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Ethics Maps for AI Analytics

By Lorenzo Patelli, Ph.D.
January 1, 2021

An ethics map is an essential component of any company’s AI usage and AI-based decision-making strategy.

 

For many companies, the implementation and execution of business strategies depend on effective AI solutions. Management accountants have an ethical responsibility to help their organizations to mitigate the ethical risks of AI. They assist senior management in the formulation and implementation of an organization’s strategy that relies on AI and are direct users of AI-­powered algorithms or software designed for planning, performance management systems, financial reporting, and data analytics. Therefore, the ethical ramifications of AI are vital areas of concern.

 

If AI is at the core of an organization’s business model, management accountants have an ethical obligation to be concerned about several issues. Such macroethical challenges include the dehumanization of business processes, exacerbation of wealth inequalities, threats to value transparency in deploying AI solutions, substantial problems with data security and system integrity, and disruption of social interactions and its consequences for humans.

 

At the macro level, the biggest and most discussed ethical dilemma raised by AI centers on the fear that it will replace human workers with bots, causing a massive loss of jobs. In reality, economists expect AI technologies to have a J-shaped productivity growth curve, meaning that they would actually lead to a decrease in productivity at first, followed by tremendous growth.

 

We aren’t experiencing an exponential growth of productivity. To reap the benefits of productivity, these technologies require substantial investments in intangible assets such as learning and adaptation.

 

The IMA Statement of Ethical Professional Practice requires management accountants to practice their profession with honesty, fairness, objectivity, and responsibility. Never sacrifice these overarching principles to pursue technological transformations without questioning the ethical implications. Rather, actively apply the principles of ethical professional practice to contribute to the diffusion of ethical cultures and sustain real technological progress that could benefit the company and society at large.

 

AI also poses other, more functional ethical challenges that affect management accounting practices. This is particularly critical when AI is deployed to perform data analytics with the purpose of creating actionable insight.

 

DIAGNOSTIC ANALYTICS

 

First, management ac­countants must practice the ethical professional standards of credibility and competence in diagnostic analytics, the examination of data to find out why things happened in the way they did. Those are keys to avoid using AI blindly and propagating biases and other ethical problems. AI delivers outputs or solutions that are often difficult to interpret.

 

Moreover, AI diagnostic analytics solutions may—or may not—have practical value. Finding a correlation between variables in a large data set doesn’t mean that the variables are meaningfully and causally connected. Thus, basing decisions solely on statistical relationships may lead to incorrect inferences.

 

Findings that managers holding certain degrees are more prevalent in certain business areas may signify that they’re better trained to succeed in certain settings, but they may simply tend to gravitate to certain areas for reasons such as personal or professional disposition, group affiliations, etc., which may or may not be related to actual ability. Basing hiring, pay, and promotion decisions on these simplistic correlations may be unfair and have significant implications for the organization’s competitive advantage.

 

PREDICTIVE ANALYTICS

 

Second, management accountants must practice the ethical professional standard of integrity in predictive analytics, the examination of data to find out what is likely to happen. Integrity is key to a culture of ethical sensitivity, which could en­hance “roboethics”—the ethics of the humans who create and design AI—and machine ethics—the ethics of autonomous (machine) decision making. AI solutions replicate the biases of human developers, who identify the training data used to make the machine “learn.”

 

Humans can introduce data and stereotype biases if they include data that fails to accurately represent the population being examined. These issues are particularly problematic for management accounting practices if they introduce cognitive biases that are suboptimal for organizational performance. Predictive models may favor short-term results over long-term growth. Participate in the review of ethical training manuals for groups in charge of the development and deployment of AI.

 

PRESCRIPTIVE ANALYTICS

 

Third, management accountants should practice the ethical professional standards of in­tegrity and credibility in prescriptive analytics, the examination of data to find out what the organization should do to achieve its objectives. Integrity and credibility are keys to preserve the reputation and trust in the profession by designing accountability processes and avoiding a responsibility vacuum. AI presents interesting ethical questions on AI solutions’ unintended consequences. AI can be misused by bad actors to process fraudulent transactions based on fraudulent input or to prescribe illegal activities.

 

ADAPTIVE ANALYTICS

 

Lastly, management accountants must practice the ethical professional standards of competence, confidentiality, integrity, and credibility in adap­tive analytics, the examination of data to execute decisions. These ethical standards must shape management accountants’ ethical acumen in dealing with AI’s autonomous responses.

 

AI can autonomously develop unethical behavior through fatally flawed judgments and actions. Machine-learning algorithms can intelligently adapt to different settings, including learning how to lie. This raises concerns about the deployment of AI for critical financial decisions such as budget allocations and reserve accounting.

 

Moving from diagnostics to adaptive analytics, the ethical risk inherent in the reliance on AI increases the responsibility of management accountants to be outspoken about their ethical judgments on their organization’s AI implementations.


IMA ETHICS HELPLINE

 

For clarification of how the IMA Statement of Ethical Professional Practice applies to your ethical dilemma, contact the IMA Ethics Helpline.

 

In the U.S. or Canada, dial (800) 245-1383. In other countries, dial the AT&T USA Direct Access Number from www.usa.att.com/traveler/index.jsp, then the above number.

 

The IMA Helpline is designed to provide clarification of provisions in the IMA Statement of Ethical Professional Practice, which contains suggestions on how to resolve ethical conflicts. The helpline cannot be considered a hotline to report specific suspected ethical violations.

 

Lorenzo Patelli, Ph.D., is the interim director of the Institute for Enterprise Ethics, an associate professor of accountancy in the Daniels College of Business at the University of Denver, and a member of IMA’s Committee on Ethics. He can be reached at lorenzo.patelli@du.edu.
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