Five Principles for Big Data Ethics

Pedro Uria-Recio Pedro Uria-Recio
October 1, 2018 Big Data, Cloud & DevOps

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Big data analytics raises a number of ethical issues, especially as companies begin monetizing their data externally for purposes different from those for which the data was initially collected. The scale and ease with which analytics can be conducted today completely changes the ethical framework. We can now do things that were impossible a few years ago, and existing ethical and legal frameworks cannot prescribe what we should do. While there is still no black or white, experts agree on a few principles:

  1. Private customer data and identity should remain private: Privacy does not mean secrecy, as private data might need to be audited based on legal requirements, but that private data obtained from a person with their consent should not be exposed for use by other businesses or individuals with any traces to their identity.
  2. Shared private information should be treated confidentially: Third party companies share sensitive data — medical, financial or locational — and need to have restrictions on whether and how that information can be shared further.
  3. Customers should have a transparent view of how our data is being used or sold, and the ability to manage the flow of their private information across massive, third-party analytical systems.
  4. Big Data should not interfere with human will: Big data analytics can moderate and even determine who we are before we make up our own minds. Companies need to begin to think about the kind of predictions and inferences that should be allowed and the ones that should not.
  5. Big data should not institutionalize unfair biases like racism or sexism. Machine learning algorithms can absorb unconscious biases in a population and amplify them via training samples.

There are certainly more principles we need to develop as more powerful technology become available. Data scientists, data engineers, database administrators and anyone involved in handling big data should have a voice in the ethical discussion about the way data is used. Companies should openly discuss about these dilemmas in formal and informal forums. When people do not see ethics playing in their organization, people in the long run go away.

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