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AI Act 101: What your board needs to know
The EU AI Act makes boards accountable for AI risk. Here’s what leaders need to know — and a 30-day plan that builds trust with regulators & investors.
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AI in Hiring Under the EU AI Act: Compliance Risks and Bias Gaps in 2025
Executive Summary Artificial intelligence (AI) is rapidly transforming recruitment and human resources (HR) practices across Europe and globally. Tools such as applicant tracking systems, resume screeners, chatbots, and video interview platforms are now integrated into hiring pipelines that previously relied on human judgment alone. While these systems promise efficiency, they also introduce new risks…
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FairByDesign research subscription terms
FairByDesign Research Subscription Terms Effective: September 2025 Introduction FairByDesign provides research papers, governance crosswalks, and templates designed to support compliance, audit, and governance teams. This document outlines the terms for accessing and using FairByDesign’s research subscription service. These terms apply to both annual and lifetime subscription options. Scope of Use Subscribers are granted a…
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License use
FairByDesign Research Subscription — License & Scope(v1.0, 2025) The Mercury Intelligence & Evidence Library provides organizations with access to whitepapers, crosswalks, and toolkits for AI governance. This document defines the scope of use and licensing terms for subscribers. 1. License Model License Type: Organization-wide. Permitted Users: All employees and contractors working on behalf of…
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Hitl-sop
Human-in-the-Loop & Escalation SOP FairByDesign | 2025 Introduction Human oversight is a cornerstone of responsible AI deployment. No AI system should operate without defined escalation pathways that allow humans to intervene in real time. This Standard Operating Procedure (SOP) describes how human-in-the-loop (HITL) oversight is designed, tested, and maintained for AI agents. The EU…
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Logging-Retention
Logging & Retention Policy FairByDesign | 2025 Introduction Effective logging and retention practices are critical for ensuring AI systems are transparent, auditable, and compliant with regulatory expectations. Logs provide the evidence needed to demonstrate accountability, while retention policies ensure that data is stored only as long as necessary and deleted when no longer required.…
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Model Card template
Model Card & Change Log Template FairByDesign | 2025 Introduction Model cards and change logs provide transparency into how AI systems are designed, deployed, and updated. A model card describes the system’s purpose, data, and performance, while the change log tracks updates over time. Together, these artifacts demonstrate lifecycle accountability, which is emphasized in…
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Evidence Journal Template
Evidence Journal Template FairByDesign | 2025 Introduction An evidence journal provides a structured way to record findings during AI audits. It captures what was tested, what evidence was observed, and whether the result met expectations. Maintaining such a journal demonstrates defensible governance and supports repeatable audit cycles (NIST, 2023; ISO, 2023). How to Use…
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Bias & Safety Testing Method-Client Handout
Bias & Safety Testing Method FairByDesign | 2025 Introduction Bias and safety testing ensures that AI systems perform consistently across diverse user groups and avoid harmful or misleading outputs. The EU AI Act, GDPR, and NIST AI RMF all stress the importance of testing for fairness, safety, and accountability in AI systems (European Union,…
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Hosting and Assurance
Hosting & Assurance Overview FairByDesign | 2025 Introduction Assurance is not only about controls inside an AI system but also about where and how the system is hosted. This document outlines FairByDesign’s approach to hosting assurance, explaining the safeguards applied to third-party providers, the data protection commitments in place, and what clients can expect…