TY - Generic T1 - Impacts of machine learning on work T2 - Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52) Y1 - 2019 A1 - Kevin Crowston A1 - Bolici, Francesco KW - artificial intelligence KW - automation KW - machine learning KW - work design AB -

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) that automate information tasks, we present a simple framework for identifying the impacts of an automated system on a task. From an analysis of popular press articles about ML, we develop 3 patterns for the use of ML--decision support, blended decision making and complete automation--with implications for the kinds of tasks and systems. We further consider how automation of one task might have implications for other interdependent tasks. Our main conclusion is that designers have a range of options for systems and that automation of tasks is not the same as automation of work.

JF - Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52) CY - Wailea, HI UR - http://hdl.handle.net/10125/60031 ER -