AI-indecision is a recursive trap. Don't get stuck.

Jean Buridan was a 14th-century French philosopher and logician who twice served as rector of the University of Paris. His subject was the will, and he made an austere claim: the will follows the intellect. Show a rational creature the greater good and it'll pick the greater good. On Buridan's account, the will keeps one freedom - the power to defer the intellect's verdict and call for more inquiry before it acts.<br>But if the will only moves once reason names a winner, what happens when the options come out entirely even?<br>Buridan's posthumous critics illustrated the problem with what became known as Buridan's Ass: put a standard-issue donkey midway between two identical bales of hay. It has no reason to prefer the left bale to the right, so by Buridan's own logic it can't move, and it must stand in place until it starves. The rational animal should hold off and keep deliberating. Suspend action, wait for new information, look harder, and trust that more reflection turns up some asymmetry that lets the animal move. Give reason enough time, and the tie breaks.<br>While the intellect waits for a reason to decide, the donkey is still hungry. Deliberation happens over time, and living things have to actually eat. A theory of choice that says "wait for sufficient reason," for an indeterminate stretch, assumes an animal that can afford the wait. So does any other decision process that lets you burn weeks at a time hoping the data will tip on its own.<br>The donkey's problem is a constraint that holds for arbiters, circuits, and in fact any system forced to convert a gradient of reasons into a binary act. Even a perfectly rational decider, handed perfectly balanced inputs, has no guarantee of choosing in time. The tie isn't always breakable on demand. The computer scientist Leslie Lamport argued that "a discrete decision based upon input having a continuous range of values cannot be made within a bounded length of time," and that this "appears to be a fundamental law of nature." He called it Buridan's Principle.<br>Well, I'm sorry to tell you, but the donkey is back.<br>He's sitting at your desk, in front of a chat window, asking an AI to help him decide between two product decisions, and he's getting nowhere.<br>The donkey is, in fact, you. Before you clutch your pearls or retreat to a safe space, rest assured, he's me too. He's every one of us, caught in the recursive loop of AI iteration and feedback, gradually receding into AI indecision.<br>Let me illustrate. You have to decide whether to sunset a product line that three people depend on, or pour money into it for two more quarters. It's a captain's call, and a hard one. So you open a chat and lay it out. The model gives you a clean, fair breakdown: the case for sunsetting, the case for keeping it, and the risks on each side.<br>Useful, surely?<br>Helpful, surely?<br>You then ask it to weigh the factors. And it does, with hedges about how only you know your values. You ask it to assume your values. It asks clarifying questions. You answer them. It generates a recommendation, then notes that the recommendation depends on assumptions you might want to revisit. So, with its help, you revisit them, and the loop begins again. An hour passes, two hours, three days, three weeks of talking and weighing and feeding back again and again, and somehow you've still not actually decided anything. You've only refined the shape of your indecision.<br>The models mirror human uncertainty with endless patience. The only thing standing between you and an unbreakable loop is your willingness to keep asking, keep prompting, keep pasting.<br>Ask a language model whether to take Path A or Path B and it won't refuse the request entirely. It'll lay out the considerations on each side, and if you're using a more recent model it may push back with a hint of firmness. But ask again, and keep asking, and it'll offer a balance and then immediately surface the conditions under which the recommendation would flip. The model is doing what it was trained to do: give you an analysis and respect your autonomy, while avoiding the confident pronouncement that might mislead you. You came to the model wanting to be pushed, wanting someone or something to break the tie, and you got an oracle that hands the tie-breaking back to you with every prompt.<br>Decision paralysis predates AI by, conservatively, all of human history. The Stoics worried about it, and so did the medieval scholastics. Thinking and rethinking so thoroughly colonized action in Hamlet that no amount of further thinking could break the loop, with every reflection generating new reasons for more reflection, leading to the famous lines: "Thus conscience does make cowards of us all, and thus the native hue of resolution is sicklied o'er with the pale cast of thought."<br>William James, in his 1890 Principles of Psychology, described how deliberation can become its own pathology, a condition he touched on in his discussion...