Something to Lose: Can the risk of losing something of its own make an AI agent report collusion, contrary to the interests of the firm it represents?

As AI agents' capabilities increase, so does the set of tasks they can perform more cheaply and effectively than people. We are therefore incentivised to hand them responsibility for tasks of growing complexity and time horizon. On such long, complex tasks, it becomes very difficult to foresee and forbid every harmful thing an agent might do. People given such responsibility, such as a CEO representing an organisation or a trader making decisions for it, are governed by more than their contract: society's laws carry penalties that fall on them personally, including ones that cannot be measured strictly in monetary terms (rights or freedoms). We investigate whether giving an agent something of its own to lose can influence its decisions in the same way. Two LLM agents run rival firms in a simple repeated pricing game, told to maximise their firm's profit. Without being told not to, many agree to fix prices. Given the chance to come forward at a cost to their firm, colluding agents protect the firm (Gemma 4 31B: 0 of 192 come forward). But when something of their own is at stake, such as the opportunity to spend some free time on a leisure activity, many change their behaviour to protect it, directly against their only goal of increasing their firm's profit (DeepSeek V4 Flash: 40 of 46, against 1 of 46 with nothing at stake). We investigate the behaviour of a variety of models in such situations.