Artificial intelligence, Explainable AI, Hybrid Intelligence
The Quest for Hybrid Intelligence
These are just two of the predictions of the type that have flooded the media over the past five years. Besides many (if not all) of them being wildly overoptimistic, they also reveal a hidden (and sometimes not so hidden) assumption underlying much mainstream work in current AI: artificially intelligent machines were going to replace humans in a wide variety of tasks. Radiologists, taxi drivers, security personnel, construction workers, even teachers and social workers were going to be replaced by AI systems.
In a recently started large Dutch research consortium, we beg to differ. Not only is this “replacement modus” of AI socially unattractive, it makes little scientific sense. It is becoming increasingly likely that human intelligence and artificial intelligence will be very different from each other. They could be as different from each other as artificial flight differs from human flight; just as “natural” bird flight is very different from “artificial” (aeroplane) human flight. When simply trying to replace one with the other, we might well end up trying to squeeze the proverbial round peg into the square hole.
Combining Human and Artificial Intelligence
Increasingly, an alternative way to think about AI is gaining ground: not “Artificial Intelligence”, but “Hybrid Intelligence”. Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. Our goal is to design Hybrid Intelligent systems, an approach to AI that puts humans at the centre, changing the course of the ongoing AI revolution.
In order to build Hybrid Intelligent systems we will have to address a whole host of deep research questions which are all too often ignored in the current AI research agenda, which is dominated by the replacement modus. We have summarised these research challenges in the acronym “CARE”: Collaborative, Adaptive, Responsible and Explainable AI.
When people collaborate, they use extensive mental models of each other: what does my colleague know, what does she believe about what I know. To build truly collaborative AI, we will need to equip our machines with a similar “theory of mind”. We’re aiming to do that in collaborations between AI researchers, logicians, cognitive scientists and social psychologists.
When people collaborate, they do so in a world that is constantly changing, and in teams that are constantly changing. Our future HI systems must be similarly adaptive, being able to predict and respond to changes in the world and the teams in which they operate.
And of course, meaningful collaboration assumes a shared set of values and goals between the members of a team. This will require us to build responsible HI systems that take these shared norms, values and goals into account.
Finally, communication is crucial for collaboration. Team members must be able to explain their decisions to each other. Explainable AI is currently a hot topic in research, and the quest for HI will make this topic only more important than it already is.
The Hybrid Intelligence Centre
Our ambitious research programme is a collaboration of teams at six Dutch universities ( Groningen, Leiden, Utrecht and Amsterdam, the TU Delft, with the Vrije Universiteit Amsterdam as coordinator). It will run for 10 years, and over these 10 years over 50 PhD students and postdocs, in collaboration with some 30 staff members, will tackle the above questions.
Keep an eye on The Hybrid Intelligence Centre to check our progress! And, last but not least: if you are an ambitious student about to complete your MSc, take a look at https://www.hybrid-intelligence-centre.nl/jobs, which lists the first 27 positions that we will be filling before the summer!
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