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.
More Targeted, Sophisticated Attacks: Where to Pay Attention
Is There Value in Identifying Software Security "Never Events?"
Cyber Security, Safety, and Ethics for the Net Generation
An Experience-Based Maturity Model for Software Security
Mainstreaming Secure Coding Practices
Security: A Key Enabler of Business Innovation
Better Incident Response Through Scenario Based Training
An Alternative to Risk Management for Information and Software Security
Tackling Tough Challenges: Insights from CERT’s Director Rich Pethia
Climate Change: Implications for Information Technology and Security
Using High Fidelity, Online Training to Stay Sharp
Integrating Security Incident Response and e-Discovery
Concrete Steps for Implementing an Information Security Program
Virtual Communities: Risks and Opportunities
Developing Secure Software: Universities as Supply Chain Partners
Security Risk Assessment Using OCTAVE Allegro
Getting to a Useful Set of Security Metrics
How to Start a Secure Software Development Program
Managing Risk to Critical Infrastructures at the National Level
Analyzing Internet Traffic for Better Cyber Situational Awareness
Create your
podcast in
minutes
It is Free