trustinai

The ability of artificial intelligence (AI) to partner with the software engineer, doctor, or warfighter depends on whether these end users trust the AI system to partner effectively with them and deliver the outcome promised. To build appropriate levels of trust, expectations must be managed for what AI can realistically deliver. In this podcast from the SEI’s AI Division, Carol Smith, a senior research scientist specializing in human-machine interaction, joins design researchers Katherine-Marie Robinson and Alex Steiner, to discuss how to measure the trustworthiness of an AI system as well as questions that organizations should ask before determining if it wants to employ a new AI technology.

To ensure trust, artificial intelligence systems need to be built with fairness, accountability, and transparency at each step of the development cycle. In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, a senior research scientist in human machine interaction, and Dustin Updyke, a senior cybersecurity engineering in the SEI’s CERT Division, discuss the construction of trustworthy AI systems and factors influencing human trust of AI systems.