‘Data Ethics’ is a fast developing field used in business, policy and research contexts. But as a fairly new term, the definition and frameworks of use, have currently no univocal meaning. Policymakers, businesses and academia are looking for common frameworks to establish practices and focus areas.
In the introduction of a recently published special issue on ‘The ethical impact of data science’ Mariarosaria Taddeo and Luciano Floridi from University of Oxford outline the emerging Data Ethics branch of research. (The intro “What is Data Ethics” was written on behalf of The Alan Turing Institute and the Oxford Internet Institute)
Taddeo and Flordi define data ethics research as the branch of ethics that studies and evaluates moral problems related to data, algorithms and corresponding practices. They retain that the complexity of a data saturated environment requires a holistic and inclusive perspective that avoids ad hoc and narrow approaches and call for an overall framework for analysing the ethical implications of data processes that will adress three core axes:
- the ethics of data (how data is generated, recorded and shared)
- the ethics of algorithms (how artificial intelligence, machine learning and robots interpret data)
- the ethics of practices (devising responsible innovation and professional codes to guide this emerging science)
Because the areas are interlinked, data ethics research must address all three axes, which they argue can be done even with different research focus. They also describe why they have chosen to use the term data ethics as a way of recentering research efforts on understanding the very data processes and what is done with data, rather than on the hardware as the main effector. It is, as they say “the data that represents the source of our new difficulties”. With these ideas on the nature of Data Ethics they describe a constructive, solution oriented research approach.
Learning from Environmental Regulation
The special issue contains a range of articles applying data ethical approaches to different areas of reasearch from big data and human rights, ethic of smart cities, data philantrophy and to data science in government.
In one particularly interesting article “Compelling truth: legal protection of the infosphere against big data spills”, Burkhard Schafer describes lessons to be learned from environmental regulation and environmental ethics when governing the data society.
Shafer argues that just like with the environment, Internet regulation must deal with a complex adaptive system that is difficult to predict the effect of and thus impossible to govern with traditional top down or single point legislation, the regulatory challenges are transnational (origins of challenges outside the jurisdiction of a nation) and in general regulation requires substantial expetise. He walks us through applications of regulatory approaches to safeguarding the environment and the experiences from these.
For example the Stewardship systems that in the end proved to be the best sollution for natural preservation, can be used as an approach to the protection of privacy in the data society. The idea behind is to maximise the use of traditional local knowledge, and information about the environment for its protection.
We currently see this approach best mirrored in the personal data store movements. Although as he argues, we must move away from an individualistic approach to privacy and data ownership to a focus on democratic communities where privacy becomes an enabler of democratic values.
This comparison may also be an incentive to companies that are increasingly seeing data ethics as a competitive advantage, but in this new field need practical tools and data ethical best practices to mirror and be inspired by.