Generative AI for ESG Reporting

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Explores the use of generative AI for enhancing Environmental, Social, and Governance (ESG) reporting practices. The document outlines various applications of generative AI across different aspects of ESG reporting, including data collection, analysis, risk assessment, and report generation. It also discusses the benefits and challenges of integrating AI into ESG reporting, emphasizing the importance of responsible implementation and ethical considerations, including mitigating bias and ensuring transparency

2024/10/26

Generative AI and ESG Reporting

Explores the use of generative AI for enhancing Environmental, Social, and Governance (ESG) reporting practices. The document outlines various applications of generative AI across different aspects of ESG reporting, including data collection, analysis, risk assessment, and report generation. It also discusses the benefits and challenges of integrating AI into ESG reporting, emphasizing the importance of responsible implementation and ethical considerations, including mitigating bias and ensuring transparency

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The ISO/IEC 23894:2023 standard is a guide for organizations to manage the risks associated with artificial intelligence systems. The standard provides a framework for identifying, assessing, and mitigating risks throughout the AI system lifecycle. It covers a wide range of topics, including data quality, algorithmic transparency, bias mitigation, ethical oversight, adversarial resilience, and governance

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Explores the use of generative AI for enhancing Environmental, Social, and Governance (ESG) reporting practices. The document outlines various applications of generative AI across different aspects of ESG reporting, including data collection, analysis, risk assessment, and report generation. It also discusses the benefits and challenges of integrating AI into ESG reporting, emphasizing the importance of responsible implementation and ethical considerations, including mitigating bias and ensuring transparency