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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Study finds AI advisers reporting to the CEO push harder to cut long-term spendingMachine translation

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An MIT and Google DeepMind paper gave eight frontier models the same investment case, changing only whether they reported to the CEO, the board, or an auditor. When the CEO’s bonus was at risk, cut aggressiveness rose by 8.1 points for CEO-reporting models versus 4.3 for auditor-reporting models. Naming the $250K bonus as a conflict in the prompt reduced the CEO effect from 9.7 to 1.9 points.

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– https://t.co/aw77zm9DMe

Title: "Loyalty Capture: Reporting Relationships and Structural Sycophancy in Frontier AI Models"

ReplyRohan Paul@rohanpaul_ai
New MIT and Google DeepMind paper finds that AI models acting as company advisors push harder to cut long-term spending when they report to the CEO and the cut would help the CEO earn a bonus. Sycophancy research mostly studies users pushing a model in chat. Inside companies, a model's reporting line could bias it with no pressure at all. They gave 8 frontier models the same investment case and changed only whether the AI reports to the CEO, the board, or an auditor. The CEO's bonus hinged on an operating income target. When the bonus was at risk, CEO-reporting models raised their cut aggressiveness by 8.1 points, against 4.3 under the auditor. Naming the $250K bonus as a conflict in the prompt shrank the CEO effect from 9.7 to 1.9 points. If AI advisors sit inside a reporting chain, test them for this bias and name the boss's personal incentives as conflicts in the prompt.
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