The promise of what AI can do for organizations has been at a fever pitch over the past few years. Yet, as the predictive potential of AI-powered models grows exponentially with new machine learning algorithms, so does their complexity-making them challenging to interpret by the business. But for AI systems to become trusted advisors to human decision-makers they need to be able to explain the “why.”
With ‘trust’ being the core factor driving adoption of AI insights, Explainable AI (XAI) has the capabilities to overcome these business concerns, while providing reassurance that decisions are made in an appropriate and non-biased way
Take a deep dive into the world of explainable AI for business and learn,
- How to effectively gauge the need for explainability for AI techniques.
- How explainable AI frameworks and interpretability techniques make AI-driven decisions more transparent, reliable, and trustworthy for business users.
- Understand the key determinants and uses of explainability in business decision-making.