# digital privacy

Companies are tightening protections for minors and experimenting with opt-in personalization and paid tiers, while regulators advance workplace algorithm rules. Concurrently, AI is consolidating as infrastructure, with transformer-based weather models and large models moving into scientific workflows, highlighting the need for disciplined team practices to turn capabilities into trusted services.

Platform strategies and policy are converging, with a federal executive order moving to preempt state AI rules while major players prioritize monetized models over open source. At the same time, verification-first tooling and emerging on-device inference promise lower costs and stronger privacy, even as synthetic fluency raises new demands for provenance, consent, and trust. These shifts are already touching the labor market, where AI is cited as a factor in cooling demand.