Data Governance

As the AI revolution unfolds, concerns surrounding data governance and the concentration of information become increasingly pertinent. The widespread adoption of AI technologies may inadvertently centralize control over data in the hands of a few private entities, such as AI research labs, unless proper regulations are in place.

This centralization of information raises questions about the potential biases embedded within AI systems. By their very nature, AI models can inadvertently reproduce and perpetuate existing biases, and they may be susceptible to arbitrary adjustments during the training process. These issues have been highlighted in numerous research papers, including "Fairness and Abstraction in Sociotechnical Systems (opens in a new tab)" (2019), which explores the challenges of addressing biases in AI development

As the world becomes increasingly reliant on AI, ensuring robust data governance and addressing potential biases are essential to create a fair and equitable digital landscape. Policymakers and industry stakeholders must work together to establish comprehensive regulatory frameworks that prevent undue concentration of power and promote fairness in AI applications.