The Machine Hums! Addressing Ontological and Normative Concerns Regarding Machine Learning Applications in Organizational Scholarship.

Item request has been placed!

Item request cannot be made.

Processing Request

Read Online Read More Add to Saved list

Author(s): Leavitt, Keith (AUTHOR); Schabram, Kira (AUTHOR); Hariharan, Prashanth (AUTHOR); Barnes, Christopher M. (AUTHOR)
Source:
Academy of Management Review. Apr2024, Vol. 49 Issue 2, p448-451. 4p.

Additional Information
- Subject Terms:
  MACHINE learning; INDUSTRIAL organization (Economic theory); ONTOLOGY; INNOVATION adoption; POSITIVISM
- Abstract:
  This article is a response by the original authors to commentaries of their 2021 article “Ghost in the machine: On organizational theory in the age of machine learning.” Here the original authors respond to several topics in the use of machine learning (ML) in organizational theory including ontological limitations of ML and the consequences of adopting ML.