what babies can tell us about the future of a.i.

Could babies show future robots the proper way to interact with other humans?

Having seen that babies seem to have an innate sense of rudimentary morality, we’ve gotten a little glimpse into the kind of research that can answer fundamental questions about what makes us who we are. And while we’re learning about the evolution of complex social interactions from infants, we can also apply a number of these findings to one of the biggest and most complex challenges in computer science: building an artificial intellect capable of passing the Turing test. Just to get a better idea of what we’re talking about, let me bring back Jeffrey, the robot whose feelings were carelessly hurt by an engineer in Intel’s Super Bowl commercial…

Now let’s down break the mechanics of this interaction. The robot hears a conversation and understands the words and the context. It identifies what the engineer is talking about with so much excitement and finds out it was being indirectly put down while being totally ignored. It gets offended and responds with sadness and an equivalent of crying. Sounds simple, right? Well, consider that Jeffrey will be science fiction for at least the next decade, if not longer, and even then, its intelligence is roughly on par with a six to eight month infant who was born with the brain wiring which makes everything we listed above either innate, or achievable as soon as the child will start understanding tone and picking up on basic context. In this comparison, babies have an unfair advantage since they have millions of years of evolution on their side as well as being wired to start learning, connecting, and forming social bonds since day one. Machines start with a blank slate. What we know about the surprisingly complex psychology of infant minds seems to be telling us that AI theories which use the way babies learn seemingly from scratch as their starting points are mistaken since humans are essentially pre- wired to do what they do and our formative years are only possible because of this.

We could even argue that the roots of what enabled human intellect started with the very first mammals, which appeared around 200 million years ago. Nature has an enormous head start on intelligence, which evolved in squids, octopi, cetaceans, birds like parrots as well as primates. Considering that machines have none of the plasticity or the advantages undergoing of eons worth of experiments which use evolutionary algorithms, it’s a pretty big stretch for us to jump into trying to simulate human intelligence, which can be rather hard to define in terms of concrete functional requirements. This doesn’t mean that we’d need to wait millions of years for an intelligent system of course. Trials can be ran much faster in the lab than in nature.

But rather than starting with something as nebulous and abstract as the human mind, maybe we should give the alternative method of modeling insect intelligence a shot. It would be far less resource intensive and allow us to get into the real basics of what an intellect requires, without bothering with languages and contexts right away. How? Well, as detailed in the link, the major difference between insect minds and brains like ours is the repetition of neuron circuits which are generally thought to allow for more precise control over large bodies and enable ever more complex mechanics and social interactions as a very useful and evolutionary advantageous side-effect. If you can track down the right patterns, you may be one step closer to solving the mysteries of intelligence…

# tech // artificial intelligence / computer science / evolution / intelligence

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