What machines can't do (yet) in real work settings

• Main Authors: DAVENPORT, Thomas H., MILLER, Steven M.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Artificial intelligence; labor force; human work; machines; Artificial Intelligence and Robotics; Technology and Innovation
• Online Access: https://ink.library.smu.edu.sg/sis_research/7333; https://ink.library.smu.edu.sg/context/sis_research/article/8336/viewcontent/Davenport_Miller_What_AI_Can_t_Do_2022month10_06_CLEAN_Word_doc_for_SMU_Library_respository_81_.pdf
• Institution: Singapore Management University

AI systems may perform well in the research lab or under highly controlled application settings, but they still needed human help in the types of real world work settings we researched for a new book, Working With AI: Real Stories of Human-Machine Collaboration. Human workers were very much in evidence across our 30 case studies. In this article, we use those examples to illustrate our list of AI-enabled activities that still require human assistance. These are activities where organizations need to continue to invest in human capital, and where practitioners can expect job continuity for the immediate future