2.25.2015

02-25-2015 | Mechanical Cognition III



Smart people often manage to avoid the cognitive errors that bedevil less well-endowed minds. But there are some kinds of foolishness that seem only to afflict the very intelligent. Worrying about the dangers of unfriendly AI is a prime example. A preoccupation with the risks of superintelligent machines is the smart person’s Kool Aid.

Why do some otherwise very smart people fall for this sleight of hand? I think it is because it panders to their narcissism. To regard oneself as one of a select few far-sighted thinkers who might turn out to be the saviors of mankind must be very rewarding. But the argument also has a very material benefit: it provides some of those who advance it with a lucrative income stream. For in the past few years they have managed to convince some very wealthy benefactors not only that the risk of unfriendly AI is real, but also that they are the people best placed to mitigate it. The result is a clutch of new organizations that divert philanthropy away from more deserving causes. It is worth noting, for example, that Give Well—a non-profit that evaluates the cost-effectiveness of organizations that rely on donations—refuses to endorse any of these self-proclaimed guardians of the galaxy.

But whenever an argument becomes fashionable, it is always worth asking the vital question—Cui bono? Who benefits, materially speaking, from the growing credence in this line of thinking? One need not be particularly skeptical to discern the economic interests at stake. In other words, beware not so much of machines that think, but of their self-appointed masters.

-- Dylan Evans

2.24.2015

02-24-2015 | Mechanical Cognition II



"Think" and "intelligence" are both what Marvin Minsky has called suitcase words. They are words into which we pack many meanings so that we can talk about complex issues in a shorthand way. When we look inside these words we find many different aspects, mechanisms, and levels of understanding. This makes answering the perennial questions of "can machines think?" or "when will machines reach human level intelligence?" fraught with danger. The suitcase words are used to cover both specific performance demonstrations by machines and more general competence that humans might have. People are getting confused and generalizing from performance to competence and grossly overestimating the real capabilities of machines today and in the next few decades.

In 1997 a super computer beat world chess champion Garry Kasparov in a tournament. Today there are dozens of programs that run on laptop computers and have higher chess rankings than those ever achieved by humans. Computers can definitely perform better than humans at playing chess. But they have nowhere near human level competence at chess.

All chess playing programs use Turing's brute force tree search method with heuristic evaluation. Computers were fast enough by the seventies that this approach overwhelmed other AI programs that tried to play chess with processes that emulated how people reported that they thought about their next move, and so those approaches were largely abandoned.

Today's chess programs have no way of saying why a particular move is "better" than another move, save that it moves the game to a part of a tree where the opponent has less good options. A human player can make generalizations and describe why certain types of moves are good, and use that to teach a human player. Brute force programs cannot teach a human player, except by being a sparing partner. It is up to the human to make the inferences, the analogies, and to do any learning on their own. The chess program doesn't know that it is outsmarting the person, doesn't know that it is a teaching aid, doesn't know that it is playing something called chess nor even what "playing" is. Making brute force chess playing perform better than any human gets us no closer to competence in chess.

-- Rodney A. Brooks - click to read the rest, it's quite superb.

2.23.2015

02-23-2015 | Mechanical Cognition I



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

2.21.2015

02-21-2015 | Bottom Lines



"Although, invoking U.S. Supreme Court Justice Louis Brandeis, online collectives have been hailed as contemporary “laboratories of democracy”, our findings suggest that they may not necessarily facilitate enhanced practices of democratic engagement and organization. Indeed, our results imply that widespread efforts to appropriate online organizational tactics from peer production may facilitate the creation of entrenched oligarchies in which the self-selecting and early-adopting few assert their authority to lead in the context of movements without clearly defined institutions or boundaries."

From "Wikipedia and the Oligarchy of Ignorance," which is quite superb. Read that.