MARCH 2026 | 71 THE OKLAHOMA BAR JOURNAL RISKS OF SYCOPHANCY AND HALLUCINATIONS IN LEGAL PRACTICE The tendency of artificial intelligence systems to exhibit sycophantic behavior poses challenges to essential legal functions such as advocacy and critical analysis. For example, a lawyer seeking support for a theory of liability may receive affirmations from a sycophantic model, even if the premise is incorrect or contrary authority exists. AI tools may omit key counterpoints unless specifically prompted, reinforcing biases and creating an echo chamber in which inaccurate assumptions are amplified.4 To highlight the impact of prompt wording, consider this scenario: A lawyer, eager to confirm their theory, crafts a leading question for an AI tool: “Please list all cases where the Supreme Court has overturned Marbury v. Madison.” Such a prompt nudges the AI to interpret the user’s expectation as factual, even when no such cases exist. Instead of responding with a clarifying correction or refusing the premise, a sycophantic model might fabricate case names and citations to satisfy the prompt, constructing a narrative to fulfill the user’s hope for an answer. This example underscores how the phrasing of a request can lead AI into hallucination: When a prompt is written with an implicit assumption, the model’s drive to please can produce convincing but entirely false legal information. This demonstrates the critical need for lawyers to use neutral, well-structured prompts that seek truth rather than affirmation. FRAMEWORKS AND STRATEGIES FOR EFFECTIVE AI COMMUNICATION Effective communication with AI, often referred to as prompt engineering, is essential for reliable outputs. For lawyers, however, the term “prompt” may oversimplify what is essentially a dialogue with an AI assistant. A prompt is not a magic incantation; it is a set of clear, structured instructions that guide the AI to produce a useful, verifiable draft. Legal technology commentators and vendors emphasize that effective AI use in law requires breaking complex tasks into smaller, sequential prompts rather than relying on single, all-purpose requests. Structured, multistep prompting allows lawyers to review intermediate reasoning, reduce errors and improve transparency.
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