A few mostly-ignored lines in the US-Mexico-Canada Agreement serve to illuminate the tensions emerging among the public’s right to explainable AI decisions, corporate intellectual property and government security.
Even if algorithmic transparency is technically feasible, can we expect corporate entities engaged in a worldwide battle for AI domination to divulge this proprietary information in any meaningful manner?
For O’Neil, evaluating the quality of an algorithm is not only contingent on assessing the data employed to train it, but determined by its impact on everyone who might be affected by the decisions it makes.
“It’s a game that you would never have fun playing,” admitted Irvine.