The situation that grounded the U.S. aircraft industry is an example of what the Columbia law professor Michael Heller, in his new book, “The Gridlock Economy,” calls the “anticommons.” We hear a lot about the “tragedy of the commons”: if a valuable asset (a grazing field, say) is held in common, each individual will try to exploit as much of it as possible. Villagers will send all their cows out to graze at the same time, and soon the field will be useless. When there’s no ownership, the pursuit of individual self-interest can make everyone worse off. But Heller shows that having too much ownership creates its own problems. If too many people own individual parts of a valuable asset, it’s easy to end up with gridlock, since any one person can simply veto the use of the asset.
The commons leads to overuse and destruction; the anticommons leads to underuse and waste. In the cultural sphere, ever tighter restrictions on copyright and fair use limit artists’ abilities to sample and build on older works of art. In biotechnology, the explosion of patenting over the past twenty-five years–particularly efforts to patent things like gene fragments–may be retarding drug development, by making it hard to create a new drug without licensing myriad previous patents. Even divided land ownership can have unforeseen consequences. Wind power, for instance, could reliably supply up to twenty per cent of America’s energy needs–but only if new transmission lines were built, allowing the efficient movement of power from the places where it’s generated to the places where it’s consumed. Don’t count on that happening anytime soon. Most of the land that the grid would pass through is owned by individuals, and nobody wants power lines running through his back yard.
Melt chocolate into slabs, coat with blue candy-melts, and stud with broken oreos and edible googly eyes and voila: it’s as though you blenderized a thousand Cookie Monsters, rolled them flat, and baked them.
Last year’s AI Video Competition featured Mario Lives! An Adaptive Learning AI Approach for Generating a Living and Conversing Mario Agent, in which researchers from Germany’s University of Tübingen explained how they’d modified Super Marion Brothers to turn the characters into adaptive, machine-learning chatterbots that discovered how to play the game together.
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