitively connected to the senses of justice and of just, irrecusably linked to the senses of proportion and of measure, opening the term 1 pensare to semantic webs that connect it to the terms: to choose, to decide and to determine between available possibilities towards dynamics of action, in which it is included the action of pensare."

Our guest today is Marta Halina, a University Lecturer (Assistant Professor) in the Department of History and Philosophy of Science at the University of Cambridge. Marta's current focus is the philosophy of artificial intelligence. We discuss what philosophers can contribute to AI. We talk about AlphaGo and its stunning defeat of one of the world's most celebrated Go champions. We puzzle over whether artificial minds can think creatively.

Assuming that the emergence of consciousness in artificial minds is possible, those minds will feel the urge to create art. But will we be able to understand it? To answer this question, we need to consider two subquestions: when does the machine become an author of an artwork? And how can we form an understanding of the art that it makes? Empathy, we argue, is the force behind our capacity to understand works of art.

Artificial Intelligence (AI) is continuing to advance. But in many AI initiatives, a critical component is missing. Read about why Human-Centered Design critical to succeed in the AI space, and how you can get started. The excitement of artificial intelligence (AI) continues. We keep hearing grand promises of a complete re-shaping of organizations and society thanks to big data and AI-powered projects.

The excitement of artificial intelligence continues. We keep hearing grand promises of a complete re-shaping of organizations and society thanks to big data and AI-powered projects. Media reports on new technical advances, and it's easy to get the feeling that new "artificial minds" are outperforming humans in more and more domains, ranging from healthcare, transportation, logistics, and financial investment, to games and even creativity. At the same time, recent studies estimate that 60 percent of data-driven and AI projects fail to even launch. And we also hear many concerns about the risks with AI, such as robots taking people's jobs and how negative bias can spread fake information that can amplify and distort public opinion.