Devdiscourse

Big data fraud detection faces a reckoning over AI transparency

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...
Morningstar

Axoniq Launches First Unified Platform to Bring Explainability to Enterprise AI

New Platform Preserves Contextual History of Every Business Decision, Closing the Trust Gap for AI in Complex and Regulated Industries AUSTIN, Texas, and UTRECHT, Netherlands, Oct. 30, 2025 ...
Harvard Business School

Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability

Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information ...
Harvard Business School

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems ...
Institutional Investor

We Will Never Fully Understand How AI Works — But That Shouldn’t Stop You From Using It

The search for alpha can take us to some unusual places — perhaps none more so than the 13th century works of Thomas Aquinas. His philosophical maxim, “Finitum non capax infiniti” — “The finite cannot ...
Outlookindia

Crucial Role Of Explainability In AI Evolution - AI Leader Perspective

In the fast-paced world of Artificial Intelligence (AI), where algorithms drive everything from personalized recommendations to autonomous vehicles, the demand for transparency and accountability has ...