IBM's Kush Varshney explains the origins of the phrase 'AI governance' and how IBM is adapting its Trust 360 toolkits for the age of generative AI. This article answers a series of questions on AI governance.  

Link: AI governance explained 

Questions 

• How do the dangers posed by LLM-powered chatbots differ from traditional machine-learning models? 

• So, there’s no one-size-fits-all approach. What else makes safety guarantees with generative AI so hard? 

• How, then, do you know what controls to build into models? 

• What do you mean by governance? 

• At what point in the AI pipeline is governance added? 

• Governance is the final stage of fine-tuning? 

• So, interventions also happen during inferencing? 

• What governance capabilities has IBM Research added to watsonx? 

• Why is AI trust and safety so critical for enterprises? 

• Some have called for a halt on AI development. Do you think we have the power to control it?