Priya patelGeeta Gurnani, IBM Technology CTO, emphasizes the significance of AI governance for responsible innovation. She explains that as AI adoption accelerates, organizations need to establish robust governance mechanisms to build and use AI responsibly, gaining the trust of users. She highlights three key elements of AI governance: the provenance of data, transparency and explainability of AI models, and ensuring fairness and reducing bias.
Gurnani also discusses the challenges faced in implementing responsible AI, such as keeping up with changing regulations and lacking proper AI governance processes and tools. To address these challenges, IBM has released the watsonx.governance toolkit to help businesses direct, manage, and monitor their AI activities. The toolkit provides an integrated platform for AI governance at scale and prepares organizations for various AI regulations.
Gurnani emphasizes the need for global collaboration in building trust in AI. Corporations, governments, and industry bodies all have crucial roles to play in shaping an ecosystem for responsible AI. IBM has worked with governments to advance smart AI regulation that focuses on the riskiest uses of AI and has launched initiatives like the AI Alliance and the Center of Excellence for Generative AI to promote broader and ethical AI innovation.
In terms of global regulatory frameworks, Gurnani believes that smart AI regulation should provide guardrails for society while fostering innovation. Governments should prioritize risk-based regulation, liability over licensing, and support open-source AI innovation. Corporate accountability should also be encouraged to ensure that AI is explainable, transparent, and fair.
