Danielle Li

A new study by professors Pierre Azoulay, Danielle Li, and co-authors, has revealed the potential impacts a smaller National Institutes of Health (NIH) would have had on past drug development. If the NIH budget had been 40% smaller from 1980 to 2007 — the level of cuts that President Donald Trump has proposed for the agency — the science underlying numerous drugs approved in the 21st century would not have been funded, according to the analysis. "Cuts today are going to have effects starting 15 years from now, roughly, and then accelerating from there," Azoulay said.

Competence penalties against women who perform identically to men are most likely to arise when evaluators use highly subjective assessment criteria, like "potential." "The problem with evaluating potential is that it's poorly defined, which leaves a lot of room for interpretation," said professor Danielle Li. "The moment you veer off metrics, that's where people's stereotypes and perceptions now have room to exist."

Professor Danielle Li believes that more experienced workers are more likely to face hardships due to AI. AI's democratizing of specialized skill may make it easier for companies to lay off or stop hiring workers who've spent their careers specializing. "That state of the world is not good for experienced workers," she said. "You're being paid for the rarity of your skill, and what happens is that AI allows the skill to live outside of people."

Professor Danielle Li said there were scenarios in which A.I. could undermine higher-skilled workers more than entry-level workers. For instance, you may no longer have to be an engineer to code, or a lawyer to write a legal brief. "That state of the world is not good for experienced workers," she said. "You're being paid for the rarity of your skill, and what happens is that A.I. allows the skill to live outside of people."