Data Science is on the agenda but what about Data Science Ethics? The twin motors of data and information technology are driving innovation forward in most every aspect of human enterprise. In a similar fashion, Data Science today profoundly influences how business is done in fields as diverse as the life sciences, smart cities, and transportation.
As cogent as these directions have become, the dangers of data science without ethical considerations is as equally apparent – whether it be the protection of personally identifiable data, implicit bias in automated decision-making, the illusion of free choice in psychographics, the social impacts of automation, or the apparent divorce of truth and trust in virtual communication.
Justifying the need for focus on the Data Science Ethics goes beyond a balance sheet of these opportunities and challenges, for the practice of data science challenges our perceptions of what it means to be human.
This contribution was inspired by Julie Compagny’s noteworthy article on the Digital Me Up. Digital Me up is the blog of our students from the Advanced Master’s in Digital Business Strategy of Grenoble Management School, where I teach and Julie is one of the students from the 2018-2019 academic year. This topic will be on the menu of next month’s lecture about “Technology and Innovation”, which I will deliver on the premises of Vinci’s incubator, aptly named Leonard.
Data Science ethics and its influences on today’s business practicesif ethics is defined as shared values that help humanity differentiate right from wrong, the increasing digitalization of human activity shapes the very definitions of how we evaluate the world around usClick To Tweet
Margo Boenig-Liptsin’s points out that our ever-increasing reliance on information technology has fundamentally transformed traditional concepts of “privacy”, “fairness” and “representation”, not to mention “free choice”, “truth” and “trust”.These mutations underline the increasing footprint and responsibilities of data science – beyond the bytes and bits, data science shakes the perceptual foundations of value, community, and equity. If academia has been quick to establish Data Science programs around statistics, computation and software engineering, few programs address the larger societal concerns of data science, and fewer still analyse how responsible data practices can be conditioned and even encouraged. Let’s sketch out the contours of this challenge. Read more