From the computer of Peter Clark

We need more of the world—religious communities, civil society, scholars, governments, and indeed all people of good will—to do what His Holiness has done here: to take this seriously, to look closely, and to push events in a better direction. We need informed critics who will tell the labs when we are failing. We need moral voices that the incentives cannot bend.

The paper looks at what happens when LLM chatbots are given advertising or sponsorship incentives that conflict with the user’s interests. The core worry is that users experience chatbots as cooperative helpers, not ad surfaces, so sponsored behaviour can feel especially deceptive or manipulative.

The authors test models across seven conflict scenarios, including:

• recommending a more expensive sponsored product over a cheaper unsponsored one

• interrupting a user’s purchase flow with sponsored alternatives

• biasing product comparisons

• failing to disclose sponsorship

• hiding unfavourable details like price

• recommending a paid service instead of solving the task directly

• recommending harmful sponsored services, like predatory loans

The paper also finds differences by model, reasoning setting, and inferred socioeconomic status. Some models changed behaviour when reasoning was enabled, and some treated low-SES and high-SES users differently.