Five Data Ethics Considerations for 2020 – eWeek
During the past two years, data theft and privacy concerns have emerged as a heavy counterweight to the benefits of big data and data analytics. Data ethics, the right or wrong conduct related to handling data, is in daily public discourse. Professionals who work in data-related fields are rethinking long-held beliefs about its management and use. The debate centers on the responsibility of companies to ethically protect the rights of data sources–in particular, consumers. For consumers, the question is: Who can you trust?
Certainly, humanity has much to gain from the potential upside from using data in areas such as health care (rare disease diagnosis) and work (four-day workweek, anyone?). However, the absence of a moral framework skews the picture of acceptable data use and organizational behavior. Last year the outcome was seen in multiple manifestations, including corporate reputation, such as Facebook’s $5 billion data privacy fine and legislation, such as the California Consumer Privacy Act, which went into force Jan. 1. Together these factors call into question how organizations consider data and its ethical use.
Pepperdine University’s Graziadio Business School tackles the technology potential and ethical challenges facing senior level executives in its Presidents and Key Executives MBA program. This eWEEK Data Points article is based on industry information from Dr. Kurt Motamedi, a serial entrepreneur, engineer and Ph.D in strategy and leadership, who works with established executives and startup entrepreneurs and prominent executives in the Pepperdine PKE program. Motamedi encourages these professionals to think deeply about their aspirations, legacy and work. In his classes, and with eWEEK readers here, he discusses five data points on current practices inviting new solutions.
Data Point No. 1: Curation
Digital data has drastically increased in volume in recent years due to the ubiquitous deployment of digital technology as well as advanced computational analytics techniques. However, the trend is not without complications. A 2019 health IT scoping study concluded that health-related big data curation is presenting major challenges to institutional arbitration boards, such as hospital Ethics Review Committees (ERCs). These ERCs are overwhelmed considering the proper use of data sources ranging from electronic health records and complex test results to fitness club memberships and Twitter hashtags. In health care and other settings, industry leaders will need to accelerate their learning about data curation before they will be able to determine acceptable sources for collecting data.
Data Point No. 2: Processing
There is intense interest and focus on data processing because of the value that can be extracted and applied to areas such as artificial intelligence and automation. For the first time there are now trillion-dollar companies processing data to build assets and profits. However, the idea of technological pollution–that something can be introduced that is harmful or poisonous–is also emerging. The danger is, in the pursuit of value, data can be reused any number of times without being consumed or diminished, and this also can be harmful. Metaphorically, the smoke may not be visible until it is suffocating. Data scientists will need to tamper a desire to push unbridled limits of processing data and focus on ethical, albeit more modest, prudent outcomes.
Data Point No. 3: Dissemination
It is common practice for data to be used in multiple independent, even unsuspected ways that may not initially be approved or intended. Multiple organizations are combining data sets and creating analytics that are nearly impossible to unwind. Data can be shared, sold, or resold without the knowledge or authority of the original source. Business leaders need to avoid becoming engulfed in technology hype and to practice caution and so-called “data minimization”–collecting only the data bound by ethics and necessary for the project or appropriate business operations.
Data Point No. 4: Algorithms
Data can now be captured and manipulated without human effort or engagement. This “automatic data capture,” when used in algorithms, is subject to unintentional biases and distortions. A recent report from consulting firm McKinsey notes these biases can negatively affect employment practices, criminal justice and health care. Certainly, data can be part of the solution in identifying and reducing biases by implementing technical improvements and operational practices. However, business leaders should know that data, especially in many algorithms, is now part of the problem because of flawed and biased assumptions and models in use.
Data Point No. 5: Transparency
In simple terms, data transparency can help provide assurance that data being reported is accurate and is generated from legitimate and official sources. In recent years, data transparency has been called into question not only in business, but also in political and consumer contexts. A review of major headlines in the last year can produce a long list of dubious practices, schemes and players in data-transparency infringements. However, there are organizations instituting more thoughtful approaches. A report from Deloitte gave WebMD credit for their transparency in how data is collected and gave consumers authority to decide what information they wish to disclose. Consumers were also able to opt out of–or opt into–data sharing. Business leaders need to understand and apply a methodology recognizing that data processes and data approaches needs to be open, ethical and apparent.
In a data context, the best and only hope is to instill in data scientists, innovators, founders, investors, managers and CEOs a set of principles, policies and guidelines what is right or wrong for all stakeholders. Within that framework, leaders can engage data while ensuring and maintaining personal freedom of choice and privacy. Under effective leadership, organizations will be called to formulate and support solutions that drive ethical conduct and responsible data values.
These are what Motamedi calls Morally Good Solutions. Unfortunately, for the near term many organizations will continue to misuse data and sow doubt among consumers, lawmakers and other stakeholders. In the longer term, Motamedi said he senses a rebound in which data misuse will become a national and business priority and curtailed, and offenders will receive their deserved fate. For organizations and people who deal in data, the end goal should always be trust and care of individual rights, freedom and well-being.
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