Five Rules of Ethical Data Science

At Signify, our core value is to tell the truth. A lot of people have asked us what being an ethical data science company actually means, so we thought we would share five rules we use to keep us honest.

 

  1. Be Transparent
    Be clear with clients about methods and sources, and the limitations of both.
     
  2. Respect Privacy
    Don't piece together data to remove anonymity*. 
     
  3. Promote the truth
    Focus on human truths and insight rather than fake news and sewing division.
     
  4. Don't distort results
    Tell the truth when presenting findings, whatever you find or cannot find.
     
  5. Be respectful
    This rule encapsulates all the points above, but it's especially important to be respectful of the people you are studying, and it's patently false to claim that you can control large sections of the population.

 

There's plenty more that Signify are doing to set up audits and provide transparency for our clients and partners, and we might blog some of it if it's interesting enough, but we just wanted to put the basics up online. Please let us know in the comments if you have questions about ethical use of data, or what we're doing, or why.

Oh, and if you want to work with a company that uses cutting edge techniques but is also committed to using our technology and our communication skills to build empathy, promote better communications and improve the lives of billions of people - please get in touch. We would love to talk to you about our work.

 

 

*there's always a caveat. We respect the privacy of individuals but will expose the identities of real people in two cases. Firstly, if they are a social media influencer or artist or journalist who relies on attribution to make a living. Secondly, when we have been asked to investigate criminal cases of online abuse, we will pass over the details of anyone committing a hate crime to the relevant authorities. Caveat ends.

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