“Big” is a relative term, meaning large or great in dimensions, bulk, or extent. “Data” is factual information. It most often takes the form of measurements or statistics used as a basis for reasoning, discussion, or calculation. It’s not exactly relative in normal usage, i.e., considered in relation to or in proportion to something else. But the combo, “Big Data,” especially when capitalized as though it was a pronoun, is driving worldwide economies, governments, leaders, liars and high fliers absolutely bananas. Thus, it is prudent that we ask, “What are the ethics of writing big data?”

Big Data is to today’s business world what oil was in the mid-19th Century. The world’s first commercially viable oil well was dug in the USA. Emerging technology created new products from oil. Some thought we’d never look back. Futurists today think the oil boom will pale to the changes Big Data will bring to the economy, our government, and everything we do. “That’s because of the sheer number of companies now turning to digital technology and data-driven business models. The research, conducted by Forbes and the law firm Clifford Chance, found that 44% of companies are already using big data, 39% believe that they are ‘too bold’ with their approach, and 34% say they are ‘exploring’ big data.”[1]

A century and a half later, we recognize what the looting, rooting and tooting oil wildcatters and oil barons did in the 19th Century. But we are only seeing history repeat itself. We’d best buckle up; Big Data will likely bring the bad old days back. Big Data is the business tool of our times. It promises transformational changes in business with potentially disruptive results.

Some experts say it also has “the potential to land companies in an ethical mire.” The mire is at minimum big reputational risk. At the extreme end, there is prison time for executives who close their eyes as they open their retirement accounts. Recent scandals include “…the one that engulfed Facebook and destroyed Cambridge Analytica. Data ethics is a topic that has received high levels of public scrutiny as well as the attention of policymakers and regulators.”[2]

One writer put it this way. “Maybe it was inevitable in hindsight, but the accumulation and monetization of human data is now an industry—a commodity—of its own. As the internet’s precursor technologies were being refined, the directive against using it for profit was gradually lifted. What we have now is essentially a global economy fueled by the internet.”[3]

Others are chiming in regularly. “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.”[4]

The very existence of Big Data generates the need for data science. While tentative, some ethical principles are emerging out from under Big Data’s heavy blanket:

(1) Private customer data and identity should remain private.

(2) Shared private information should be treated confidentially.

(3) Because third-party companies share sensitive data—medical, financial or locational—they must have restrictions on whether and how that information can be shared further.

(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 is a relatively “new” player in the world of Big Data. It claims to be the “World’s First Print and Digital Publication focused on Artificial Intelligence, Big Data and Analytics. The Analytics Insight Magazine features opinions and views from top leaders and executives in the industry who share their journey, experiences, success stories, and knowledge to grow profitable businesses. Analytics Insight’s market focus remains on disruptive technologies.”[5]

While nascent, Analytics Insight Magazine is making good first steps. “AI should follow data ethics. Data ethics are a regulatory measure to current and historic frameworks, cultural mores and physical organizations. The most important part to understand when it comes to ethical issues involving data is the combination of personal information and ownership of data. The personal information of a person’s data file could even feature the individual’s qualification, living strategy, people and institutions they interact with. The use of such personal information involves a lot of issues if it fails to cope with ethics. Therefore, ethical applications should follow simple guidelines that could be useful for formulating a more detailed policy.”[6]

Time will tell whether “simple guidelines” are useful. More likely the bombshell mindset will take over. The bad actors in Big Data will open doors all over the world, throw their hand-grenades in, and run as fast as they can to the bank.

Gary L Stuart

I am an author and a part-time lawyer with a focus on ethics and professional discipline. I teach creative writing and ethics to law students at Arizona State University. Read my bio.

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[1] https://boardagenda.com/2020/02/26/big-data-ethics-pose-biggest-technology-challenge-for-businesses/

[2] https://boardagenda.com/2020/02/26/big-data-ethics-pose-biggest-technology-challenge-for-businesses/

[3] https://www.euroscientist.com/big-data-ethical-issues/

[4] https://towardsdatascience.com/5-principles-for-big-data-ethics-b5df1d105cd3

[5] https://www.analyticsinsight.net/ai-readiness-threat-ethics-technology-sector/

[6] Ibid.