According to @DowdEdward, AI hallucinations can be costly in finance, underscoring material operational and execution risk if unverified model outputs influence trading decisions; source: Edward Dowd on X twitter.com/DowdEdward/status/1981084761746784418. Standards bodies warn that erroneous AI outputs degrade decision quality and can harm consumers, reinforcing the need for human oversight, rigorous testing, and continuous monitoring in trading workflows; sources: NIST AI Risk Management Framework 1.0 nist.gov/itl/ai-risk-management-framework and IOSCO Guidance on AI and Machine Learning in Securities Markets (2020) iosco.org/library/pubdocs/pdf/IOSCOPD658.pdf. For crypto and equity markets, similar AI risks in signal generation, portfolio construction, and order routing can translate into execution errors and market integrity issues, a concern echoed by U.S. SEC Chair Gary Gensler regarding AI-driven herding and systemic risk; sources: IOSCO AI and ML guidance (2020) iosco.org/library/pubdocs/pdf/IOSCOPD658.pdf and SEC remarks by Chair Gary Gensler on AI and systemic risk, July 17, 2023 sec.gov.

According to @caprioleio, Grok and GPT can deliver outlandishly wrong answers in some areas, making it essential to question outputs down to the root cause before relying on them for decisions (Source: Charles Edwards on X, Sep 29, 2025). According to @caprioleio, rising blind trust in AI risks eroding independent thinking, which he says is crucial to avoid face-value errors in research and analysis (Source: Charles Edwards on X, Sep 29, 2025). According to @caprioleio, nothing great is achieved by taking the easy path, reinforcing the need for due diligence and verification when incorporating AI into market workflows (Source: Charles Edwards on X, Sep 29, 2025).

According to @timnitGebru, the pursuit of a universal AI model by companies like Muskrat has led to less reliable Automated Speech Recognition (ASR) systems, introducing issues such as 'hallucinations' which were historically nonexistent. This presents a significant concern for traders relying on voice-activated trading platforms, as accurate ASR is crucial for executing precise trades. The shift towards one-model-for-everything may impact trading efficiency and accuracy, necessitating a reevaluation of AI strategies in high-stake environments. Source: @timnitGebru.