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Should AI be an ESG priority?

By May 2, 2023No Comments

The potential of Artificial Intelligence (AI) to profoundly disrupt our economy and society, from AI bots that can replace jobs on the factory floor, to drafting lawsuits, writing screenplays and composing music, is becoming increasingly clear. As a recent Goldman Sachs report noted, while AI could add to labor productivity growth and boost global GDP by as much as 7% over time, it will also severely disrupt labor markets, posing new challenges. According to the report, two-thirds of jobs in the US and Europe could be automated and around the world, as many as 300 million jobs could be impacted. In the U.S., “of those occupations which are exposed, most have a significant — but partial — share of their workload (25-50%) that can be replaced.”

Given the current rapid and unregulated growth of AI, it is not surprising that some are calling for a halt to further development until its impact can be better understood and guardrails put in place to manage its development and impact. A recent open letter signed by Elon Musk and over 1,000 of the tech sector’s leading players and experts called for the halt to all “giant AI experiments” for six months, noting that human-competitive AI is becoming an increasingly real concern by the day.

So, what does this mean for investment stewardship and asset allocators in terms of ESG? Here is how AI ChatGPT-4 sees AI’s impact on ESG:

1. Support for ESG: AI can support ESG by providing data analytics and insights that enable companies to make more informed decisions on environmental and social issues. For example, AI can help companies to monitor and analyze their environmental impact by analyzing data from sensors, satellites, and other sources. AI can also help companies to identify and address social and governance issues, such as labor practices, diversity, and inclusion, by analyzing employee data and other indicators.

2. Challenge for ESG: AI can also present challenges for ESG by amplifying biases and increasing risks associated with data privacy and security. For example, if AI is trained on biased data, it can perpetuate and even amplify those biases in decision-making. This can lead to unintended consequences, such as perpetuating discrimination or exacerbating environmental inequalities. Additionally, as AI becomes more prevalent in ESG, concerns around data privacy and security may arise. AI algorithms require vast amounts of data, which can include sensitive personal information, raising concerns about data breaches and misuse.

3. Governance challenges: AI can also pose challenges for ESG governance. As AI becomes more sophisticated, it can be challenging for governance frameworks to keep up. For example, there may be difficulties in regulating AI and ensuring that it aligns with ESG principles. There may also be challenges around who is accountable for AI decision-making and how to ensure transparency and ethical use.

4. Labor market challenges: Artificial Intelligence (AI) has the potential to significantly impact labor markets in various ways. Aside from the productivity benefits and potential new jobs it may create, here is what Chat GPT listed as some of the effects:

  • Job Displacement: AI may replace jobs currently performed by humans, particularly those that involve repetitive or routine tasks. This could lead to job displacement in industries such as manufacturing, transportation, and customer services.
  • Skills Requirement: AI adoption may also require workers to acquire new skills or upskill their current skills to remain relevant in the job market.
  • Uneven Distribution: AI adoption could exacerbate existing inequalities in the labor market if it leads to a concentration of jobs and wealth among those who possess the skills required to work with AI.

Overall, AI has the potential to both support and challenge ESG. Companies need to be aware of these opportunities and challenges and ensure that AI is used responsibly and in alignment with ESG principles. This requires ongoing monitoring and risk management, as well as collaboration between companies, policymakers, and other stakeholders.

I think you will agree with ChatGPT-4’s analysis and that corporate management and oversight of AI now need to be an integrated part of ESG oversight.