We should bridge the AI-human trust gap on ESG reporting
For every AI action, there is awe that goes with an equal and opposite reaction of scepticism.’ This is how Newton’s third law might be rewritten for artificial intelligence (AI). That there exists a trust gap on all things AI is a reality; equally, there is blind acceptance of much that AI delivers. Among the early adopters of AI are organizations using it for Environmental, Social and Governance (ESG) reports.
As regulatory demands rise to report detailed ESG metrics with qualitative management commentary, there is a scramble to train human talent in those aspects. However, much of the ESG assessment, by way of data collation and analysis for example, can be automated. This explains the debate on whether AI-generated reports can match the quality and trustworthiness of those made by humans.
The pro-AI point: Advocates of AI-generated ESG reports argue that AI offers unparalleled efficiency, accuracy and scalability. AI algorithms can process vast amounts of data, detect patterns and identify relevant ESG metrics with minimal human intervention. Further, AI-powered analytics can uncover hidden correlations and predictive insights, enabling organizations to address emerging ESG issues proactively.
Moreover, AI eliminates biases inherent in human decision-making, enhancing objectivity and consistency in report generation. Of course, AI will carry any bias that human-made learning material has pre-loaded it with. Still, AI-driven insights enable organizations to identify ESG risks and opportunities more effectively, thereby enhancing transparency and accountability.
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