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Marvin Minsky et al. raised the issue that AI can function as a form of surveillance, with the biases inherent in surveillance, suggesting HI (Humanistic Intelligence) as a way to create a more fair and balanced "human-in-the-loop" AI. [61] Explainable AI has been recently a new topic researched amongst the context of modern deep learning.
This has led to advocacy and in some jurisdictions legal requirements for explainable artificial intelligence. [68] Explainable artificial intelligence encompasses both explainability and interpretability, with explainability relating to summarizing neural network behavior and building user confidence, while interpretability is defined as the ...
Institutions must also establish explainable AI systems to maintain consumer trust while mitigating bias or decision errors,” Sinha explained. Bias in AI algorithms is another concern.
Full Characterization of Parikh's Relevance-Sensitive Axiom for Belief Revision, Journal of Artificial Intelligence Research 2019, with Theofanis Aravanis and Pavlos Peppas. Well-M³N: A Maximum-Margin Approach to Unsupervised Structured Prediction', IEEE Transactions on Emerging Topics in Computational Intelligence, 2019. with Abidi, S ...
The rise of emotion-aware AI. Virtual assistants can set reminders and answer questions. Soon, however, they'll be able to sense when you're having a rough day and offer a comforting response.
The topic provides an interdisciplinary challenge of bridging the gap of transparency between technical and non technical academics and policy makers to ensure the safety and equity of algorithmic systems as they advance at a rapid rate. [6] Some solutions and techniques that have been discovered include Explainable artificial intelligence (XAI).
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