Day: April 6, 2025

AI Ethics Auditing: From Regulatory Push to Building Trustworthy AI

AI systems are increasingly scrutinized for bias and unintended consequences, leading to the rise of AI ethics auditing. This emerging practice aims to evaluate these systems, driven primarily by expected regulations and the need to maintain a positive public image. Though still developing, these audits face challenges including regulatory ambiguity, difficulties in coordinating various expertise, and limited resources. Ultimately, they aim to ensure AI aligns with ethical principles, minimizing potential harm and fostering responsible AI innovation.

April 6, 2025

AI Risk Mitigation: Principles, Lifecycle Strategies, and the Openness Imperative

Artificial intelligence presents both opportunities and challenges, demanding responsible development through identification and mitigation of potential risks. Effective risk mitigation requires adaptable, balanced, and collaborative approaches, incorporating shared responsibility among stakeholders and continuous oversight. This necessitates strategies throughout the AI lifecycle, from data collection to ongoing monitoring, while accounting for the degree of openness in AI models. Addressing upstream and downstream risks with tailored policy and technical interventions is critical for maximizing benefits and minimizing harms.

April 6, 2025