Data strategies are helping to reimagine digital transformation in organizations around the world, but what of data ethics. Many companies embark on offensive data strategies that lack processes that involve data ethics. Many years ago, data ethics was a concept reserved for academia and research papers. For-profit companies used data sparingly and took some risks in the use and management of data. That’s all shifted, though. Digital transformation brings forward a flood of information and data. A decision on how to use data is something that needs ethical understanding. Using data has direct business consequences. It takes on legal, regulatory, and reputational risks. Those risks, if not properly managed, can result in a direct impact on the bottom line.

Perhaps the most relevant example that we see in the market today is the cyber defense of data. Laws are catching up, and companies are being forced to take precautions to defend and protect the data they collect from customers. David McCandless & Tom Evans demonstrate the challenges around safeguarding data in this incredible visualization. Many of these events spark ethical questions around the role these companies played and their part in protecting that data. For instance, why did some of them even need to store data in an un-obfuscated form? Work in encryption and synthetic data creation from real data sets are expanding fields that seek to address these challenges.

A great story related to business ethics is Target’s use of data to predict pregnancy. Charles Duhigg of the New York Times interviewed Target’s Andrew Pole and learned what Target was attempting to do. Pole lays out the strategy Target used to mine data from women who registered for baby registries. They found patterns, of course, like purchasing lotion, scent-free soap, supplements, and other items common among those on the registries. Ultimately, they found that about 25 products could reasonably predict pregnancy with about 87% accuracy. They ended up sending ads to a girl still in high school, and her father became very upset with Target. Turns out Target was accurate, and regardless of an anecdote, is it ethical to use that data to determine personal information like that? While target marketing can be ethical, in this case, there are several ethical questions, like why market to a minor come into question.

Ethical use of data begins at the top of the organization. It should be a part of your data strategy and conversations with executives and the board. The esoteric nature of data ethics means that it may be essential to have individuals that understand ethics to challenge the use, storage, and management of data in an organization. Offensive strategies are particularly at risk for needing to understand the ethical risks in using data. This is because offensive systems tend to shift towards multiple versions of the truth (MVoTs), data meshes, and strategies that encourage use and experimentation with data. The ethical management of data, dissemination, access controls, and other policies have to move left so that the MVoTs don’t create ethical challenges with AI, ML, and other strategic data uses.

AI is a specific use case that gets brought up in ethical studies. Regardless of the debate on if it’s “really” AI, AI introduces a few things that make people uncomfortable. If data were ethically collected and managed, the data the AI uses can be a problem. If the algorithm is difficult to explain, regulatory and legal challenges, depending on the industry, can be concerning as well. Explainable AI is a set of tools and technologies that help to explain how models got to their results. This is very important when AI makes decisions without any human intervention. If poor data, unethical data, or unexplainable models are used in building an AI, it could impact the business’s bottom line.

Ultimately, data strategies have to wrap ethics as part of the transparency of the use of data within the organization. Senior leaders need to understand how data is being used, not myopically, but the governance and strategy. Keeping leadership at the table for data strategy conversations, getting an ethics expert involved for perspective, and keeping your governance model connected to the ethical use of data will enhance your data strategy.

References:

How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did (forbes.com)
A Practical Guide to Building Ethical AI (hbr.org)
Explainable AI | Google Cloud
World’s Biggest Data Breaches & Hacks — Information is Beautiful