Emanuele Ratti, Mark Graves,
"Cultivating Moral Attention: a Virtue?Oriented Approach to Responsible Data Science in Healthcare"
, in Philosophy and Technology, Springer, 5-2021, ISSN: 2210-5441
Original Titel:
Cultivating Moral Attention: a Virtue?Oriented Approach to Responsible Data Science in Healthcare
Sprache des Titels:
Englisch
Original Kurzfassung:
In the past few years, the ethical ramifcations of AI technologies (in particular data science) have been at the center of intense debates.
Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral
responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars have highlighted the limitations of such a principled approach.
Drawing from microethics and the virtue theory tradition, in this paper, we formulate a diferent approach to ethics in data science which is based on a diferent conception of
?being ethical? and, ultimately, of what it means to promote a morally responsible data science. First, we develop the idea that, rather than only compliance, ethical decision-making consists
in using certain moral abilities(e.g., virtues), which are cultivated by practicing and exercising them in the data science process. An aspect of virtue development that we discuss here is moral
attention, which is the ability of data scientists to identify the ethical relevance of their own technical decisions in data science activities. Next, by elaborating on the capability approach,
we defne a technical act as ethically relevant when it impacts one or more of the basic human capabilities of data subjects. Therefore, rather than ?applying ethics? (which can be mindless),
data scientists should cultivate ethics as a form of refection on how technical choices and ethical impacts shape one another.
Finally, we show how this microethical framework concretely works, by dissecting the ethical dimension of the technical procedures involved in data understanding and preparation of electronic health records.
Forschungs-