By Suzanne Cosgrove
SEC Chairman Gary Gensler was enthusiastic about the promise of AI in remarks Monday at the National Press Club luncheon, stating AI could open up opportunities from healthcare to science to finance, the SEC chairman said. As machines take on pattern recognition, AI can create greater efficiencies across the economy, he said.
“Text prediction in our mobile devices and emails has been commonplace for years,” he noted. “It’s being used for natural language processing, translation software, recommender systems, radiology, robotics, and your virtual assistant. … In finance, AI already is being used for call centers, account openings, compliance programs, trading algorithms, sentiment analysis, and more. It’s also fueled a rapid change in the field of robo-advisers and brokerage apps.”
Focused on outcomes, not tech. However, the SEC itself is technology neutral, Gensler said. The regulator is focused on the outcomes, rather than the tool itself. Within its current authorities, the Commission is focused on protecting against certain of its challenges, he said.
Those concerns are twofold, with the first related to “narrowcasting” or the micro abilities of AI-based models to make predictions about individuals. That ability raises issues, such as bias, that are not necessarily new to AI but are magnified by it, Gensler said.
“The challenges of explainability may mask underlying systemic racism and bias in AI predictive models,” he cautioned. “The ability of these predictive models to predict doesn’t mean they are always accurate or robust.
On guard against fraud. “As advisers and brokers incorporate these technologies in their services, the advice and recommendations they offer—whether or not based on AI—must be in the best interests of the clients and retail customer and not place their interests ahead of investors’ interests,” Gensler added.
“Since antiquity, bad actors have found new ways to deceive the public. With AI, fraudsters have a new tool to exploit,” he said. “They may try to do it in a narrowcasting way, zeroing in on our personal vulnerabilities.”
Social impact looms large. AI challenges also go beyond the scope of narrowcasting to take on a broader social significance, Gensler said. “Just as with historic transformative times of moving to more automation of the farm, factory, and services, there will be macro challenges for society in general,” he said.
“Given that today's AI relies on an insatiable demand for data and computational power, there can be economies of scale and data network effects at play, Gensler said. “We’ve already seen companies, both incumbents and startups, relying on base or foundation AI models and building applications on top of them. …Once again, this raises a host of issues that are not new to AI but may be accentuated by it,” and in this case involve privacy and intellectual property concerns.”
The SEC’s role. For the SEC, the challenge here is to promote competitive, efficient markets in the face of what could be dominant base layers at the center of the capital markets, Gensler said. “I believe we closely have to assess this so that we can continue to promote competition, transparency, and fair access to markets.”