five sides, mounted on a ten-foot-wide mirrored base. A variety of viscous and unpleasant-looking fluids (yellow, reddish-orange, brown), dry materials (sawdust? flour?), and even insects drizzle or dust their way down the head, whose stoic sublimity is made gorgeously virtual on the work’s enormous screens. Dead Imagine, through its large-scale and cubic “Platonic” form, remains both artificial and locked into the body— refusing a detached “intelligence” as being no intelligence at all. Artists in the new millennium inherit this critical tradition and inhabit the current paradigms of AI, which has slid from partial simulations to claims of intelligence. In the 1955 proposal thought to be the first printed usage of the phrase “artificial intelligence,” computer scientist John McCarthy and his colleagues Marvin Minsky, Nathaniel Rochester, and Claude Shannon conjectured that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” This modest theoretical goal has inflated over the past sixty-four years and is now expressed by Google DeepMind as an ambition to “Solve intelligence.” Crack the code! But unfortunately, what we hear cracking is not code but small-scale capitalism, the social contract, and the scaffolding of civility. Taking away the jobs of taxi and truck drivers, roboticizing direct marketing, hegemonizing entertainment, privatizing utilities, and depersonalizing health care—are these the “whips” that Wiener feared we would learn to love? Artists can’t solve any of this. But they can remind us of the creative potential of the paths not taken—the forks in the road that were emerging around 1970, before “information” became capital and “intelligence” equaled data harvesting. Richly evocative of what can be done with contemporary tools when revisiting earlier possibilities is French artist Philippe Parreno’s “firefly piece,” so nicknamed to avoid having to iterate