Chapter 5: Searching for Unicorns: Organizations’ Misperceptions of Data Science and Misconceptions of Technical Solutions Without Accounting for the Human Interface

Prior research on socio-technical systems has productively explored the benefits of considering human needs and behavior in work settings where technology is used. AI/data-driven projects, which suffer high failure rates, present a particularly important and appropriate opportunity for consideration in a socio-technical framework. This paper hypothesizes that a meaningful, but not previously recognized, factor impacting the success of AI/data-driven work is an individual’s or group’s unconscious identification with this technology. Through examination of examples from a small number of companies, this research shows how better performing companies have implicitly addressed the competitive posture humans instinctively adopt toward future looking technology. Successful companies do this by more clearly distinguishing the value and contributions of humans from tech. The findings help consultants begin to imagine how to leverage the human element better and more effectively prevent data use failure. They also demonstrate expanded application of the framework of socio-technical systems theory, which provides researchers with a new tool to drive further investigation and thought leadership opportunities.