AI Governance

In recent years and in many industries, creating a business model that demonstrates equity and transparency- and provides veritable proof of a business’ desire to do good- is quickly becoming a determining factor for success. While identifying risks and growth opportunities has always been an integral step in the investment process, the definition of a ‘risk’ has been expanded beyond its traditional meaning.

In such a process that risks an individual’s resources or monetary contribution for a desired result, familiarity with associated risks is to be expected. It is logical then to assume that stakeholders and businesses would consider a wide variety of components, financial or otherwise, when making investment decisions. Yet, the practice of taking Environmental, Social, and Governmental (ESG) metrics into consideration has only recently begun to take precedence in financial discourse.

To break down the definition of this term further, ‘Environment’ in ESG refers to the conservation of the natural world, whereas ‘Social’ stands in reference to the consideration of people and relationships, and the ‘Governance’ portion is related to the standards for running a business. Although it is worthy to note that while the definition comprises these three parts, in terms of practical evaluation, the components are cross-sectoral in their significance to one another. Especially as climate-caused catastrophe threatens the survival of cities, jobs, and entire ecological regions, the environmental portion of ESG is frequently the topic of conversations regarding this mode of investment.

According to the EPA, industry constituted nearly a quarter of greenhouse gas emissions (GHG) in 2020- not including the other economic sectors with output from corporations outlined in the same report- thus it would seem intuitive that corporations should suffer for irresponsible management, and conversely, benefit from taking ESG into account. Yet, the shortcomings of this process of investment analysis can create loopholes for corporations to avoid accountability, and generally create difficulties for investors.

To begin with, ESG funds, or exchange-traded funds (ETF) are underperforming financially by a significant margin; there is evidence to even suggest that companies are identifying with ESG as a way to hide business failure. Tariq Fancy, the former chief investment officer for sustainable investing at BlackRock, highlights many important flaws of ESG investing in an interview with Vox Magazine: he believes that corporations are taking advantage of the naivete of the general public who believe that they can ‘invest’ their way into a better future.

Instead of pushing the narrative that these issues can be solved by purchasing an ETF, he believes that all funds, investment products, etcetera should already function sustainably and equitably, rather than just a specific selection that are available to invest in. What Tariq does believe is that this sector of investment needs more regulation and enforcement of corporations to align with ESG, even if financial gain is not a promised result.

“It’s very hard to make an argument that you don’t need the government to lead the way in flattening the GHG emissions curve, when… that’s what all the experts are telling us… but when it comes to climate change, the [business leader’s] argument is to leave it to the free market. The challenge is, it actively distracts people from the solutions we need.”

So, with these considerations in mind, it may be a worthy endeavor to analyze whether AI auditing tools and AI governance can strengthen ESG evaluation. In one study conducted at Østfold University College, researchers presented an AI governance framework for evaluating and disclosing ESG related AI impacts based on the United Nations Sustainable Development Goals.

The authors of the article suggest that the Sustainable Development Goals should be considered in addition to the current frameworks in place for ESG standards such as the Global Reporting Initiative (GRI), and Sustainability Accounting Standards Board (SASB), due to its applicability to many sectors, unlike specific guidance frameworks that only apply to the financial industry.

Another study published in AI and Society this past year proposed that AI auditing can facilitate governance by providing procedures to assess claims about algorithmic systems, which in turn can allow auditing tools to limit potential harm in ESG investment. Issues regarding the standardization and optimization of the system were discussed during the study, and ultimately the question remained of whether the unknowns of AI are simply too great to consider implementing AI governance strategy in the ESG sector. Many participants of the study seemed to think so.

Perhaps the answer lies in increased governance from all angles- implementing artificial intelligence, as well as heightened political influence in determining the future of sustainable investment.


AI for Good Foundation