AI

“Can machines be therapists?” is a question receiving increased attention given the relative ease of working with generative artificial intelligence. Although recent (and decades-old) research has found that humans struggle to tell the difference between responses from machines and humans, recent findings suggest that artificial intelligence can... See more

Agrawal et al. argue that the framing of AI automation versus augmentation is wrong. Rather than being distinct they are often one and the same. They say that AI, initially intended for automating tasks, inadvertently acts as a force for augmentation of the broader workforce. For example, automating diagnostic skills in healthcare could diminish... See more

The community remains puzzled about whether these models genuinely generalize to unseen tasks, or seemingly succeed by memorizing the training data. This paper makes important strides in addressing this question. It constructs a suite of carefully designed counterfactual evaluations, providing fresh insights into the capabilities of... See more

In other words, rather than trying to please humans, Scientist AI could be designed to prioritize honesty.

Quanta interviewed 19 current and former NLP researchers to tell that story. From experts to students, tenured academics to startup founders, they describe a series of moments — dawning realizations, elated encounters and at least one “existential crisis” — that changed their world. And ours.

The web is no longer primarily human-generated text created for human readers; it is increasingly AI-generated text created for algorithmic amplification, mixed with human-generated text optimized for the same algorithmic reward functions.

As AI systems train on this degraded corpus, they learn to reproduce its characteristics—shallow reasoning,... See more

Cut the bullshit: why GenAI systems are neither collaborators nor tutors