Why AI needs a physical body to emotionally connect with humans
Theory of mind
Of course, we already have primitive versions of such systems. But audio-command systems and call-centre-style script-processing justpretend to be conversations. What is needed are proper social interactions, involving free-flowing conversations over the long term during which AI systems remember the person and their past conversations. AI will have to understand intentions and beliefs and the meaning of what people are saying.
This requires what is known in psychology as atheory of mind– an understanding that the person you are engaged with has a way of thinking, and roughly sees the world in the same way as you do. So when someone talks about their experiences, you can identify and appreciate what they describe and how it relates to yourself, giving meaning to their comments.
We also observe the person’s actions and infer their intentions and preferences from gestures and signals. So when Sally says, “I think that John likes Zoe but thinks that Zoe finds him unsuitable”, we know that Sally has a first-order model of herself (her own thoughts), a second-order model of John’s thoughts, and a third-order model of what John thinks Zoe thinks. Notice that we need to have similar experiences of life to understand this.
Physical learning
It is clear that all this social interaction only makes sense to the parties involved if they have a “sense of self” and can similarly maintain a model of the self of the other agent. In order to understand someone else, it is necessary to know oneself. An AI “self model” should include a subjective perspective, involving how its body operates (for example, its visual viewpoint depends upon the physical location of its eyes), a detailed map of its own space, and a repertoire of well understood skills and actions.
That means a physical body is required in order to ground the sense of self in concrete data and experience. When an action by one agent is observed by another, it can be mutually understood through the shared components of experience. This means social AI will need to be realized in robots with bodies. How could a software box have a subjective viewpoint of, and in, the physical world, the world that humans inhabit? Our conversational systems must be not just embedded but embodied.
A designer can’t effectively build a software sense-of-self for a robot. If a subjective viewpoint were designed in from the outset, it would be the designer’s own viewpoint, and it would also need to learn and cope with experiences unknown to the designer. So what we need to design is a framework that supports the learning of a subjective viewpoint.
Fortunately, there is a way out of these difficulties. Humans face exactly the same problems but they don’t solve them all at once. The first years of infancy displayincredible developmental progress, during which we learn how to control our bodies and how to perceive and experience objects, agents and environments. We also learn how to act and the consequences of acts and interactions.
Research in the new field of developmental robotics is now exploring how robots can learn from scratch, like infants. The first stages involve discovering the properties of passive objects and the “physics” of the robot’s world. Later on, robots note and copyinteractions with agents(carers), followed by gradually more complex modeling of the self in context. Inmy new book, I explore the experiments in this field.
So while disembodied AI definitely has a fundamental limitation, future research with robot bodies may one day help create lasting, empathetic, social interactions between AI and humans.
This article is republished fromThe ConversationbyMark Lee, Emeritus Professor in Computer Science,Aberystwyth Universityunder a Creative Commons license. Read theoriginal article.
Story byThe Conversation
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