In the expanding landscape of AI integration, conducting AI-specific due diligence is crucial for corporate transactions involving AI technology. Traditional diligence methods often miss AI-unique risks like opaque model origins and insufficient monitoring, requiring a dedicated approach to evaluate liabilities and ensure smooth integration.
President Tharman Shanmugaratnam highlights Singapore’s structural readiness to face the rapid impact of artificial intelligence (AI), emphasizing global governance and cooperation to harness AI’s benefits while managing its risks.
This study proposes a quantitative ethical decision-making model integrating military ethics principles and international legal norms, addressing AI’s increasing autonomy in combat systems. It highlights the need to redefine human pilots’ roles within AI-integrated operations for improved accountability and ethical compliance.
Researchers are increasingly alarmed by the safety challenges posed by low-compute AI models, which now enable malicious actors to conduct sophisticated digital harm campaigns using consumer-grade hardware. Their findings reveal a troubling trend where smaller models rapidly approach the performance levels of larger systems, exposing critical gaps in current AI governance strategies.
Omnea is enhancing its procurement platform in the US through a partnership with MongoDB to improve governance and third-party risk controls amid rising AI adoption. This collaboration highlights the growing importance of structured procurement and compliance tools for AI-related services in the technology sector.
As AI becomes central to boards seeking shareholder value, a gap emerges between ambitions and operational realities. Effective governance requires reframing AI as a comprehensive investment portfolio that links initiatives to financial outcomes while addressing risks and strategic impacts.
Crypto platforms typically fail not because of faulty code, but when users rush to withdraw funds, overwhelming infrastructure. Bryan Benson explores how AI-driven trading, liquidity crises, and governance challenges add complexity to crypto market dynamics.
The rise of shadow AI presents significant risks to organizational security, with nearly 90% of employees using AI tools without informing IT departments. Leaders must shift from restrictive policies to a governance framework that enables safe, transparent AI adoption and turns risks into competitive advantages.
Experts advocate for licensing medical Generative AI (GenAI) models similarly to healthcare professionals to ensure a regulatory framework that balances innovation, accountability, and oversight in clinical AI.
Fujitsu’s Dippu Singh highlights the limitations of checklist governance in AI compliance, emphasizing that the EU AI Act demands observable engineering realities rather than paperwork. He advocates for a shift to “Ethics by Design” to address dynamic AI risks and ensure effective compliance.
