FideAI

Research

Research for trustworthy AI.

Fide AI studies AI systems through the lens of making them more trustworthy. We research whether systems use evidence well, remain within legitimate authority, preserve human control, and stay accountable while they act.

This research develops and validates the methods independent assurance depends on. We publish evidence and public-good artifacts that others can inspect, challenge, and use in their own work.

What trust demands

No single discipline can make AI trustworthy.

AI systems cannot become trustworthy through capability testing alone. Trust also depends on how systems use evidence, exercise authority, affect human judgment, operate within institutions, and behave in consequential settings.

These questions cross technical, social, moral, and institutional disciplines. Our research agenda maps their connections and turns them into concrete calls for research. Some will be pursued by Fide AI. Others are invitations for researchers, labs, institutions, and domain experts to take forward.

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Connected research areas

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Public calls for research

Open

A research commons built for contribution

Research areas

The questions receiving focused attention.

Explore the full research agenda →

Published research

Evidence from our first high-trust domain.

Our released studies currently focus on faith-facing systems. Each page states the question, method, result, artifacts, and limits so readers can inspect the evidence directly.

Emerging research direction

Independent research on AI behavior and cybersecurity risk.

Fide AI aims to conduct rigorous, independent research on how advanced AI systems behave in cybersecurity settings. We seek to investigate how agents use their capabilities, cross authority boundaries, respond to oversight, and create risks that become visible only when the complete system is examined.

Our perspective emphasizes legitimate authority, evidence integrity, human agency, and accountability. We make the assumptions behind our research explicit so others can examine both the methods and the conclusions.

Cybersecurity is an emerging research direction for Fide AI. We are building on our published work in source fidelity and system behavior, and seeking security researchers and partners to develop and test methods in this domain.

Interpretation limits

A result describes behavior under named versions, prompts, conditions, rubrics, and evaluation procedures. It does not establish general safety, product approval, or deployment readiness beyond the tested scope. Faith-domain studies also do not confer theological or pastoral authority.