Why would the machines think like us? The reason for this has nothing to do with our ways of thinking being objectively right or unique. Rather, it has to do with what I'll dub the 'big data food chain'. These AIs, if they are to emerge as plausible forms of general intelligence, will have to learn by consuming the vast electronic trails of human experience and human interests. For this is the biggest repository of general facts about the world that we have available. To break free of restricted uni-dimensional domains, these AIs will have to trawl the mundane seas of words and images that we lay down on Facebook, Google, Amazon, and Twitter. Where before they may have been force-fed a diet of astronomical objects or protein-folding puzzles, the break-through general intelligences will need a richer and more varied diet. That diet will be the massed strata of human experience preserved in our daily electronic media.
The statistical baths in which we immerse these potent learning machines will thus be all-too-familiar. They will feed off the fossil trails of our own engagements, a zillion images of bouncing babies, bouncing balls, LOL-cats, and potatoes that look like the Pope. These are the things that they must crunch into a multi-level world-model, finding the features, entities, and properties (latent variables) that best capture the streams of data to which they are exposed. Fed on such a diet, these AIs may have little choice but to develop a world-model that has much in common with our own. They are probably more in danger of becoming super-Mario freaks than becoming super-villains intent on world-domination.
--Andy Clark
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