Insights & perspectives

The new generation of language models is actively trained away from agreement. Anthropic's Claude Fable 5, relaunched in July 2026, is the clearest example so far:

Every organization recognizes three layers of infrastructure it has to build and maintain. The physical layer of buildings, machines, and power. The IT layer of networks, servers, and systems. The data layer of records, pipelines, and governance. Each has an owner, a budget, a depreciation schedule, and someone accountable when it fails.

We track every new model release. We benchmark, compare, implement. An entire industry is built around measuring what AI can do. The question I have followed is a different one: what happens to our own capacity in the process? I have worked with behavioral data in digital environments for nearly two decades. Since language models entered the market, I have continuously tracked how this new layer affects what we already knew about algorithmic flows, concentration, and interpretive ability.

The concept of cognitive impairment has traditionally described medical conditions such as dementia and MCI. Recent research points to a different form of cognitive decline that does not stem from neurological disease but from our dependence on digital tools and AI systems.

We build systems to help us think, but in the same process, those systems change how we think. AI is no exception. What begins as support for analysis and decision-making can, over time, become a steering factor—not because the technology takes over, but because our own frames of reference gradually shift.