EMANUEL MOSS
CUNY Graduate Center / Data & Society
FRIEDERIKE SCHÜÜR
Cloudera Fast Forward Labs
[s2If is_user_logged_in()]
Download PDF
[/s2If]
[s2If current_user_can(access_s2member_level1)]
[/s2If]
The successes of technology companies that rely on data to drive their business hints at the potential of data science and machine learning (DS/ML) to reshape the corporate world. However, despite the headway made by a few notable titans (e.g., Google, Amazon, Apple) and upstarts, the advances that are advertised around DS/ML have yet to be realized on a broader basis. The authors examine the tension between the spectacular image of DS/ML and the realities of applying the latest DS/ML techniques to solve industry problems. The authors discern two distinct ways, or modes, of thinking about DS/ML woven into current marketing and hype. One mode focuses on the spectacular capabilities of DS/ML. It expresses itself through one-off, easy-to-grasp marketable projects, such as DeepMind’s AlphaGo (Zero). The other mode focuses...