Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Risk Insights: Yusuf MoollaInsights for financial services leaders who want to enhance fairness and accuracy in their use of data, algorithms, and AI.
Each episode explores challenges and solutions related to algorithmic integrity, including discussions on navigating independent audits.
The goal of this podcast is to give leaders the knowledge they need to ensure their data practices benefit customers and other stakehol... more
| Publishes | Daily | Episodes | 33 | Founded | 2 years ago |
|---|---|---|---|---|---|
| Categories | BusinessManagement | ||||
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Latest Episodes
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Technical stakeholders need detailed explanations.
• Non-technical stakeholders need plain language.
• Visuals, layering, literacy, and feedback are among the techniques we can use.
To s... more
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Algorithmic systems create challenges in balancing explainability with privacy and confidentiality.
• Key challenges include protecting sensitive information, preserving proprietary algori... more
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Explainability is necessary to build trust in AI systems.
• There is no universally accepted definition of explainability.
• So we focus on key considerations that don't require us to sele... more
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Algorithmic processes are often complicated by intricate data flows and transformations.
• Data flow diagrams and documentation can help make processes simpler.
To subscribe to the weekl... more
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Complexity must be actively managed rather than passively accepted.
• Data relevance directly impacts both accuracy and explainability.
• Technical “visibility” techniques can be useful.
more
Spoken by a human version of this article.
TL;DR (TL;DL?)
• Why Explainability Matters: It builds trust, is needed to meet compliance obligations, and can help identify errors faster.
• Key Challenges: Complex algorithms, intricate workflows, priva... more
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 ... more
Spoken by a human version of this article.
One question that comes up often is “How do we obtain assurance about third party products or services?”
Depending on the nature of the relationship, and what you need assurance for, this can vary widely. more
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this podcast launched 2 years ago and published 33 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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