Key Dimensions of Algorithmic Management, Machine Learning and Big Data in Differing Large Sociotechnical Systems, with Implications for Systemwide Safety Management

Abstract

The time is ripe for more case-by-case analyses of “big data”, “machine learning” and “algorithmic management”. A significant portion of current discussion on these topics occurs under the rubric of Automation (or, artificial intelligence) and in terms of broad political, social and economic factors said to be at work. We instead focus on identifying sociotechnical concerns arising out of software development in the topic areas. In so doing, we identify trade-offs and at least one longer-term system safety concern not typically included alongside notable political, social and economic considerations. This is the system safety concern of obsolescence. We end with a speculation on how skills in making these trade-offs might be noteworthy when system safety has been breached in emergencies.