The growth of artificial intelligence (AI) has attracted its fair share of criticism in recent years just as it has become central to the conversation about how to scale up and improve ESG performance across corporate America.
To be fair, such concerns about AI are warranted. After all, humans are still designing these systems, so bias is still a risk at many levels, whether it comes to face recognition technology or how companies vet potential hires. Some brands, in fact, have pledged to work together to prevent algorithmic bias from entering the workplace. Google is an example of a company that says it is striving to teach developers about fairness considerations when building, evaluating and deploying AI and machine learning models.
Nevertheless, AI systems in aggregate can offer the ESG practitioner one important tool that will be hard to overlook: The ability to deal with the overwhelming amount of data through which teams must sift as they gauge their companies’ performance.
Some ways in which AI can prove to be useful, and score that “ah-ha” moment among the skeptics is when it comes to the “E” in ESG — as in measuring and finessing environmental performance. As the World Economic Forum (WEF) reminded us last week, one of the most difficult sets of data to measure are Scope 3 emissions, notoriously pesky to track as they comprise companies’ emissions coming from their supply and value chains. Chasing suppliers down for that data — if they’ll even measure and then reveal such information in the first place — is a task no sane person would demand from another. But reporting systems that run on AI can help solve that problem; WEF points to a BCG study concluding that companies harnessing such technologies are about twice as likely to both measure their emissions effectively and reach their emission reduction targets.
Further, while poorly designed AI systems are at risk of amplifying humans’ biases, at the same time on the “S” for social front, they can help to identify top candidates for jobs while identifying teams of current employees who are at risk of being disengaged. Optimized AI platforms can potentially smooth out potential rough patches between managers and their direct reports. “Managers’ biases can also creep in when it comes to setting goals for employees. AI can help by comparing employees’ goals against others with the same tenure and then alerting managers if they’re consistently assigning fewer or less important goals to certain workers,” wrote technology journalist Linda Rosencrance last year.
Outside a company’s office, AI and machine learning platforms can team up to identify possible snags within a supply chain — a lesson many organizations are still learning after what occurred worldwide during the global pandemic. Supply chain managers can deploy these technologies to help monitor human rights violations such as forced labor or risks including unsafe working conditions.
As for companies with a very specific mission, AI is achieving what used to take huge teams of professionals to accomplish. Take the plant-based protein industry, which on one hand can harness this technology to determine what raw materials can recreate the texture and nutrition of meat at a competitive cost — while on the other AI-driven sequencing can even improve their flavors, too.
Finally, at a time when more investors adopt an ESG framework to hone in on companies’ governance structures, AI can also lend an assist. Companies with operations spread all over the globe need to know in real time how regulations differ in different companies and here in the U.S., even in different states. Next-generation risk modeling can help corporate boards make decisions with the best possible information as they evaluate market trends and potential risks. “As for governance, a focus on data sovereignty and the creation of a single view of real-time data ensures that data is treated with respect,” Mike Hughes wrote for Forbes last month.
Image credit: Markus Spiske via Unsplash
Leon Kaye has written for 3p since 2010 and become executive editor in 2018. His previous work includes writing for the Guardian as well as other online and print publications. In addition, he's worked in sales executive roles within technology and financial research companies, as well as for a public relations firm, for which he consulted with one of the globe’s leading sustainability initiatives. Currently living in Central California, he’s traveled to 70-plus countries and has lived and worked in South Korea, the United Arab Emirates and Uruguay.
Leon’s an alum of Fresno State, the University of Maryland, Baltimore County and the University of Southern California's Marshall Business School. He enjoys traveling abroad as well as exploring California’s Central Coast and the Sierra Nevadas.