AI Experiments: The New Frontier with Old Problems

The explosion of large language models and autonomous AI agents has sparked a new trend. Researchers are now using AI as stand-ins for humans in studies about decision-making and social interactions. But with AI taking on roles that impact real-life decisions, understanding their behavior isn't just important, it's important.

AI as Proxies: More than Just Cost-Efficient

Let’s face it, AI agents offer a lot. They're scalable, cost-effective, and they bring experimental control to a whole new level. But there's a catch. These experiments come with their own baggage of methodological issues, some even worse than those in human research. AI may be fast, but it's not flawless.

Enter Preregistration: A Solution?

Preregistration is being touted as the remedy for these issues. If it works for human subjects, why not for AI experiments too? The argument is that by laying out your research plans in advance, you can sidestep the traps of flexible research choices. Model selection, prompt wording, settings, they all can be gamed without clear reporting norms. Without preregistration, who's keeping track?

Time to Step Up

Here's the crux: Conferences, journals, funding agencies, it's time they step up and demand preregistration for AI experiments. This isn't just about adding another layer of bureaucracy. It's about ensuring that the new age of AI research doesn't repeat the mistakes of the past. If the scientific community doesn't act now, are we just setting ourselves up for another replication crisis?