Summary

The Royal Society's statement is the result of "a public dialogue on data science ethics, including deliberative workshops, an experimental conjoint survey and an online engagement tool" (Drew, 2016). The document asserts six "basic principles": show clear user need and public bene?t; be minimally intrusive; use robust data science models; be alert to public perceptions; be as open and accountable as possible; and keep data secure. It also contains a checklist for each principle on "a sliding scale from very acceptable (green) to more challenging (blue)."
The document reflects the idea that people's ethical judgements are relative. "People's support is highly context driven. People consider acceptability on a case-by-case basis, ?rst thinking about the overall policy goals and likely intended outcome, and then weighing up privacy and unintended consequences" (Ibid). This relativism is clear in a statement from a participant: "Better that a few innocent people are a bit cross at being stopped, than a terrorist incident - because lives are at risk." And this relativism often reflects their own interests: "a direct personal bene?t (e.g. giving personalized employment advice), bene?t to a local community, or public protection" (Ibid). Thus the inclusion of "being alert to public perception" as an ethical principle.
GDPR
Robustness and Explainability of Artificial Intelligence https://ec.europa.eu/jrc/en/publication/robustness-and-explainability-artificial-intelligence

Content

Force:yes