Sarah Matthews

The increasing adoption of AI technologies demands a fundamental shift in how organizations approach system design and implementation. Traditional software development methodologies fail to address the unique challenges posed by AI systems, particularly regarding human-centered design considerations and ethical risk management. Organizations that prioritize robust user research and thoughtful design phases consistently achieve stronger ROI on their AI investments.

·       Integrating comprehensive user research before technical development begins

·       Implementing continuous risk assessment frameworks adapted for AI-specific challenges

·       Establishing cross-functional teams bridging technical expertise with design thinking

Join this interactive deep-dive workshop to develop practical frameworks for adapting your organization's AI development lifecycle. You'll leave with actionable strategies to rebalance project resources toward human-centric design principles, risk identification methodologies, and oversight mechanisms that extend beyond conventional software development approaches.

AI’s increasing role in workplace decisions, from hiring to performance management, raises important ethical concerns. This session will explore the ethical implications of AI-driven decisions, focusing on transparency, fairness, and accountability. We will address the role of governance in ensuring AI systems are used responsibly and in ways that uphold organizational values and employee rights.

·       Examining the ethical impact of AI-assisted decisions on the workforce.

·       Discussing strategies for ensuring fairness, transparency, and accountability in AI algorithms.

·       Managing the ethical challenges of algorithmic management in the workplace.