A defense attorney, Sarah, is representing a client accused of insider trading under the Securities Exchange Act of 1934. The case hinges on whether her client, a mid-level executive, acted on non-public information to trade company stocks. With only a week before the trial, Sarah uses an AI legal research tool to find relevant case law that could support a defense of insufficient evidence of intent. The AI identifies United States v. Smith, a case where the defendant was acquitted of insider trading due to a lack of clear evidence showing intent to defraud. Trusting the AI's summary, Sarah incorporates the Smith precedent into her defense strategy, arguing that her client similarly lacked the intent to commit fraud. However, the AI missed a crucial detail: United States v. Smith was a state-level case with specific local securities laws that differ significantly from federal laws. Additionally, the ruling had been partially overturned in a higher court, which the AI failed to flag. When Sarah presents this precedent in court, the prosecution quickly points out the case's inapplicability, severely undermining her argument. This misstep weakens Sarah’s defense, and the client faces a much higher risk of conviction.
