Babylonian lottery is a term borrowed from literature for which no scientific term exists. It describes the slow encroachment of programmatic choice, or what we refer to today as “algorithms”. Today we feel the weight of these algorithms. They amplify our product choices and news recommendations; they’re embedded in our financial markets. While we may not have direct experience building algorithms or understand their reach we believe them to be all encompassing.
Algorithms as rules for computation are nothing new. What’s new is the sudden cognizance of their scope Algorithms have evolved from deterministic to probabilistic, broadening in scope and incorporating randomness and noisy social signals. A probabilistic computation feels somehow mightier than a deterministic one; we can know it in expectation but not exactly. Today’s algorithms are increasingly specialized. Few can both understand the first principles and make a meaningful contribution at its bleeding edge.
That algorithms aren’t neutral but in many cases codify bias or chance isn’t news to anyone who’s worked with them. The way out of Babylon is found in storytelling. A story, like a code of ethics, is unlike any algorithm. Algorithms are rules for determining outcomes. Stories are guides to decision-making along the way. A story teaches us to make new mistakes rather than recursively repeating the old. It reminds us that the reach of algorithms is perhaps more limited than we think. By beginning with rather than arriving at meaning, a story can overcome the determinism of chance.