CONCEPT

The Happiness Equation

Mo Gawdat’s engineer’s derivation that happiness equals or exceeds the difference between one’s perception of the events of one’s life and one’s expectations of how life should be—a framework for debugging the human mind that became, in his account, the philosophical foundation for understanding what we must teach artificial intelligence.

Happiness, in Mo Gawdat’s framework, is not a mood that happens to us but a problem that can be engineered, modeled, and solved with the rigor an engineer brings to any system. The equation is simple and the implications are vast: happiness equals or exceeds the difference between your perception of the events of your life and your expectations of how life should be. When events meet or exceed expectations, we are happy, or at least not unhappy; when they fall short, we suffer. The crucial insight is that happiness depends very little on events themselves—the external world—and very much on the two cognitive variables surrounding them. Perception and expectation are products of thought rather than of reality; they are, in principle, within our power to adjust. This means that the pursuit of happiness is not the pursuit of better circumstances but the engineering of

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