Two things that are notoriously slippery to pin down: fairness and democracy.
Fairness—what is it, really? To me, fairness is just another way of thinking about efficiency. To elaborate, we often define efficiency as the sum of everyone’s value or surplus. But maybe that’s too simplistic. What if fairness is just a more complex version of that same idea? Instead of a straightforward sum, fairness might be a more intricate mapping of each participant’s value into the final outcome. In the end, achieving fairness feels a lot like maximizing some kind of welfare function—it’s just a matter of balancing competing interests and getting the best overall result.
Democracy, this one’s tricky. I remember every time we tried to define democracy in my law class, the room would fall into dead silence. But in recent years, modern theoretical computer science—particularly its intersection with Algorithmic Game Theory (AGT)—offers some new angles to think about democracy. And before anyone gets all classical on me, let me quote something from OpenAI (yes, I know, democracy was born in Athens…)
By ‘democratic process,’ we mean a process in which a broadly representative group of people exchange opinions, engage in deliberative discussions, and ultimately decide on an outcome via a transparent decision-making process.
—Democratic Inputs to AI, OpenAI