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Differentiating Intrinsic and Post Hoc Explainability
Artificial intelligence (AI) continues to develop at an unprecedented rate and transform our lives across various fields, from finding cancer cures to tackling climate change and exploring space. According to PwC’s 2022 annual business survey, https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-business-survey.html, 41% of surveyed companies indicated they used AI to enhance decision-making.
While the potential for autonomous learning using machine learning (ML) models is promising, demand for explanations as to how algorithms make decisions is emerging. The research community and end users want to understand AI systems’ influence on real-life scenarios, hidden risks, and consequences ...
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