Hello, fellow humans! Today, we’re looking at three stories that cover three major areas of AI influence: how we think, how we speak, and what we do in the workplace. It’s a tectonic shift, but the more we understand, the more we can adapt.

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Stave Nadis writes for Quanta Magazine, and republished in Wired, that an LLM has achieved “metalinguistic” abilities.

The conventional wisdom was summed up by Noam Chomsky in 2023 in the New York Times “The correct explanations of language are complicated and cannot be learned just by marinating in big data.”

Going forward, we’re going to define our relationship to AI based on our human capacities and AI’s complementary capabilities and limits. Tom McCoy, a computational linguist at Yale says, “As society becomes more dependent on this technology, it’s increasingly important to understand where it can succeed and where it can fail.”

Human languages have a lot of inherent ambiguity that we are able to decode because we have cultural context cues, background information, and mental models of both language and the world that AI does not and (theoretically) cannot possess.

The team of researchers created 30 “mini-languages,” each with 40 made-up words. Even though there was no way that these words could have been in the training data, the model was able to generate a robust model for phonetics and pronunciation in each of these languages. Something that surprised the researchers.

But if you consider that LLMs are next-token predictors, predicting something like phonetics does make a certain amount of sense. Nonetheless, this research still forces us to reconsider what our cognitive processes are that we call human, alongside the emergent capabilities of AI models.

Research is revealing significant psychological effects of AI adoption, including changes in cognitive patterns, attention spans, and decision-making processes. Marlynn Wei MD reports in Psychology Today that some use patterns can weaken our cognitive abilities and others can strengthen them.

Typical work patterns that can weaken our cognition are:

On the other hand, to enhance critical thinking skills, you can use AI

Studies show that AI collaboration can boost work performance significantly, but also raises concerns about AI-associated psychosis, depersonalization, and the risk of over-dependence. The field is exploring how AI shapes human cognition and the importance of maintaining human agency in AI-augmented environments.

Fast Company reports that employees are handing the reins to AI more than ever, with full task automation up 8% while augmentation is declining. Even though studies show that AI is most effective when used as an augmentation tool, an analysis of changing workforce dynamics shows a shift from AI augmentation to automation as a cost driver, downplaying the importance of human oversight.

This has strategic implications for HR and workforce planning in AI-driven business environments.

As companies fundamentally restructure their operations around AI-native architectures, they are moving beyond adding AI features to designing AI-first products and workflows. This transformation means leaner, faster organizational models infused with AI at every layer, requiring new governance structures and leadership approaches. In other words, new human decision-making and management strategies. Some organizations are reporting real productivity gains, with workers saving two hours per day through AI that can then (theoretically) be reinvested into creativity and strategy.