Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Risk Insights: Yusuf Moolla
27 episodes
7 months ago
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
All content for Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing is the property of Risk Insights: Yusuf Moolla and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
Guest 2. Patrick Sullivan: VP of Strategy and Innovation at A-LIGN
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
32 minutes
9 months ago
Guest 2. Patrick Sullivan: VP of Strategy and Innovation at A-LIGN
Navigating AI Governance and Compliance Patrick Sullivan is Vice President of Strategy and Innovation at A-LIGN and an expert in cybersecurity and AI compliance with over 25 years of experience. Patrick shares his career journey, discusses his passion for educating executives and directors on effective governance, and explains the critical role of management systems like ISO 42001 in AI compliance. We discuss the complexities of AI governance, risk assessment, and the importance of clear ...
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
