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Better Transparency and Fairness in AI Systems

Posted July 28, 2020 | Technology |
Better Transparency and Fairness in AI Systems
Neural-symbolic artificial intelligence (AI) combines the pattern-recognition and pattern-matching capabilities of neural networks with the symbolic-reasoning functionality and transparency features of rule-based and knowledge-based systems (KBSs). One of the main goals of neural-symbolic AI is the development of hybrid AI systems that are more explainable and transparent in their reasoning.
About The Author
Curt Hall
Curt Hall is a Cutter Expert and a member of Arthur D. Little’s AMP open consulting network. He has extensive experience as an IT analyst covering technology and application development trends, markets, software, and services. Mr. Hall's expertise includes artificial intelligence (AI), machine learning (ML), intelligent process automation (IPA), natural language processing (NLP) and conversational computing, blockchain for business, and customer… Read More
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