Tag Archives: artificial intelligence

This is the text version of remarks given by the author on June 26, 2016, at a panel on the Moral Economy of Tech at the SASE conference in Berkeley to an audience of social scientists. The other panel participants were Kieran Healy, Stuart Russell and AnnaLee Saxenian. This piece originally appeared on the author’s blog, Idle Words. I am only a small minnow in the technology ocean, but since it is my natural habitat, I want to make an effort to describe it to you. As computer programmers, our formative intellectual experience is working with deterministic systems that have been designed by other human beings. These can be very complex, but the complexity is not the kind we find in the natural world. It is ultimately always tractable. Find the right abstractions, and the puzzle box opens before you. The feeling of competence, control, and delight in discovering a clever twist that solves a difficult problem is what makes being a computer programmer sometimes enjoyable.  

“The real world is a stubborn place. It is complex in ways that resist abstraction and modeling.”

  But as anyone who’s worked with tech people knows, this intellectual background can also lead to arrogance. People who excel at software design become convinced that they have a unique ability to understand any kind of system at all, from first principles, without prior trainin... Read more

I am standing in the dark, looking at the shadows on the walls of this ancient cave when my pocket buzzes — Facebook wants to notify me that I’ve been invited to a play tonight. Who am I? You might say I am Plato, except, like, I also have a smartphone. Editor Stacy Hale had a great conversation with Bryan A. Knowles about AI and giving meaning to language. Greek philosophy, among some silly things, asks the real questions, like: “What is the true nature of the universe?” This question might seem impossible to answer simply because it is impossibly vague, but in Plato’s famous Allegory of the Cave, it is explained that we can never even look upon the face of Truth — our ability to know anything is intrinsically limited by our imprecise senses, psychological processes, and non-universal language. BK: Keep in mind that this train of thought is carried on the assumption that one true Truth exists, something that Relativity and the Uncertainty Principle and the Uniqueness Problem all contradict. Regardless, Plato’s Cave remarkably sums up much of modern scientific skepticism:  There are things we can never know, such as whether any given computer code will halt when executed; there are things we can never approximate, since all it takes is a single electron counted wrong and our weather predictions will quickly be way off; and, there are things we can never expect, such as ... Read more

Why is success deceptive and what does that have to do with robot brains, and more important, our current paradigm of innovation? Because nobody innovates in a vacuum, we can look at innovation as a network phenomenon. Network activity can take things that seem distant or unrelated and prove they belong together. Like dropping out of college to tinker in a garage and later running a billion-dollar company. Or vacuum tubes and computation.  

“Nature has an evolutionary algorithm, and it depends on emergence.”

  This is precisely what Kenneth Stanley and Joel Lehman, artificial intelligence (AI) researchers and authors of the book Why Greatness Cannot Be Planned, wanted to understand when they invented the Novelty Search algorithm. If robots can stumble upon the right answer more effectively than working a plan, maybe there’s a lesson in there for ambitious human beings. Nature has an evolutionary algorithm, and it depends on emergence. Nature is telling us that wild goose chases can be good or bad, depending on which scale you’re zoomed in on. It seeks novelty and will adapt and assimilate nearly everything in its path. Path dependence (time’s arrow), prevents us from mapping the great open search space that is the future. We only ge... Read more