Euformation Technology



The deployment of artificial intelligence and technology today is sometimes accompanied by a general – public, academic, corporate… – discourse about the necessity for it to be “good”, “human-centred”, “ethical”, “sustainable”, “universal”, etc. Information Technology has become euformation technology, from the Greek prefix eu (good, beneficial, pleasant, true): machines need not only to perform but also to be well-intentioned and deliver a “better society”.

However, humanity has never – and today less than ever – reached a consensus on what constitutes a good life. So how could we code the good life into our anthrobots? Should we have right-wing or leftist AI? The discourse about “good AI” must not only be about calming the people’s fears or ubiquitous social control in an anthrobotic era. Ethical committees may be well-intentioned but not always clear-minded regarding “the better society” they might wish to promote.

We know that hell can be paved with good intentions. What if “good AI” turned out to be the worse possible AI, a golden prison of artificial benevolence? What if benevolent and human-centred technology turned out to be, in the long term, nefarious for the prospect of life on earth and the socially-creative disparity of humanity? We should remain critical about universalistic beneficial solutions, and focus more on the notion of deployment.

There is much focus today on development and design, and each day we are presented with fascinating experiments and promises that won’t scale up or be implemented into reality. Deployment, the effectual spread of anthrobotic practices, on-site and “in the wild”, remains understudied, perhaps because it seems to differ on a case-by-case basis. When a complex technology is deployed, it is modified and the world changes along with it.

As we carefully deploy our anthrobotic environments, we need to give up on the anthropocentric bias and see the world as a constant and unsettled process of intertwined deployments, in which global felicity is never certain and perhaps metamorphic.

AI och Robotar / Luis de Miranda / Intervju – P4 Sverigesradio (Svenska)

Luis de Miranda Tre i rad

En intervju genomförd av Päivi Kotka
P4 Örebro Sveriges Radio

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Call for chapters: Humans Meet AI


Following our successful international conference in June 2019 at Örebro University, Prof Alessandro Saffiotti and myself will be the editors of the following book. We wish to extend the chapters to authors that did not participate in the symposium. You are welcome to send your abstract before the end of September 2019. Full papers (7000 words) are expected by the end of 2019 and content will be peer-reviewed. The publisher is very likely to be Springer (Anticipation Science Series). Please contact us for more details.

Humans Meet AI

Anticipating Anthrobotic Systems

Much has been said about artificial intelligence being used to replace the need for human workers, and perhaps even for human intelligence. We propose a reflection on the relationship between humans and AI, not in terms of replacement, but in terms of encounter, if possible a collaborative and supportive meeting. How is that possible? First we ought to admit, problematize and understand the anthrobotic nature of our epoch, the fact that humans and intelligent systems are now enmeshed in socio-technical ensembles. Then we need to anticipate what situations, issues or opportunities this merging might implicate, given that AI tools are often used today to reinforce analytical methods of prediction, a form of mechanistic anticipatory intelligence. If human and biological anticipation is more than reactive and mechanistic prediction, how can it play a role in the new anthrobotic symbiosis, if it is a symbiosis: intuitive, participative, proactive, dialectical, creative? This book emerged from the cross-disciplinary conference “Anticipation and Anticipatory Systems: Humans Meet AI”, organized at the university of Örebro in June 2019. It combines papers by computer scientists, philosophers, sociologists, psychologists, historians, etc. It is a unique and long-awaited contribution to the fields of Anticipation Studies and collaborative AI, and a contribution to the necessary cross-disciplinarity needed to solve the challenges and problems of cognitive automation in the twenty-first century.