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.
Three Variations on the V Model for System and Software Testing
Adapting the PSP to Incorporate Verified Design by Contract
Comparing IT Risk Assessment and Analysis Methods
AADL and Aerospace
Assuring Open Source Software
Security Pattern Assurance through Roundtrip Engineering
The Electricity Subsector Cybersecurity Capability Maturity Model (ES-C2M2)
Applying Agile in the DoD: Fifth Principle
Software Assurance Cases
Raising the Bar - Mainstreaming CERT C Secure Coding Rules
AADL and Télécom Paris Tech
From Process to Performance-Based Improvement
An Approach to Managing the Software Engineering Challenges of Big Data
Using the Cyber Resilience Review to Help Critical Infrastructures Better Manage Operational Resilience
Situational Awareness Mashups
Applying Agile in the DoD: Fourth Principle
Architecting Systems of the Future
Acquisition Archetypes
Human-in-the-Loop Autonomy
Mobile Applications for Emergency Managers
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