The arc of Ethics in Data Analytic Organizations and the Greater Good

Floyd A. Brown

            The Social good is best served by an evolution of moral philosophy that drives ethical practices toward people-centric laws and regulations. Otherwise, what is the point of rights if not to foster stability, mutual benefits, protections and respect across society? Whether or not there is a market or business, people have rights. From the time we were drifters of small societies on prehistoric plains following herds or living in high caves, clashing flint stones to usher timbers of fire for warmth or living in modern coastal cities peering, from the technological wonder of modern skyscrapers embedded with LED lights out to wide seas with hope to the future, it remains true that all these stages of civilization, whether we recognized it as so or not, man had inalienable rights to liberty, privacy, equality and freedom to shape our destiny. For the first time an intelligence hovers on the horizon of society’s future, vacuuming up every meta data about humanity, collectively and individually. We stand at a point in human history where our advancement face the possibility of being usurped by rise of artificial intelligence (AI), and one of the main defenses that we have in assuring a safe future is the willingness and courage of organizations and data analyst, on whom the threads of artificial intelligence is weaved, to ensure that the ethics they lift up is for the greater good.

            Technology has developed to the point where machines are able to make decisions, understand natural language, solve complex problems, harvest insights and solutions from data analysis, and other cognitive abilities once attributable only to humans. The revolutionary growth of AI is dependent on massive data stores for training. AI’s hunger, aptly captured by the Spanish saying “saber es poder”, English translation ”Knowledge is Power”, has introduced moral and ethical challenges to privacy as people lose control over how medical records are used, biased data that may lead to further marginalization, as well as dilemmas in ownership for firms that may develop products or services based on data that was obtained without required permission. The dragon of artificial intelligence in its infancy needs to be fed data curated, packaged and dispatched by various contributors across the data analytics workflow. Unfortunately, the data consumption that powers AI’s lore sometimes disenfranchises people of their ability to control their privacy. It is not a question of whether we can have privacy in the information age, it is arguably a necessity that we maintain it to foment trust, personal development, and hold on to part of an identity of what makes us human, in that we have dignified access to a safe space in ourselves that others should not.

            Organizations need to establish ethical framework and privacy guidelines in a reality where the data analytic process is innovative and growing at a clip that is faster than “… the passage of relevant laws” (Edquist, 2022). Due to impact on reputation, that of business and customers, it is customarily upheld that a best practice in financial sector is that, it is the responsibility of everyone in the organization to manage risk. Similarly, to protect customers, the public and wider society, it is also the responsibility of everyone in an data analytics oriented organization, to ensure that ethical principles of operation and conduct are in sync with privacy guidelines that are current law such as, The General Data Protection Regulation (GDPR), for European companies to be transparent on their efforts to collect information as well as, laws that may be adopted in the spirit of upholding privacy as a benefit for the common good. 

            Businesses and organizations are enabling Data Analytics and other branches of AI by driving the research, the technical know-how in algorithms and compute technology, building resulting products and services, marketing and enlisting public appetite for these developments thus, need to police themselves while government laws and regulations play catch-up to designing and deploying guidelines to ensure that society is able to safely and ethically integrate AI. As businesses and organizations are subgroups within society, they are obligated to ensure they represent society’s ethical values in their build-out and dissemination of AI as a disruptor across businesses, education institutions, governments, health sector, recreational arts and entertainment, politics, and countless other disciplines. The gathering of meta data from these areas allows data analytics companies to use disparate data base information, web browsing cookies and, web purchases to learn customer habits and interest, then predict types of products or services users may next purchase.

            What are the ethical options for companies and data analyst with this power to influence a person’s life? Act Utilitarians may argue that the value of the consequences of collaborative filtering, gathered through data and used in predicting a customer preference, may make that person happy as they will see product offers to their liking while other internet users may view smart ads, to their choice preference, as intruding on their privacy as they never agreed to be targeted for such. It may be difficult to evaluate the Act Utilitarianism in the summation of the benefit of targeted ads, as millions of people may welcome it while many may not. As such, the responsibility of data analytic professional and firms to act as moral agents by offering opt-out option to folks to not partake in targeted advertising, as while the financial benefit of placing all the targeted ads may be significant, a large number of individuals across society may be unhappy and find insufficient utility in this offering. The opt out policy maintains a balance in maximizing utility of the service and social good as those who want data analytics influence in their lives can enjoy it while those persons that do not, have a mechanism to opt out.

            As data analytics is applied across datasets and new algorithms and machine learning techniques are developed, privacy and ethical boundaries will continue to be impacted (Edquist 2022) in new ways. As such, organizations will need to establish ethical frameworks that are robust and resilient in the rapidly changing field of data analytic techniques and tools that are driven by demand for AI systems, services and scaling efficiencies. The constant sea of AI changes shows urgent need for companies to anchor ethical guidelines around stable moral centers that are people-centric and not artificial intelligence or solely to the benefit of data analytics centered approach. This is one approach where despite societies changing moral standards and current laws, it’s better to err in defense of human rights, privileges and privacy as a prudential right (Quinn, 2020) than to defer to technology changes that may pose adverse effects to  society’s benefits.

            While companies and organizations are working to ensure that the values they have in place reflect wider societal attitudes and ethics towards privacy protection in the tsunami of big data analytic events, governments cannot allow the profit driven narratives that argue against privacy as some type of luxury that is more so a threat than not to the social good. Businesses need to be wary not to yield to the temptation of minimizing societal value on privacy to gain unfettered access to data that establishes and grows the interests of AI while erasing important scales of an individual’s humanity with the respect, trust and freedom we expect from others and grant them in turn – the latter is very important to some people as they view it in part as ability to control data about themselves.

