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Signal.

Product demo videos, releases and notes from the work — the latest from validant.ai, in order.

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EventsOpen to read

29 October 2026

You Cannot Audit What You Cannot Trace

A fairness verdict rests on data twice over: the data a model learned from and the data it was tested on. Notes from the Swiss Data Space Forum 2026 and the Swiss Data Alliance white paper on AI-ready data, on why data spaces and fully open models decide what an assessment can prove.

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ResearchOpen to read

5 October 2026

Controlling Agents Triples Their Value. Proving It Is What Makes It Count.

BCG surveyed 1,330 executives and found that companies which control their AI agents properly get about three times as much value from them. Only 5% have those controls in place, and every one of the six is checked by the company itself. A reading of the Applied AI Index 2026, the gap it leaves open, and why proof is what lets the tripled value count.

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28 September 2026

The Preemptive Assurance Paradox: Who Guards the AI Guardrails?

In one September week a lab asked to slow down, a president declared himself the only guardrail AI needs, and The Economist asked whether the arms race can be stopped. Notes from Trust Valley Days 2026 at EPFL on why the answer is not a pause or a sprint, but liability, outcomes and verification.

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ResearchOpen to read

10 August 2026

Precision Is Not Proof: The Trap in Every AI Fairness Verdict

A model that predicts perfectly stops insuring anyone; a verdict published without its detection limit invites you to assume the limit is zero. Two failures, one omission, and two borrowed words for keeping them apart.

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Swiss-style line drawing of Daniel Glinz smiling, in a light beige blazer and open-collar shirt with a conference lanyard, holding a certificate that reads Best Paper Award, The Architecture of Digital Trust, on a clean white ground.

ResearchOpen to read

24 July 2026

The Trust Problem Nobody Wants to Name

Everybody is spending on AI; almost nobody can say what they got back. A new paper, awarded the Best Paper Award at the IEEE Swiss Conference on Data Science and AI, names that gap and shows it is a trust problem wearing a technical costume: seven mechanisms, a four-layer architecture, an iceberg beneath it, and five design principles for closing it.

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Fine grey-blue technical drawing on warm paper of a single rack-mounted frontier-AI model unit gone dark, beside a large knife-blade breaker switch thrown to off and actuated by a sealed letter, with dashed data lines to small client terminals and a faint world map all cut by break-marks, one teal switch lever, a soft coral wash and a small human figure for scale.

ResearchOpen to read

14 June 2026

When a Model Becomes a Munition

A frontier AI model was switched off worldwide by a single government letter. Reading the June 2026 shutdown through the three-body picture of digital trust: how the kill switch stopped being a metaphor, why the most governable lab was governed least carefully of all, and what single-vendor, single-jurisdiction dependence now costs a board.

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ResearchOpen to read

11 June 2026

Agents Will Act for Us. Who Vouches for Them?

When agents start acting for us, trust moves from outputs to actors. Reading Michael Casey’s case for proof of control alongside our three-body picture of digital trust: where convenience quietly pulls authority toward a few global platforms, how validant.ai answers it, and a closed beta for scientific validation opening in Q3 2026.

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ResearchOpen to read

5 June 2026

Digital Trust Is an Orbit, Not a Pillar

Trust is not one more pillar to stack. It is the orbit three bodies trace together: the model, the person and the organisation. Why the three-body problem is the honest metaphor for trustworthy AI, and how to tell where you are in the orbit.

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30 May 2026

Two Views of One Decision: Trustworthy and Explainable AI in Practice at HSLU

Notes from a Lucerne specialists course on Trustworthy and Explainable AI, and what it confirms about the Validant.ai approach.

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Swiss-style technical line drawing of a single magnifying lens at the centre, identical lines fanning out from it to a row of small office buildings and a uniform crowd of figures, with one lone figure softly stained coral and set apart, in thin black lines on white.

StudiesOpen to read

27 May 2026

The Wrong Question, Asked at Scale

A landmark study of 4 million job applications shows how AI hiring tools hide their bias, why one rejection can become rejection everywhere, and why independent, position-level assessment is no longer optional.

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EventsOpen to read

26 May 2026

No System Has Ever Been Fair

What four breakout sessions, one fairness tool demo, and 50+ years of collective experience taught us about fairness in AI, at the Trustworthy AI Circle.

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