Explainable Artificial Intelligence (XAI) by Pethuru Raj (.PDF)

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Explainable Artificial Intelligence (XAI): Concepts, enabling tools, technologies and applications by Pethuru Raj, Utku Köse, Usha Sakthivel, Susila Nagarajan
Requirements: .PDF reader, 30.0 MB
Overview: The world is keen to leverage multi-faceted AI techniques and tools to deploy and deliver the next generation of business and IT applications. Resource-intensive gadgets, machines, instruments, appliances, and equipment spread across a variety of environments are empowered with AI competencies. Connected products are collectively or individually enabled to be intelligent in their operations, offering and output. AI is being touted as the next-generation technology to visualize and realize a bevy of intelligent systems, networks and environments. However, there are challenges associated with the huge adoption of AI methods. As we give full control to AI systems, we need to know how these AI models reach their decisions. Trust and transparency of AI systems are being seen as a critical challenge. Building knowledge graphs and linking them with AI systems are being recommended as a viable solution for overcoming this trust issue and the way forward to fulfil the ideals of explainable AI. Explainable Artificial Intelligence (XAI) is a set of promising algorithms and approaches that empower users to comprehend why and how AI models reach a particular decision. These AI models must be penetrative, pervasive and persuasive, trustworthy, and transparent. XAI plays a significant role in ensuring a heightened confidence in the recommendations made by AI systems.
Genre: Non-Fiction > Tech & Devices

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