            Data Analytics can easily take our ability to control data away from ourselves throughout its cycles of mining “…raw data to find trends and answer questions…” (edX.org, 2023). There are different personnel involved with management and application of the data during its cycle through the organization or company structure. Each team or individual worker may have different responsibilities in the technical or non-technical categories of their role. As such, company guidelines need to keep a common thread of certification that the data interaction is ethically driven across frameworks of descriptive analytics, data diagnostics, predictive analytics and, prescriptive analytics (Coursera, 2023).

            Personnel teams includes data scientist, junior analyst, etc., and all “AI initiatives, strategies, goals, and objectives should be clearly defined and prioritized for key teams and personnel within an organization” (Lumenova, 2024). As organizations are subgroups of society, required to uphold the ethical views of wider society, so too are individuals of the organization held to upholding what’s right. If an organization fails to provide its employees with ethical guidelines due to the pace of innovation in data analytics or any other field, for any reason, those personnels are still obligated to act in a way that is people-centric, for the wider good and, betterment of society.

            All technical and non-technical employees can absorb the lesson of Jacobus Lentz who used IBM computers and his data processing abilities of consequence in the Germany’s industrialized success in sending trainloads of innocents to extermination camps in World War II (Quinn, 2020). Intentional or not, Lentz is morally responsible for his actions that supported Genocide. Likewise, technologist and non-technical workers in the absence of clear laws or not, need to ensure that their actions are ethical. How do they know if their actions support people-centric results? It is, if the results of their work does not solely add to the profit line of organizations despite moral costs or to their own personal gain to the wider loss of the greater good in society with safety, freedom from oppression, individually ability to express themselves – all of which benefits everyone.

            History has shown that the time for ethical actions for the greater good is always now. When members of society fail during their time to act for the greater good, the philosophy of ethics have over the passage of time, curved back to that moment to acknowledge the moral lapse and apologies, as proven in America’s use of census data to round up Japanese-American citizens into prison camps in the course of World War II (Wang, 2018). The application of ethical standards is a challenge where laws may not exist at the time for the clarity of the greater good. As such, it is critical that businesses and organizations link their moral code and values to wider umbrellas of societal benefits that are steady over time and unwavering in support of promoting safety, respect, trust, peace and justice. Across the history of society and that of technological revolutions where innovations faced the question of use for good or ill, moral matters where “the arc of the moral universe is long but it bends towards justice” (Harold, 2022) and, the ethical practices of data analyst in  this fourth and most powerful Industrial Revolution so far, helps to ensure the curvature of society’s offering is that which is towards equity, lack of bias and egalitarianism in an era blanketed by artificial intelligence.

            The moral compass of companies, organizations and their staff whether technical or non-technical is best structured to focus primarily in not violating ethical principles of wider society to act in the moral interest of the greater good. Regardless of the logic they employ in so doing, they will be in alignment of moral philosophy that can be logically argued for making the right choices whether it is Kantianism, and its teachings that moral laws or universal, or leveraging the reasoning of Good Will and Categorical Imperative in encouraging others to be dutiful in doing what helps others (Quinn, 2020). It is a categorically imperative that is always correct regardless of the technology in play at that time, whether data analyst now with NVIDIA driven processors at their disposal or data accounting done with an abacus in the halls of trade in ancient Mesopotamia (Ethw, 2021), in individual decisions and corporate value systems, there needs to be an intent to act and honor ethics, privacy and morality in furthering the greater good.

            Data Analytical entities need to honor the covenant with society, the social theory that everyone that is a part of society will live according to the moral norms that are accepted even those not codified in law. (Quinn, 2020). Companies and organizations are not outside of society thus, they are beholden to act in moral favor of society. The aspiration of these goals in corporate culture, values and guidelines are understood by data analyst and other individual workers, customers and stakeholders as the moral conduct of all these groups are cut from the same moral cloth as partners of ethical responsibility. Companies and organizations are obligated to ensure that at its core, their work with data analytics will retain reasonable protection of privacy, in line with societal morals and ethics, for the benefit of all in light of the vast amounts of data that is driving the largess of the world’s transformation in the age of Artificial Intelligence.

References

Coursera. (2024, October 2). Data analytics: Definition, uses, examples, and more. Coursera. https://www.coursera.org/articles/data-analytics

Edquist, A., Grennan, L., Griffiths, S., Edquist, A., Grennan, L., Griffiths, S., & Rowshankish, K. (2022, September 23). Data ethics: What it means and what it takes. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/data-ethics-what-it-means-and-what-it-takes

edX.org. (2023, October 5). What is data analytics?. mastersindatascience.org. https://www.mastersindatascience.org/learning/what-is-data-analytics/

Ethw. (2021, May 12). Ancient computers. ETHW. https://ethw.org/Ancient_Computers#2nd_abacus_design

Harold, E. (2022, July 28). We are bending the arc of the moral universe toward justice. 2Civility. https://www.2civility.org/we-are-bending-the-arc-of-the-moral-universe-toward-justice/

Lumenova AI. (2024, June 13). The intersection between AI ethics and AI Governance. https://www.lumenova.ai/blog/intersection-between-ai-ethics-ai-governance/

Quinn, M. J. (2020). Ethics for the information age. Pearson.

Wang, H. L. (2018, December 26). Some Japanese-Americans wrongfully imprisoned during Wwii oppose census question. NPR. https://www.npr.org/2018/12/26/636107892/some-japanese-americans-wrongfully-imprisoned-during-wwii-oppose-census-question