UK Govt releases Data Science Ethical Framework


Data science carries both huge opportunities and a duty of care. Technology is changing so rapidly; as are the public’s views. To mediate this landscape, the UK government has just released a Data Science Ethical Framework that seeks to maximise the potential for data science, whilst navigating the legal and ethical issues that accompany new forms of analysis.

The guidelines draw upon a public consultation process, which sought to understand what the public knew about data science and how it can be used. Perhaps unsurprisingly, the majority of respondents’ views on data science and its capacity to positively engage issues changed throughout the sessions; yet, a large degree of hesitance was still noted.


And the concerns of Section B are not just limited to the engagement of data science by government – journalists, too, often face public reluctance.

Public outcries following the publication of a data visualization that revealed the names and addresses of legal weapons owners in the United States, document dumps of classified material by Wikileaks, and the use of misleading data sources to map Nigerian Kidnappings, all illustrate some of the wide-reaching ethical issues encountered by anyone who works with data.

By this token, the Framework’s six guiding principles can just as easily by utilized by journalists as they can by government:

  1. Start with clear user need and public benefit
  2. Use data and tools which have the minimum intrusion necessary
  3. Create robust data science models
  4. Be alert to public perceptions
  5. Be as open and accountable as possible
  6. Keep data secure

In applying these principles to their work, journalists can self-assess through the Framework’s quick checklist and technique-specific guidelines.


Image: Ethical guidelines for web scraping

Importantly, the document is just a starting point – the first iteration of what its authors hope will be an ongoing discussion with the public on data science, its potential to stimulate innovation, and the imperatives underlying responsible action.

“It is difficult to try and develop a set of ‘do or don’t’ standards that can be applied universally across all data science projects – the public do not identify opportunities in that way. Instead, they conduct a more nuanced assessment to evaluate the methods against the objectives of the policy,” explained Steven Ginnis, Head of Digital Research at the Social Research Institute at Ipsos MORI.

“Getting the policy opportunity right is just as crucial as the data science method. To date, much of the debate surrounding use of data science has largely focused on balancing public benefit with concerns about privacy and security; this research has shown that the public are willing and able to take the discussion a step further, and explore how values of fairness, transparency, agency and accountability are upheld within data science.”

Read the Data Science Ethical Framework here.

Image: ビッグアップジャパン