Jakub Szarmach

AI Governance Controls Mega-map (Feb 2025)

MIT AI Risk Analysis Framework (AI-RAF)

AI Vendor Security and Safety Assessment Guide

A Taxonomy of Trustworthiness for Artificial Intelligence

AI Liability Along the Value Chain

From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

Governance in the Age of Generative AI: A 360º Approach for Resilient Policy and Regulation

A Legal Framework for eXplainable Artificial Intelligence

NIST: Reducing Risks Posed by Synthetic Content An Overview of Technical Approaches to Digital Content Transparency

METHODOLOGY FOR THE RISK AND IMPACT ASSESSMENT OF ARTIFICIAL INTELLIGENCE SYSTEMS FROM THE POINT OF VIEW OF HUMAN RIGHTS, DEMOCRACY AND THE RULE OF LAW (HUDERIA METHODOLOGY)

Professionalizing Organizational AI Governance Report

Competences and governance practices for artificial intelligence in the public sector

Generative AI Governance Framework

Applying Data Protection Principles to Generative AI: Practical Approaches for Organizations and Regulators

Standards as a Basis for the Global Governance of Al in Research

Roles and Responsibilities Framework for Artificial Intelligence in Critical Infrastructure

Ethics in Action: From White Paper to Workplace

The Anatomy of AI Rules A systematic comparative analysis of AI rules across the globe

EU AI Act Compliance Matrix

Harmonised Standards for the European AI Act

Global Trends in AI Governance Evolving Country Approaches

Navigating AI Compliance Part 1: TRACING FAILURE PATTERNS IN HISTORY

FRAMEWORK TO ADVANCE AI GOVERNANCE AND RISK MANAGEMENT IN NATIONAL SECURITY

Generative AI and the Nature of Work