Can we open the black box of AI?

Nature

Volumn 538, Issue 7623, 2016, Pages 20-23

  Castelvecchi, Davide ^a  

^a London   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALUMINUM; ARTIFICIAL NEURAL NETWORK; BRAIN; MACHINE LEARNING; MACHINERY; RESEARCH WORK; ROBOTICS;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BASIC RESEARCH; COMPUTER; HUMAN; KNOWLEDGE; LEARNING ALGORITHM; MAMMOGRAPHY; NONHUMAN; PRIORITY JOURNAL; RISK FACTOR; ROBOTICS; SYNAPSE; ASTRONOMY; CREATIVITY; INFORMATION PROCESSING; MACHINE LEARNING; PHYSICS; PROCEDURES; STANDARDS; THINKING; TRENDS; UNCERTAINTY;

ASTRONOMY; CREATIVITY; DATASETS AS TOPIC; HUMANS; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER); PHYSICS; ROBOTICS; THINKING; UNCERTAINTY;

EID: 84990235978     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/538020a     Document Type: Article

References (5)

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3. Nguyen, A., Yosinski, J., & Clune, J Preprint at https://arxiv.org/abs/1412.1897 (2014).
4. Lipson, H., & Schmidt, M Science 324, 81-85 (2009).
5. Ghahramani, Z Nature 521, 452-459 (2015).