When advanced AI systems are being developed, the people most motivated to work on them often have strong optimism about the technology's benefits. This creates a potential blind spot—their enthusiasm might lead them to overlook risks or overestimate positive outcomes. The result could be AI systems built without adequate safeguards, posing significant long-term dangers. Investigating this "motivation-based optimism bias" could help make AI development safer and more balanced.

How Optimism Shapes AI Development

The core hypothesis is that AI researchers, especially those working on highly advanced systems, tend to be more optimistic than the general population about the technology's benefits and risks. One way to test this would be:

• Surveying AI researchers about their expectations for future AI systems and comparing their responses to control groups
• Analyzing whether more optimistic researchers are more likely to work on risky AI projects
• Examining public statements from leading AI labs for patterns of optimism versus caution

Potential Applications of Findings

If significant optimism bias is found, several approaches could help create more balanced AI development:

• Diversifying AI teams to include members with different risk perspectives
• Developing training programs to help researchers recognize cognitive biases
• Creating evaluation frameworks that systematically assess risks alongside benefits

Getting Started With Research

A simple way to begin would be conducting anonymous surveys at AI conferences, asking researchers to estimate both potential benefits and risks of advanced AI. Subsequent phases could include more controlled experiments and analysis of existing research teams' composition and output. The results could inform both organizational practices and potential policy guidelines for AI safety.

This type of research could provide concrete data about how psychological factors influence one of the most important technological developments of our time, potentially leading to safer approaches to building advanced AI systems.