Why Greatness Cannot Be Planned: The Myth of the Objective Kenneth O. Stanley, Associate Professor, University of Central Florida
In artificial intelligence and elsewhere, it has long been assumed that the best way to achieve an ambitious outcome is to set it as an explicit objective and then to measure progress on the road to its achievement. Upending this conventional wisdom, a series of unusual experiments in machine learning has shown that, for a broad class of outcomes, the very act of setting objectives can block their achievement. More fundamentally, the same so-called “objective paradox” applies not only in computer algorithms but across many human endeavors: Often, to achieve our highest aspirations, we must be willing to abandon them. As a corollary, collaboration can sometimes thwart innovation by tacitly forcing its participants into an objective-driven mindset. The moral is both sobering and liberating: We can potentially achieve more by following a non-objective yet still principled path, after throwing off the shackles of objectives, metrics, and mandated outcomes.