Researchers are advocating for the use of experimental methods to better predict how future technologies will influence human behavior, according to a perspective article published in Nature (Rahwan et al., 2025). The article highlights the potential of these methods to provide insights into the complex interplay between technology and human decision-making.

The authors, led by Iyad Rahwan, argue that understanding this interplay is crucial as technology becomes increasingly integrated into daily life. They propose employing techniques such as controlled experiments and simulations to model how individuals and groups might respond to new technological advancements. This approach, they suggest, could help anticipate both the positive and negative consequences of technological adoption.

However, some researchers point out limitations to this approach. One angle not covered in the perspective article is how encounters with new technologies can transform users' values and preferences in ways that are impossible to predict, according to L. A. Paul in "Transformative Experience" (Oxford Univ. Press, 2014). This suggests that while experimental methods can offer valuable insights, they may not fully capture the dynamic and evolving nature of human behavior in response to technology.

The Nature article also references a related article, published in Nature (Nature 649, 827 (2026) doi: https:doi.org10.1038d41586-026-00209-4), which discusses the impact of artificial intelligence on the economy and the need for a comprehensive understanding of its effects. This underscores the broader context of the research, which aims to address the societal implications of emerging technologies.

The call for experimental methods in predicting technological impact reflects a growing recognition of the need for proactive strategies in managing technological change. By anticipating potential behavioral shifts, policymakers and industry leaders can develop more effective policies and products that align with human values and promote positive outcomes. The ongoing research in this area is expected to contribute to a more informed and responsible approach to technological innovation.