Cambridge Analytica: Recommendations on Data Ethics

Before going deep into Data Ethics, I would highly recommend watching the documentary The Great Hack on Netflix which summarizes Cambridge Analytica’s involvement in the largest Data Ethics issue and how it played a role in Brexit, the Trump Campaign, the Cruz Campaign, and others. It is also interesting to know that the people who were interviewed in this film have “relevant” backgrounds of analyzing behavioral patterns and they were all brought together for a reason. Another interesting factor is the deep-dive into Facebook quizzes which formed “personality models” based on people’s responses.

Digital Marketing is one of the largest industries and top priorities for ALL organizations. What makes Digital Marketing successful is data, customer journey maps, personas, and creating a personalized message for a target market. All of these decision points require loads of data and science to identify behavioral patterns. However, with it comes a moral dilemma on what is the ethical correctness and level at which you can use data to describe a customer or a prospect or a market.

It was summarized very well in the movie.

You send your quizzes/questions out –> People fill it and it comes back to you –> You build your personalized messages –> You target the people –> Results follow

Addressing Data Ethics

So how do you address the Ethics questions at an organizational level:

• Form an executive level “Ethics Committee” which will ask the question, “What is the right level of ethical data you can capture and use for Digital Marketing?”
• Form a Data Governance committee in partnership with Ethics committee that will control the data being used and why/how it is used?
• Consider categorizing your data inventory into Systems of Record, Shared Data Assets, Enrichment Data, and Opportunistic Data
• Customer data should be truly treated as an asset and treated similar to physical assets. This will provide lineage on how the data is getting used
• Invest in a Data Catalog platform that will and MUST provide clear line of sight on “how” data is getting used within the enterprise
• Get a clear picture (probably a maturity model) on your companies Data Literacy [How does your company use Data for decision making?]
• STOP using Data Extracts in desktops, mobile phones, MS Excel, or others [I know you use it :)] . Use a standardized data platform instead where your Data usage can be tracked and monitored
• Carefully consider building and using machine learning and cognitive algorithms that can use social media data for personality analysis. Have a good handle on how these automated algorithms use data
• Monitor and track usage of 3rd Party datasets

Data is the most powerful asset in your company. The winners and losers in any industry are identified by effective usage of data. But every organization has the moral obligation to protect and ethically use data for decision making. Talk to Perficient on how to define Data and AI Ethics.