The European Union has launched a comprehensive plan to establish itself as a global leader in artificial intelligence, aiming to enhance its technological independence and competitiveness against the US and China. The initiative includes two strategies: “Apply AI” to accelerate AI adoption in key industries and “AI in Science” to bolster research capabilities.
Artificial intelligence (AI) is increasingly being used in human resources (HR) for tasks such as drafting job descriptions and conducting interviews, but it also brings significant legal risks, including discrimination claims and privacy issues. Employers must ensure compliance and human oversight to mitigate these risks while benefiting from the efficiency that AI offers.
On September 25, the United Nations launched the Global Dialogue on AI Governance, aiming to provide a platform for discussions on the safe development of AI systems and addressing capacity gaps in developing countries. However, the initiative faces opposition, particularly from the United States, which rejects multilateral governance efforts, raising questions about the future effectiveness of the dialogue.
At the 80th session of the United Nations General Assembly, two new initiatives were launched: the Global Dialogue on AI Governance and the Independent International Scientific Panel on AI, both aimed at addressing critical issues surrounding AI. This ambitious governance framework seeks to promote international cooperation and informed policymaking, but challenges remain regarding enforcement, funding, and achieving equitable outcomes.
This article clarifies the differences between AI governance and information security (InfoSec), emphasizing the need for both a secure framework and responsible operational guidelines in AI initiatives. It highlights the importance of integrating AI governance with InfoSec to manage risks effectively, ensuring that AI systems are not only secure but also ethical and compliant.
In an insightful interview with Greg Hutchins of Quality Plus Engineering, the discussion focused on the emerging importance of AI governance and risk management frameworks, particularly the NIST AI RMF and ISO 42001. Hutchins emphasizes that establishing standards for AI is crucial for building trust and ensuring the safety and reliability of AI systems as they become increasingly integrated into business operations.
Health systems and startups are facing challenges in governance and regulatory compliance as they adopt new AI tools, with many lacking the infrastructure to monitor machine learning models effectively. Recent discussions highlighted the need for standardized practices and the importance of building internal capabilities for quality control in AI applications within healthcare organizations.
A recent EY survey reveals that companies implementing advanced Responsible AI measures experience significant improvements in innovation, efficiency, and revenue growth. However, nearly all organizations face financial losses due to AI-related risks, highlighting the urgent need for effective governance and controls in AI deployment.
In the AI era, effective business governance is crucial for safeguarding trust by ensuring integrity, accountability, transparency, and resilience. Boards must converge AI transformation with cybersecurity practices, fostering collaboration from the start to enhance innovation and mitigate risks.
Unchecked AI integration in governance poses significant threats to human rights, accountability, and democratic principles, potentially leading to state overreach. Without strong public opposition and regulation, we may face a dystopian future where AI-driven decisions undermine individual liberties and justice.