Abstract
Americans are often reluctant to support policies that aim to meaningfully change transportation. Here we show how new techniques from artificial intelligence can be harnessed to increase public support for green policies. We use text-to-image generative AI models to create re-imagined, car-free versions of various streets in America and find that across two large-scale survey studies (N = 3,129), viewing these re-imaginations significantly increases support for a hypothetical sustainable transport bill.
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Data availability
Anonymized participant data for all our experiments are available at https://github.com/rachit-dubey/car-free-america.
Code availability
The code to run the analyses and reproduce the figures is available on GitHub at https://github.com/rachit-dubey/car-free-america.
References
Pucher, J. & Lefèvre, C. in The Urban Transport Crisis in Europe and North America 175–200 (Palgrave Macmillan, 1996).
Saeidizand, P., Fransen, K. & Boussauw, K. Revisiting car dependency: a worldwide analysis of car travel in global metropolitan areas. Cities 120, 103467 (2022).
Kenworthy, J. R. Transport energy use and greenhouse gases in urban passenger transport systems: A study of 84 global cities. In International Sustainability Conference 1–28 (Institute for Sustainability and Technology Policy, Murdoch Univ., 2003).
Moody, J., Farr, E., Papagelis, M. & Keith, D. R. The value of car ownership and use in the United States. Nat. Sustain. 4, 769–774 (2021).
Jakle, J. A. & Sculle, K. A. Lots of Parking: Land Use in a Car Culture (Univ. Virginia Press, 2004).
Axsen, J., Plötz, P. & Wolinetz, M. Crafting strong, integrated policy mixes for deep CO2 mitigation in road transport. Nat. Clim. Change 10, 809–818 (2020).
Milovanoff, A., Posen, I. D. & MacLean, H. L. Electrification of light-duty vehicle fleet alone will not meet mitigation targets. Nat. Clim. Change 10, 1102–1107 (2020).
Rosenfield, A., Attanucci, J. P. & Zhao, J. A randomized controlled trial in travel demand management. Transportation 47, 1907–1932 (2020).
Kristal, A. S. & Whillans, A. V. What we can learn from five naturalistic field experiments that failed to shift commuter behaviour. Nat. Hum. Behav. 4, 169–176 (2020).
Gössling, S. Why cities need to take road space from cars-and how this could be done. J. Urban Des. 25, 443–448 (2020).
Nall, C.The Road to Inequality: How the Federal Highway Program Polarized America and Undermined Cities (Cambridge Univ. Press, 2018).
Klein, N. J., Ralph, K., Thigpen, C. & Brown, A. Political partisanship and transportation reform. J. Am. Plann. Assoc. 88, 163–178 (2022).
Taylor, S. E., Pham, L. B., Rivkin, I. D. & Armor, D. A. Harnessing the imagination: mental simulation, self-regulation, and coping. Am. Psychol. 53, 429–439 (1998).
Rojas-Padilla, E., Metze, T. & Termeer, K. Seeing the visual: a literature review on why and how policy scholars would do well to study influential visualizations. Policy Stud. Yearb. 12, 103–136 (2022).
Elder, R. S. & Krishna, A. The ‘visual depiction effect’ in advertising: facilitating embodied mental simulation through product orientation. J. Consum. Res. 38, 988–1003 (2012).
Petrova, P. K. & Cialdini, R. B. in Handbook of Consumer Psychology (eds Haugtvedt, C. P. et al.) 510–528 (Routledge, 2018).
Metze, T. Visualization in environmental policy and planning: a systematic review and research agenda. J. Environ. Policy Plan. 22, 745–760 (2020).
Luo, Y. & Zhao, J. Attentional and perceptual biases of climate change. Curr. Opin. Behav. Sci. 42, 22–26 (2021).
Stanford, C. The 15-minute city: where urban planning meets conspiracy theories. The New York Times https://www.nytimes.com/2023/03/01/world/europe/15-minute-city-conspiracy.html (2023).
Nixon, H. & Agrawal, A. W. Would americans pay more in taxes for better transportation? Answers from seven years of national survey data. Transportation 46, 819–840 (2019).
McCright, A. M., Charters, M., Dentzman, K. & Dietz, T. Examining the effectiveness of climate change frames in the face of a climate change denial counter-frame. Top. Cogn. Sci. 8, 76–97 (2016).
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C. & Chen, M. Hierarchical text-conditional image generation with clip latents. Preprint at https://doi.org/10.48550/arXiv.2204.06125 (2022).
Rombach, R., Blattmann, A., Lorenz, D., Esser, P. & Ommer, B. High-resolution image synthesis with latent diffusion models. In Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition 10674–10685 (IEEE, 2022).
Acknowledgements
We thank E. Kreiss, D. Yu, L. Globig and J. Peterson for valuable comments and feedback, and Z. Katz (Better Streets AI) for providing the prompts to generate car-free versions of American streets using Dall-E 2. Special thanks to Rethink35 team for providing valuable feedback and inputs on the images we generated using Stable Diffusion. This work was supported by funds from the NOMIS foundation.
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R.D. and M.D.H. developed the study concept. R.D. wrote the software, conducted experiments and analysed the data. T.L.G. and R.B. supervised the study design and data analysis. All authors discussed the results. R.D. drafted the paper, and M.D.H., T.L.G. and R.B. provided critical revisions. All authors approved the final version of the paper for submission.
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Nature Sustainability thanks Maria Luce Lupetti, Tamara Metze and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Supplementary Figs. 1–3, Results for Study 1 and Results for Study 2.
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Dubey, R., Hardy, M.D., Griffiths, T.L. et al. AI-generated visuals of car-free US cities help improve support for sustainable policies. Nat Sustain 7, 399–403 (2024). https://doi.org/10.1038/s41893-024-01299-6
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DOI: https://doi.org/10.1038/s41893-024-01299-6
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