Our paper explores the role of intentional friction in Human-AI interactions, challenging the prevailing notion that frictionless experiences are inherently superior. Grounded in three theoretical frameworks—Media Richness, Situation Awareness, and Split-Attention theories—we investigated how introducing friction impacts user perceptions and decision-making when interacting with a Generative AI Assistant.

I served as the leader in developing ServiceNow’s long track record of unlocking AI's value to reduce complexity and make the world work better for everyone. Looking to the future, we envision a seamless integration of AI across our products, with tools that not only streamline the creation, configuration, and monitoring of AI services but also democratize AI utility, making it accessible regardless of expertise in data science.

This white paper analyzes the lessons learned and the insights gained that can guide us toward a future where we mitigate the risks while maximizing the opportunities for innovation, equity, and shared understanding.

This White Paper discusses the human impact and transformative potential of generative AI and ChatGPT, likening the increased accessibility of AI tools to breaking "the fourth wall" between creators and audiences. It explores how this technology is dismantling traditional barriers and prompting new inquiries.

Presented at EMNLP.
This paper introduces Azimuth, an open-source, user-friendly tool designed for error analysis in text classification.