Unveil AI decisions with Explainable AI
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White paper
Explainable AI and the need to ensure transparency in AI models
Coforge's ExplainableAI: Unveiling the Why behind AI decisions
The transformative power of AI is undeniable, but for many organizations, a hurdle exists – the "black box" nature of the AI models. Coforge's ExplainableAI solution tackles this challenge head-on, fostering trust and accelerating AI adoption.
ExplainableAI sheds light on the inner workings of AI models, enabling organizations to understand the factors influencing AI decisions. This transparency helps build trust in AI recommendations, allowing stakeholders to make informed decisions based on clear reasoning. Finally, by understanding how the model arrives at its conclusions, organizations can improve its accuracy and effectiveness through targeted adjustments.
Coforge's ExplainableAI utilizes various techniques like feature attribution methods (SHAP, LIME) to pinpoint the most impactful data points in a model's decision-making process. Additionally, counterfactual analysis allows for simulating alternative scenarios, providing valuable insights into how adjustments to input data might influence the outcome.
What we know.
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White paper | Quasar Responsible AI
Future-Proofing Finance: Building a Sustainable AI strategy in a Regulated Landscape
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