| Literature DB >> 29342707 |
Piotr M Patrzyk1, Daniela Link1, Julian N Marewski1.
Abstract
Artificial intelligence algorithms seek inspiration from human cognitive systems in areas where humans outperform machines. But on what level should algorithms try to approximate human cognition? We argue that human-like machines should be designed to make decisions in transparent and comprehensible ways, which can be achieved by accurately mirroring human cognitive processes.Entities:
Mesh:
Year: 2017 PMID: 29342707 DOI: 10.1017/S0140525X17000255
Source DB: PubMed Journal: Behav Brain Sci ISSN: 0140-525X Impact factor: 12.579