#earningsseason
Ripple CTO Emeritus Revisits Gensler’s 2020 AI Warning
Ripple CTO Emeritus David Schwartz revisited Gary Gensler’s 2020 AI paper, agreeing with much of its concern about financial risk.
The paper warned that widespread deep-learning adoption could make markets more fragile if institutions rely on similar models, data and optimization strategies.
Schwartz questioned whether smarter systems would make irrational decisions, shifting attention toward correlated behavior, incentives and how autonomous agents could affect financial stability at scale.
Ripple CTO Emeritus David Schwartz has weighed in on a resurfaced 2020 paper co-authored by former SEC Chair Gary Gensler on AI and financial stability. Schwartz said much of the argument made sense, while questioning the idea that capable systems would become smart enough to behave irrationally. His response revives a debate over whether widespread AI adoption could create financial risks through synchronized decision-making. The discussion arrives as AI agents interact with financial infrastructure rather than remaining limited to research
AI Agents Revive Gensler’s Financial Stability Warning
Gensler co-authored the paper, titled “Deep Learning and Financial Stability,” with Lily Bailey in November 2020, before becoming SEC chair. The research argued that deep learning adoption across finance could create fragility if institutions relied on similar models, data and optimization strategies. The concern was less about individual algorithms failing and more about many systems reacting similarly at the same time. That possibility has become more relevant as AI agents move toward autonomous financial activity, including investing, payments and portfolio manage#ment.
The discussion also referenced concerns that autonomous agents could rapidly shift deposits or investments when optimizing returns, amplifying stress during market disruptions. Schwartz appeared to accept the coordination risk while rejecting the idea that greater intelligence naturally lead
Ripple CTO Emeritus Revisits Gensler’s 2020 AI Warning
Ripple CTO Emeritus David Schwartz revisited Gary Gensler’s 2020 AI paper, agreeing with much of its concern about financial risk.
The paper warned that widespread deep-learning adoption could make markets more fragile if institutions rely on similar models, data and optimization strategies.
Schwartz questioned whether smarter systems would make irrational decisions, shifting attention toward correlated behavior, incentives and how autonomous agents could affect financial stability at scale.
Ripple CTO Emeritus David Schwartz has weighed in on a resurfaced 2020 paper co-authored by former SEC Chair Gary Gensler on AI and financial stability. Schwartz said much of the argument made sense, while questioning the idea that capable systems would become smart enough to behave irrationally. His response revives a debate over whether widespread AI adoption could create financial risks through synchronized decision-making. The discussion arrives as AI agents interact with financial infrastructure rather than remaining limited to research
AI Agents Revive Gensler’s Financial Stability Warning
Gensler co-authored the paper, titled “Deep Learning and Financial Stability,” with Lily Bailey in November 2020, before becoming SEC chair. The research argued that deep learning adoption across finance could create fragility if institutions relied on similar models, data and optimization strategies. The concern was less about individual algorithms failing and more about many systems reacting similarly at the same time. That possibility has become more relevant as AI agents move toward autonomous financial activity, including investing, payments and portfolio manage#ment.
The discussion also referenced concerns that autonomous agents could rapidly shift deposits or investments when optimizing returns, amplifying stress during market disruptions. Schwartz appeared to accept the coordination risk while rejecting the idea that greater intelligence naturally lead
