Video produced by Steve Nathans-Kelly
In this clip from Data Summit 2026, Cal Al-Dhubaib, principal technologist at Rubrik, explores how data complexity and task complexity serve to increase uncertainty when working with AI systems and trusting the quality of the summaries they provide, the actionable code they generate, the biases they reproduce, and the resulting chaos they produce, and how these challenges multiply in the progression from generative to agentic AI.
“What we have with these AI systems is an explosion of edge cases,” Al-Dhubaib said. “Machine learning and AI systems are known to be vulnerable to very simple manipulations.”
These models are highly sensitive to biases and errors in ground truth data, he explained. Context can be undermined or manipulated as well.
“With large context the language model itself can’t disambiguate from conflicting sources of information,” Al-Dhubaib said.
The annual Data Summit conference returned to Boston, May 6-7, 2026, with pre-conference workshops on May 5.
Videos and clips of presentations from Data Summit 2026 are now available for on-demand viewing on the DBTA YouTube channel.
More information about Data Summit 2027 is coming soon.