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XAI—Explainable artificial intelligence

It is necessary to help end users to understand the competencies of the AI systems in terms of what competencies a particular AI system has, how the competencies should be measured, and whether an AI system has blind spots;

From a human-centered research perspective, research on competencies and knowledge could take XAI beyond the role of explaining a particular XAI system and helping its users to determine appropriate trust.

These roles could include not only learning and explaining to individuals but also coordinating with other agents to connect knowledge, developing cross-disciplinary insights and common ground, partnering in teaching people and other agents, and drawing on previously discovered knowledge to accelerate the further discovery and application of knowledge.

Michael Stevens: Vsauce | Artificial Intelligence (AI) Podcast

This conversation is part of the Artificial Intelligence podcast.This episode is presented by Cash App: download it & use code 'LexPodcast'INFO:Podcast website: Podcasts: episodes playlist: playlist: LINKS:Vsauce YouTube: Twitter: Instagram: - Introduction2:26 - Psychology3:59 - Consciousness6:55 - Free will7:55 - Perception vs reality9:59 - Simulation11:32 - Science16:24 - Flat earth27:04 - Artificial Intelligence30:14 - Existential threats38:03 - Elon Musk and the responsibility of having a large following43:05 - YouTube algorithm52:41 - Mortality and the meaning of lifeCONNECT:- Subscribe to this YouTube channel- Twitter: LinkedIn: Facebook: Instagram: Medium: Support on Patreon:

AI for the Common Good.

Open Source NLP Platform Design, evaluate, and contribute new models on our open-source PyTorch-backed NLP platfom, where you can also find state-of-the-art implementations of several important NLP models and tools.

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