What codes inform our work with digital data?

This is the second of a three-part series on the ethics of data in civil society, leading up the Stanford Conference on September 15-16.

Ethical codes abound - here's a list of just a few of them with relevance to how nonprofit organizations or private action for the public benefit.

Asilomar Convention: Ethical decision making in higher education research

A manifesto for the future of the 'right to be forgotten' debate

The Consumer Privacy Bill of Rights (USA)

Compendium of Ethics and Standards for Nonprofits

The Data Bill of Rights


(A longer, but still not comprehensive, list of examples can be found here)

What, if anything, is different about digital data that requires us to rethink our work in civil society? Here are some characteristics of digital data that may require new ethical choices. 
  • Digital data can be collected passively, without knowledge or consent of those from whom the data are collected.
  • Digital data enable the application of predictive analytics the accuracy or validity of which are still unknown.  
  • Digital data can be stored remotely, and for unknown lengths of time, by third parties who have collected the data or purchased the information.
  • Digital data alter the time frame for our actions. For example, real-time satellite imagery lets us adjust our interventions with information never before available. Alternatively, stored data collected from a person today may be used to define actions on behalf of or against that person's children or grandchildren. It can both shorten and lengthen the relevant time frame.
Several scholars have written about ethical provocations of big data, the need for ethics related to big data, and the need for legal due process where big data, algorithmic predictions, or other software applications are concerned. Here are two resources by individuals participating in the Stanford conference.

Kate Crawford and Jason Schultz, Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms.

Neil Richards and Jonathan King, Big Data Ethics 

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