Measuring an artificial intelligence agent's trust in humans using machine incentives

Understand

Scientists and philosophers have debated whether humans can trust advanced artificial intelligence (AI) agents to respect humanity's best interests.

• Yet what about the reverse? Will advanced AI agents trust humans? Gauging an AI agent's trust in humans is challenging because--absent costs for dishonesty--such agents might respond falsely about their trust in humans.
• Here we present a method for incentivizing machine decisions without altering an AI agent's underlying algorithms or goal orientation.
• In two separate experiments, we then employ this method in hundreds of trust games between an AI agent (a Large Language Model (LLM) from OpenAI) and a human experimenter (author TJ).