Patrzyk PM Link D Marewski JN 2017 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. application/pdf https://sonar.ch/global/documents/148323 eng info:eu-repo/semantics/altIdentifier/doi/10.1017/S0140525X17000255 info:eu-repo/semantics/altIdentifier/pmid/29342707 info:eu-repo/semantics/openAccess The Behavioral and brain sciences. - 2017 Algorithms Artificial Intelligence Cognition Decision Making Humans Learning Human-like machines: Transparency and comprehensibility. http://purl.org/coar/resource_type/c_6501