SEC Warns of AI-Panic in Financial Markets and Institutions
The SEC has raised concerns about the impact of generative AI and chatbots on financial markets and institutions, warning of potential market panic.
- SEC stresses the need to address the challenges posed by AI while recognizing its transformative potential.
- SEC Chair Gary Gensler warns of financial institutions making decisions based on flawed information provided by AI models.
- The concerns align with broader discussions on privacy, intellectual property, bias, and robustness in AI systems.
On July 17th, the US Securities and Exchange Commission (SEC) raised concerns about the impact of generative AI and chatbots on financial markets and institutions.
SEC Chair Gary Gensler delivered a speech at the National Press Club, emphasizing the potential risks associated with the increasing reliance on generative AI and the concentration of data and computing power in a few tech platforms.
Gensler warned financial markets and institutions from basing their decisions on inaccurate or irrelevant information provided by AI models, “If a model provides inaccurate or irrelevant information, financial institutions may end up using the same flawed data and making the same bad decisions.” He drew parallels between the 2008 financial crisis, where banks played “follow the leader” based on flawed information from credit raters, and the potential risks of a centralized dataset or model in the finance sector.
Gensler expressed concern that the rise of generative AI and other deep-learning models could exacerbate the interconnectedness of the global financial system and promote herding behavior among market participants. He expressed concern about AI’s potential to heighten financial fragility, stating, “AI may promote herding with individual actors making similar decisions because they are getting the same signal from a base model or data aggregator.” Gensler cautioned that this could encourage monocultures and further concentrate systemic risk.
While acknowledging the financial sector’s AI use, Gensler specifically focused on large language models (LLMs) and called generative AI and LLMs the “most transformative technology of our time.” He stressed the need to update risk management guidelines and called for a broader industry-wide reconsideration of how AI technology is utilized in finance.
This is not the first time Gensler has voiced concerns about AI’s impact on financial markets and institutions. In a paper written while he was at MIT, Deep Learning and Financial Stability, Gensler explored the regulatory challenges posed by using AI in finance. The SEC has also been actively engaged in AI-related issues, establishing the FinHub resource center in 2018 to address questions surrounding AI, cryptocurrencies, and other fintech-related matters. The SEC itself employs machine learning for market surveillance to enforce its policies.
The SEC’s warning comes as chatbots like ChatGPT gain popularity in disseminating financial information on social media. The SEC expressed worries about financial markets and institutions relying on the same subset of information for decision-making, potentially leading to financial instability. Gensler cautioned that the dominance of a few AI platforms in the market could pose challenges to financial stability.
The SEC’s concerns align with broader discussions on AI’s implications for privacy, intellectual property, bias, and robustness. Gensler highlighted the difficulty of explaining AI models’ decisions, potential biases, and the risk of deception and fraud facilitated by AI technology. He also emphasized the macro-level challenges, such as the potential for job market disruption and the concentration of power in AI platforms.
Gensler concluded by stating that the SEC remains technology-neutral but focused on addressing the micro and macro challenges presented by AI. While recognizing the transformative potential of AI, he stressed the importance of considering its risks and called for a system-wide rethink on policy interventions for maintaining financial stability.
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