Data ethics has become an increasingly critical topic as the volume of data collected by organizations has grown and the proportion of decisions driven by that data has grown with it. That said, there is not much point in trying to drive discussions regarding data ethics principles without first ensuring you are building on a strong foundation of organizational ethics in general.

This may seem like an obvious point, and I am sure many will take this for granted. I would argue, however, that this attitude is not universal. I propose a five-step plan for data leaders to get to a better place on ethics.

  1. Define your ethical viewpoint as a company. Are ethics and values part of your cultural company consciousness, or do you do what you do only because you are required by law? The regulatory landscape is ever-evolving and increasingly complex, requiring more resources to stay compliant, particularly if you are a global business. These requirements are necessary but, in my view, not sufficient. How far beyond ‘must do’ does your organization go, and who is thinking about what it ‘should do’? For example, at Tines, we have enshrined in our company values the uniquely Irish concept of soundness - that is, to do the right thing, focusing on transparency, honesty and integrity in our interactions with ourselves, our customers and the wider cybersecurity community.

    If your leadership is not engaged meaningfully on the topics of ethics and values, it is unlikely any coherent data ethics vision will emerge. If the ethics cart is before the data horse, you cannot have a data ethics conversation.
     
  2. Translate your ethical viewpoint to the use of data. Assuming you have a defined ethical view as an organization, how do you translate that to your data? In other words, how do you apply this ethical lens to your data operations? The actions we can take with our data are infinite, but data leadership should provide a strong voice in ensuring these are the right actions to take for your users, customers, or competitors. So, where do you, your teams and organization stand on how you use data? You will likely be surprised at how much unstated ambiguity you find. 
     
  3. Think through the legal, privacy and data security obligations. Privacy is probably the most obvious piece of the data ethics equation, but with the right privacy and security frameworks, data can become an incredibly powerful tool for driving ethically sound decisions. Do you have allies in these areas of your company to help you think through data ethics issues? If not, work on building those bridges to create a solid foundation for data ethics in your business.
     
  4. Identify allies to drive the conversation forward. Let us assume that your leadership already has some view on how they want their company to be perceived in the world, and that you have aligned with stakeholders on your legal, policy, and security teams. This is a good point to seed discussions across the business on how to balance bringing greater objectivity through data-driven decision-making with staying true to your company’s values and avoiding cold hyper-objectivity. These are important conversations to have about your first data ethics principles.
     
  5. Codify practices within data teams. Once you have defined a working, credible point of view on ethics and how that applies to data, it is time to evangelize and operationalize it in the way your teams treat data. The larger and more complex your business is, the harder it will be to do this comprehensively. Your goal should be creating a culture where people work from an innate sense of what is right and wrong, but they are never reluctant to raise their hands for clarity. This requires wrangling with questions such as, “Are there hard constraints we need to put on our data use? Or are there things we can do that are beneficial, that we should be doing more of? If we amplify bias in a certain area, is that good or bad?” Having these conversations in tandem, and not completely divorced from the company culture overall, is my best recommendation. 

As a data leader, there is an impetus for you to take on a role as guiding the proper and ethical use of data in your business. For one thing, there are really no external regulatory bodies for data ethics right now. But these things matter. They have real-world implications, and the larger and more influential a company you are, the more you want to have a viewpoint on it.  

The value of healthy tension
Data ethics is a broad space. It means so many things to different people, and manifests in completely different ways in a financial institution versus a social network. At a bare minimum, having a consciousness or an awareness that data ethics matters is essential. If you do not have a viewpoint on what your values are, start with that, and then work with your data functions and the allies who touch on data topics to codify what your company should look like through a data lens.

As we begin to see more data regulation, hard and soft, I feel that we will arrive at better shared, consistent language around these topics. Remember that it is okay to ask challenging questions and feel uncomfortable. Challenging questions keep people on track and keep you focused on making progress on these topics.

All of this inquiry is crucial because as incredibly quickly as the technical elements of the data industry have grown, there is still a lot of this vagueness on the ethics side. As the space matures, I am confident we will get to a more common understanding of how we define problems and how we solve them together.