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many quit in search of better work opportunities, self employment, or, simply, higher pay.

The recent trend towards higher pay exists in the context of decades of low-wage growth, as until recently, wages in the US had stagnated.

The current competitiveness of the labor market – at least the proportion that is driven by gap between the high demand for workers and the supply of those searching for work – might be temporary.

in September and October of this year, there were 1.4 million fewer mothers actively engaged with the labor force than those same months in 2019.

Mothers with college degrees and telework-compatible jobs were more likely to exit the labor force and more likely to be on leave than women without children. She also found that teachers are most likely to leave the labor force as compared to their counterparts in other industries.

Salman said he could imagine a future where companies, even the ones who generate the AI models, could certify that uploaded images are immunized against AI models. Of course, that isn’t much good news for the millions of images already uploaded to the open source library like LAION, but it could potentially make a difference for any image uploaded in the future.

there are some AI systems that can detect deepfake videos, and there are ways to train people to detect the small inconsistencies that show a video is being faked. The question is: will there come a time when neither human nor machine can discern if a photo or video has been manipulated?

Back in September, OpenAI announced users could once again upload human faces to their system, but claimed they had built in ways to stop users from showing faces in violent or sexual contexts. It also asked users not to upload images of people without their consent

Noah asked Murati if there was a way to make sure AI programs don’t lead us to a world “where nothing is real, and everything that’s real, isn’t?”

The theories that make sense when you have huge amounts of data look quite different from those that make sense when you have small amounts

The bigger the dataset, the more inconsistencies the AI learns. The end result is not a theory in the traditional sense of a precise claim about how people make decisions, but a set of claims that is subject to certain constraints.

theory-free predictive engines embodied by Facebook or AlphaFold.

“Explainable AI”, which addresses how to bridge the interpretability gap, has become a hot topic. But that gap is only set to widen and we might instead be faced with a trade-off: how much predictability are we willing to give up for interpretability?