The Center for Humane Technology set out seven principles for AI that serves humanity. This tracker maps, week by week, how reality has drifted — across norms, laws, and product design.
Codebook v0.1 · 69 indicators · published Apr 2026. Open corpus under CC-BY 4.0.
Seven CHT principles × three domains of change. Each cell shows direction over the selected window.
Coded events moving the matrix. Each one is tagged to an indicator, checked for triangulation, and weighted by magnitude.
The Electronic Frontier Foundation (EFF) published a critique of Palantir's human rights policy, arguing that the company's continued provision of surveillance tools to ICE contradicts its stated commitments.
A new academic paper analyzes AI-enabled female sex robots, arguing their design perpetuates male-centric bias and epistemic injustice, and proposes feminist design directions for equitable human-robot interaction.
Researchers introduced FairLogue, a new toolkit for intersectional fairness auditing, and demonstrated its use by evaluating disparities in clinical machine learning models.
A new study reveals that LLMs used by federal agencies to summarize public comments exhibit bias based on the commenter's occupation.
Researchers published an algorithmic audit of TikTok, revealing that the platform's personalization algorithm ranks comments differently based on users' political leanings.
Everyone feels the drift. Nobody has a single picture of it. This tracker is that picture — grounded in the Center for Humane Technology's seven principles, coded against a public codebook, checked by triangulation before it moves the board.
An LLM tags each event to an indicator, direction, and magnitude. A human confirms edge cases and writes one deep process-tracing analysis per cycle. Cells with fewer than two signals stay blank — absence of motion is its own signal.
Principles, indicators, signals, and the rubric are public under CC-BY 4.0 at github.com/DavidHITL/hitl-tracker-corpus. Spotted a wrong tag, a dead link, or a missing event? Email david@tenone.eu — corrections land in the next refresh.