Elon Musk’s Grok chatbot has sparked controversy after generating non-consensual images, including sexualized depictions of minors. Riana Pfefferkorn discusses the implications of this incident and the need for stronger regulatory measures to prevent abuses in generative AI.
Join our expert panel from Gibson Dunn for a recorded webcast analyzing President Trump’s executive order designed to enhance U.S. leadership in Artificial Intelligence by addressing state AI laws and regulations. Gain insights into regulatory strategies and implications for companies.
Over 70% of IT leaders worry about regulatory compliance when implementing generative AI, facing a complex regulatory environment with conflicting laws and rising legal risks that demand robust governance.
The trucking industry faces increasing compliance challenges due to stricter federal regulations. AI offers a transformative solution by streamlining onboarding, verifying driver qualifications in real time, and providing transparent audit trails to turn compliance from a bottleneck into a competitive advantage.
Agentic AI is transforming business operations by automating workflows and enabling autonomous decisions. However, it brings new security and governance challenges. Organizations must implement robust frameworks, including governance structures and human oversight, to manage these risks effectively.
The emergence of the AI Compliance Officer marks a crucial evolution in corporate governance, ensuring ethical, transparent, and compliant AI deployment. Compliance professionals are positioned to lead this integration of innovation with regulatory oversight to build trustworthy AI systems.
The AI Act uses a risk-based approach to regulate AI systems, with stricter obligations for higher-risk applications. European harmonized standards are being developed to implement these obligations, focusing on risk management, quality assurance, and maintaining AI system trustworthiness throughout their lifecycle.
Artificial intelligence (AI) plays a crucial role across various sectors but can reproduce or amplify existing biases, threatening fairness and user trust. This article explores different types of AI biases, their consequences, and best practices for identifying and mitigating them responsibly.
AI systems, while transformative, can perpetuate or create biases that undermine fairness and trust. This article explores the types, consequences, and best practices for identifying and mitigating AI biases to ensure responsible governance.
As AI technology advances, global regulators are intensifying efforts to ensure responsible development through frameworks like the EU’s Artificial Intelligence Act. Companies face complex compliance landscapes across regions, needing to balance transparency, innovation, and adaptability to stay competitive.