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The Ethics of Analytics: Answering the Should We Question

Ness Digital Engineering Data Ethics

A great deal has been written on data related to its storage, security, meaning, governance, and usage. Regulations have been defined to protect individuals’ rights and how their data is used from a privacy perspective. While these are all important topics, there is one that often gets overlooked – ethics. Even though we can determine cause and effect in a certain circumstance and possibly divine the future, should we?

Let’s look further into the ethical use of data and the intersection of ethics and analytics to help answer the ‘should we’ question.

Regulations and the Ethical Use of Data

Ethics has always been at the forefront of what we consider to be good business. Should we promote misleading product information, or can we manipulate accounts? The obvious ethical answer is no. We have regulations to support ethical business practices supporting the rights of the individual and society as a whole; however, at this point, there are no regulations associated with the ethical use of data.

Data is not something that we manufacture or gather from the planet. In most cases, it is something that we create or collect with permission. As with any other asset, it is how we use this resource that has become the point of contention. New privacy regulations relate to how an organization can use data from a marketing perspective. Much has been written on who owns the data and if a group or individual should have access to it. However, not much has been said on what data should be used for in our daily lives.

A code of ethics for data analysts typically includes:

  1. Protect the client (from a privacy perspective).
  2. Let the data tell the story. If the data provides an answer that is not what the framer was expecting – the data is what the data is.
  3. Don’t intentionally misinterpret the data.
  4. Don’t embellish when not applicable.
  5. Don’t lie.
  6. Don’t change the data.

While these are important ethical standards that must be upheld, the real ethical conundrum is, “Should some questions be asked?”. When we look at it with that lens, we see that we can use data for discriminatory purposes in many circumstances.

Common Scenarios Where Ethics and Analytics Intersect

Medical: The medical field provides one of the best uses of analytics. Not only can both payers and providers analyze claims history to get an understanding of what is going wrong and why, but they can also take this information and add additional health data to form patient safety protocols. These processes and procedures can reduce injury and malpractice suits and increase patient satisfaction. The ability to search through histories of health data to determine the best intervention for a specific injury or illness based not only on how this patient presents themselves but the medical histories of millions of patients is another opportunity for analytics to be put to good use.

Analytics & Ethics Questions: While there are many benefits to leveraging data in the medical profession, there are ethical questions associated with the use of data. We all understand the concerns associated with acquiring patient data and how privacy must be maintained. What if, through the use of analytics, that risk aside, decisions on patient care were made? These decisions could be based not on actual patient care but on the perceived ability to pay, the predicted ability to recover, or, more concerning, the predicted outcome that could lead to an insurance claim against the hospital or doctor. Should a procedure not be undertaken, or a patient allowed to suffer or die based on the financial decision to avoid paying an insurance claim?

Education: Universities can use analytics to determine the viability of a professor based on history. Do all the students who have this particular professor for economics drop that as a major or continue? Is that professor better suited for other areas of instruction? By using historical data to ensure that the right professors are teaching the right courses, everyone benefits. The professors’ reputations and the school increase as the students who learn and graduate attribute their success to the school. The students benefit by getting the best education available to them.

Analytics & Ethics Questions: Where is the harm, and what are the ethical questions? There is any number, including what data should be made available to professors on student capabilities or how data is used in the admissions process itself. Should a university select students, not based on academics but on the student’s predisposition to donate to the university itself? If that decision overrides the decision based on academics, then the university may have turned down a more promising student based solely on financial information.

Preventing the Unethical Use of Data

Questions of ethics and analytics span a range of industries, and the questions arise on how to prevent the unethical use of data. A director of a data science group for a state agency stated that on numerous occasions, once the data has been retrieved for study, the requesting state agency noticed that other implications could be derived, especially when that data needed to be pulled from multiple agencies. The director was concerned that these additional questions were outside of the original purview of the analysis, had not been vetted, and could result in unethical use of the data itself. As part of the development of an Operating Model for the group, Ness helped determine that an ethics clause needed to be added to the mission and vision statements for the group and that an ethics board would need to be enacted.

While these questions are being raised, they are seldom being answered. There is no single body that has yet defined a true code of ethics for use in analytics. Some major universities are offering courses on the ethical use of data from the philosophical point of view, but there were no organizations that had included this type of ethos within their standards of behavior. Even the ADaSci (Association of Data Scientists) has a handbook, but these ethics focus more on issues associated with transparency as defined above to ensure that the data is not manipulated or misinterpreted.

Setting Standards for Data Analysis

An old comic stated, “With great power comes great responsibility.” In this case, we have given a great deal of power to a great number of people, but can we find a way to manage that power? Many professions have organizations that work to ensure both ethics and standards within their communities. Membership within these organizations is a recognition not only of the skill attained but of those standards. The time has come to define a set of ethics associated with the purpose for which it is analyzed. It may be as simple as borrowing from another profession – data shall not be used or analyzed in any way as to cause harm to or bias against any individual or group.

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