Guy Courtin, Forbes.com, February 28, 2024
Large language models (LLMs), natural language processing (NLP), machine learning (ML), cognitive AI and a litany of other “hot” artificial intelligence technologies have flooded our discussions since early 2023. From media coverage to overzealous CEOs, the message ringing in our ears is clear—get on the AI train or be left behind.
From helping solve your supply chain planning problems and enhancing customer service to improving patient care, determining better product mixes and reducing the number of HR memos, AI has been bellowed from the rooftops as the next elixir to all our ills. There’s no doubt that AI holds great opportunities for businesses and society but at what cost? And how does it impact another hot topic—sustainability?
A Hidden Conflict?
How soon we forget. Environmental, social and governance (ESG) responsibility—or sustainability—was once the subject of every headline. It was deemed a vital business driver and commanded above-the-fold ink not that long ago. However, being more sustainable remains an elusive target. Companies across all industries are striving to better understand, control and reach sustainable levels. Providing more transparency and reporting on ESG will soon become a requirement for publicly traded companies.
Is there a conflict between these two trends? Potentially. By some accounts, the environmental footprint needed to train OpenAI’s GPT-3 was the equivalent of “driving a car to the moon and back”—480,000 miles—and evaporating 700,000 liters of freshwater. Amplify that by the number of queries that are being pumped through LLMs like ChatGPT and the necessary computation power needed and the ecological toll becomes clear. However, there’s a fine line that companies can walk to leverage AI and still uphold their ESG commitments. Here’s what companies need to consider when it comes to ensuring AI efforts don’t conflict with ESG goals.
