How AI promotes ethical business practices

New tools can detect bad behavior, often before it happens

AI stops bad ethics before it gets worse

Jeff Liu had a hunch. The ethics monitoring algorithm he built as a consultant for a large enterprise had identified a regional sales office as the source of suspicious expense reports.

“So we started to look at culture,” he says. He interviewed staffers at the regional office and discovered a close‑knit community, where coworkers would regularly socialize outside the office. It soon dawned on him: the close personal relationships made managers more likely to approve unethical expense claims.

That teamwork of sophisticated high‑tech pattern recognition and old‑fashioned human sleuthing and intuition may be the shape of things to come. AI is now used as a tool to help root out ethical misconduct at all levels of an organization, from fishy expense reports to questionable decisions by board members.

“AI can look at the data and predict when we can stop these ethical slippery slopes before they get out of control,” said Lui, who is now AI director at Deloitte.

Those slippery slopes seem to be getting steeper. The last few years have seen a wave of ethical breaches in some of the country’s biggest companies. With hindsight it’s easy to ask why these companies missed all the warning signs.

Machine learning algorithms can help by finding suspicious patterns in vast data sets. Expense reports are a case in point. A few dollars here and there may seem insignificant to the person filing, but “it gets to a point where expenses get out of control,” Lui says.

Finding the ‘trigger moments’

Lui, who also previously worked on Google’s AI team, wrote his ethics monitoring tool using the open‑source TensorFlow AI platform. The tool looks for red flags in expense claims by crunching data from enterprise applications like Salesforce and SAP.

Many companies already take a proactive approach to potential ethical breaches by deploying whistleblower help lines and providing ethics training. Some are also building machine learning algorithms into ethics and compliance management software that identify situations where employees are at high risk of unethical behavior, such as opening a purchase order or filing an expense claim.

“These are all trigger moments that expose people to risk,” says Philip Winterburn, chief product officer at Convercent, a provider of ethics and compliance technology tools. Winterburn aims to prevent instances of so‑called “ethical fading” by sending employees text messages reminding them of their ethical responsibilities just as those trigger moments occur.

To do this effectively, the software must analyze complex data sources and be cleanly integrated with a range of enterprise applications, ranging from human resources to travel and expense reporting. Convercent’s tech also assesses personal data, such as salary and office location, in order to “assess the action in context of everything else we know about that person,” Winterburn says.

The program can distinguish between, say, an engineer on a business trip to Texas, and a salesperson travelling to China where they might be entertaining government officials. Each situation carries its own level of risk. By distinguishing these risk levels, Convercent can deliver appropriate reminders to employees.

Board-eye view

Other tools go further up the corporate ladder. Barry Libert, CEO of OpenMatters and a senior fellow at the Wharton School of Business, is building an automated advisory system that he hopes will create a “360‑degree view” of board members.

OpenMatters uses machine learning tools to construct rich portraits of 250,000 serving board members, analyzing past activities and statements, professional bios and social media profiles, along with mentions in news stories and corporate disclosure statements.

Libert believes this data, when combined and analyzed, provides an accurate snapshot of ethical strengths and weaknesses as well as skills and knowledge. The tool is designed to help companies make more informed decisions about board appointments.

Ethical lapses, intentional or not, will never completely disappear from the corporate world. Teamwork between human and machine intelligence can help companies reduce their risk.


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