Google’s shopping spree has continued with the purchase of the British artificial intelligence (AI) start-up DeepMind, acquired for an eye-watering £400M ($650M).  This is Google’s 8^th biggest acquisition in its history, and the latest in a string of purchases in AI and robotics. Boston Dynamics, an American company famous for building agile robots capable of scaling walls and running over rough terrain (see BigDog here), was mopped up in 2013. And there is no sign that Google is finished yet. Should we be excited or should we be afraid?

Probably both. AI and robotics have long promised brave new worlds of helpful robots (think Wall-E) and omniscient artificial intelligences (think HAL), which remain conspicuously absent. Undoubtedly, the combined resources of Google’s in-house skills and its new acquisitions will drive progress in both these areas. Experts have accordingly fretted about military robotics and speculated how DeepMind might help us make better lasagne. But perhaps something bigger is going on, something with roots extending back to the middle of the last century and the now forgotten discipline of cybernetics.

The founders of cybernetics included some of the leading lights of the age, including John Von Neumann (designer of the digital computer), Alan Turing, the British roboticist Grey Walter and even people like the psychiatrist R.D. Laing and the anthropologist Margaret Mead.  They were led by the brilliant and eccentric figures of Norbert Wiener and Warren McCulloch in the USA, and Ross Ashby in the UK. The fundamental idea of cybernetics was consider biological systems as machines. The aim was not to build artificial intelligence per se, but rather to understand how machines could appear to have goals and act with purpose, and how complex systems could be controlled by feedback. Although the brain was the primary focus, cybernetic ideas were applied much more broadly – to economics, ecology, even management science.  Yet cybernetics faded from view as the digital computer took centre stage, and has remained hidden in the shadows ever since.  Well, almost hidden.

One of the most important innovations of 1940s cybernetics was the neural network, the idea that logical operations could be implemented in networks of brain-cell-like elements wired up in particular ways. Neural networks lay dormant, like the rest of cybernetics, until being rediscovered in the 1980s as the basis of powerful new ‘machine learning’ algorithms capable of extracting meaningful patterns from large quantities of data. DeepMind’s technologies are based on just these principles, and indeed some of their algorithms originate in the pioneering neural network research of Geoffrey Hinton (another Brit), who’s company DNN Research was also recently bought by Google and who is now a Google Distinguished Researcher.

What sets Hinton and DeepMind apart is that their algorithms reflect an increasingly prominent theory about brain function. (DeepMind’s founder, the ex-chess-prodigy and computer games maestro Demis Hassabis, set up his company shortly after taking a Ph.D. in cognitive neuroscience.) This theory, which came from cybernetics, says that the brains’ neural networks achieve perception, learning, and behaviour through repeated application of a single principle: predictive control.  Put simply, the brain learns about the statistics of its sensory inputs, and about how these statistics change in response to its own actions. In this way, the brain can build a model of its world (which includes its own body) and figure out how to control its environment in order to achieve specific goals. What’s more, exactly the same principle can be used to develop robust and agile robotics, as seen in BigDog and its friends

Put all this together and so resurface the cybernetic ideals of exploiting deep similarities between biological entities and machines.  These similarities go far beyond superficial (and faulty) assertions that brains are computers, but rather recognize that prediction and control lie at the very heart of both effective technologies and successful biological systems.  This means that Google’s activity in AI and robotics should not be considered separately, but instead as part of larger view of how technology and nature interact: Google’s deep mind has deep roots.

What might this mean for you and me? Many of the original cyberneticians held out a utopian prospect of a new harmony between people and computers, well captured by Richard Brautigan’s 1967 poem – All Watched Over By Machines of Loving Grace – and recently re-examined in Adam Curtis’ powerful though breathless documentary of the same name.  As Curtis argued, these original cybernetic dreams were dashed against the complex realities of the real world. Will things be different now that Google is in charge?  One thing that is certain is that simple idea of a ‘search engine’ will seem increasingly antiquated.  As the data deluge of our modern world accelerates, the concept of ‘search’ will become inseparable from ideas of prediction and control.  This really is both scary and exciting.