In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, a senior research scientist in human-machine interaction, and Jonathan Spring, a senior vulnerability researcher, discuss the hidden sources of bias in artificial intelligence (AI) systems and how systems developers can raise their awareness of bias, mitigate consequences, and reduce risks.
Why Software Architects Must Be Involved in the Earliest Systems Engineering Activities
Selecting Metrics for Software Assurance
AI in Humanitarian Assistance and Disaster Response
The AADL Error Library: 4 Families of Systems Errors
Women in Software and Cybersecurity: Suzanne Miller
Privacy in the Blockchain Era
Cyber Intelligence: Best Practices and Biggest Challenges
Assessing Cybersecurity Training
DevOps in Highly Regulated Environments
Women in Software and Cybersecurity: Dr. Ipek Ozkaya
The Role of the Software Factory in Acquisition and Sustainment
Defending Your Organization Against Business Email Compromise
My Story in Computing with Dr. Eliezer Kanal
Women in Software and Cybersecurity: Eileen Wrubel
Managing Technical Debt: A Focus on Automation, Design, and Architecture
Women in Software and Cybersecurity: Grace Lewis
Women in Software and Cybersecurity: Bobbie Stempfley
Women in Software and Cybersecurity: Dr. Lorrie Cranor
Leading in the Age of Artificial Intelligence
Applying Best Practices in Network Traffic Analysis
Create your
podcast in
minutes
It is Free