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.
Mission-Based Prioritization: A New Method for Prioritizing Agile Backlogs
My Story in Computing with Carol Smith
Digital Engineering and DevSecOps
A 10-Step Framework for Managing Risk
7 Steps to Engineer Security into Ongoing and Future Container Adoption Efforts
Ransomware: Evolution, Rise, and Response
VINCE: A Software Vulnerability Coordination Platform
Work From Home: Threats, Vulnerabilities, and Strategies for Protecting Your Network
An Introduction to CMMC Assessment Guides
The CMMC Level 3 Assessment Guide: A Closer Look
The CMMC Level 1 Assessment Guide: A Closer Look
Achieving Continuous Authority to Operate (ATO)
Challenging the Myth of the 10x Programmer
A Stakeholder-Specific Approach to Vulnerability Management
Optimizing Process Maturity in CMMC Level 5
Reviewing and Measuring Activities for Effectiveness in CMMC Level 4
Situational Awareness for Cybersecurity: Beyond the Network
Quantum Computing: The Quantum Advantage
CMMC Scoring 101
Developing an Effective CMMC Policy
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