My research interests focus on developing tools and methods that can help policy makers engage their residents in constructive and nuanced ways. I work with policy makers who have an interest in engaging residents or stakeholders in a decision, in order to study how real people can engage with questions they really care about.
See also my ORCID overview
Over the past years we have built the Stanford Platform for Online Deliberation which is able to scale the organization of small-group deliberations with a structures agenda to about 1500 people across 150 groups at the same time, without the need for human moderators. We have deployed the platform in dozens of deliberative polls in many languages and countries, with more than 20,000 unique participants, deliberating collectively more than 50,000 hours. The platform is a collaboration between the Crowdsourced Democracy Team and the Deliberative Democracy Lab, both at Stanford University.
See especially: Achieving Parity with Human Moderators: A Self-Moderating Platform for Online Deliberation (2023)
See also: Estimating Contribution Quality in Online Deliberations Using a Large Language Model (2024)
With the Stanford Participatory Budgeting Platform we have supported dozens of cities across the United States and many NGO's to organize the voting phase of participatory budgeting (PB) processes. PB is a process where a decision maker (often a city) asks voters to propose, develop and vote on projects. With our platform we give cities an easy way to implement a PB vote with a few different voting methods. Collectively, these 120+ processes have distributed more than $100 million with input from residents.
In our 2024 paper we analyzed the data from these elections and compare voting methods. We conclude that in the PB-setting, making the ballot a bit more complex does correlate with more time spent, but does surprisingly not correlate with voters not completing their ballot. We show that voters prefer lower-cost projects when the number of projects they can select is limited by their total budget, rather than a fixed number (knapsack voting).
See especially: Rank, Pack or Approve: Voting Methods in Participatory Budgeting (2024)
We have designed a few different feedback exercises for cities to engage their residents in the city budgeting process. We implemented two designs in collaboration with the cities of Austin and Long Beach.
Our implementation in Austin (2020) a survey where residents were invited to give feedback on budgets of various city service areas including the Police Department became a natural experiment when George Floyd was tragically killed by law enforcement in the middle of the feedback process, followed by intensified nationwide protests. The responses to our exercise increased and shifted drastically. In our 2024 paper we analyze this shift, and conclude that this was in part due to an actual opinion shift toward the police, rather than due to differential turnout. We show that the opinion shift on police funding persisted the next year, and that the opinion gap on police funding widened. We show that clustering multi-dimensional opinion data can be a valuable tool in the toolbox of survey organizers and can help contextualize opinion shifts during the survey.
See especially: Opinion Change or Differential Turnout: Changing Opinions on the Austin Police Department in a Budget Feedback Process (2024)
LG, Mohak Goyal, Bhargav Dindukurthi, Ashish Goel, and Alice Siu. "Estimating Contribution Quality in Online Deliberations Using a Large Language Model". Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 12 (October 14, 2024): 65–74.
LG and Ashish Goel. "Opinion Change or Differential Turnout: Changing Opinions on the Austin Police Department in a Budget Feedback Process". Digital Government: Research and Practice 5, no. 3 (September 30, 2024): 1–32.
Wellings, Thomas, Fatemeh Banaie Heravan, Abhinav Sharma, LG, Regula Hänggli Fricker, and Evangelos Pournaras. “Fair and Inclusive Participatory Budgeting: Voter Experience with Cumulative and Quadratic Voting Interfaces.” In Design for Equality and Justice, edited by Anna Bramwell-Dicks, Abigail Evans, Marco Winckler, Helen Petrie, and José Abdelnour-Nocera, 14536:65–71. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2024.
LG and Ashish Goel. "Rank, Pack or Approve: Voting Methods in Participatory Budgeting". In Proceedings of the International AAAI Conference on Web and Social Media 18 (May 28, 2024): 448–61.
LG, Liubov Nikolenko, Sukolsak Sakshuwong, James Fishkin, Ashish Goel, Kamesh Munagala, and Alice Siu. “Achieving Parity with Human Moderators: A Self-Moderating Platform for Online Deliberation.” In The Routledge Handbook of Collective Intelligence for Democracy and Governance, edited by Stephen Boucher, Carina Antonia Hallin, and Lex Paulson, 202–21. Routledge International Handbooks. New York: Routledge, 2023.
Azizifard, Narges, LG, Jean-Olivier Gransard-Desmond, Miriam Redi, and Rossano Schifanella. “Wiki Loves Monuments: Crowdsourcing the Collective Image of the Worldwide Built Heritage.” Journal on Computing and Cultural Heritage 16, no. 1 (March 31, 2023): 1–27.
LG, Ashish Goel, Sungjin Im, and Kamesh Munagala. “Representational Robustness in Social Choice.” Extended abstract presented at the ACM Collective Intelligence 2022, 2022.
LG, and Ashish Goel. “Opinion Change or Differential Turnout: Austin’s Budget Feedback Exercise and the Police Department.” In Proceeding of the Second Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO ’22), 2022.
Shen, Zeyu, Aleksandra Korolova, LG, Ashish Goel, and Kamesh Munagala. “Robust Allocations with Diversity Constraints.” In Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 13, 2021.
Garg, Nikhil, LG, Sukolsak Sakshuwong, and Ashish Goel. “Who Is in Your Top Three?” In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 7:22–31, 2019.
LG and Vereniging Wikimedia Nederland. “Schrijven voor Wikipedia”. In Dutch. Culemborg: Van Duuren Media, 2018. ISBN 978-94-6356079-5
Zwetsloot, F.J.M., LG, and R.J.W. Tijssen. “International Comparison of Technology Transfer Data.” In University Technology Transfer, 1st ed., 428–35. Routledge, 2016.
Angamuthu, Raja, LG, Maxime A. Siegler, Anthony L. Spek, and Elisabeth Bouwman. “A Molecular Cage of Nickel(Ii) and Copper(i): A [{Ni(L)2}2(CuI)6] Cluster Resembling the Active Site of Nickel-Containing Enzymes.” Chemical Communications, no. 19 (2009): 2700.
Kimmo Grönlund, Kaisa Herne, James Fishkin, Janette Huttunen, Maija Jäske, Marina Lindell, Isak Vento, Kim Backström, Alice Siu and LG. “Good deliberation regardless of mode? A comparison of automated online, human online and face-to-face moderations in a deliberative mini-public.”
Samuel Chang, Estelle Ciesla, Michael Finch, James S. Fishkin, LG, Ashish Goel, Ricky Hernandez Marquez, Shoaib Mohammed, Alice Siu. “Meta Community Forum Results Analysis: What principles should guide generative AI’s engagement with users?”. Technical Report. Stanford CA, April 3, 2024
Guo, Kun, LG, and Ashish Goel. “Newton Zoning Exercise 2022 Report.” Stanford Digital Repository, 2022.
LG, Daniel Kim, and Ashish Goel. “The City of Austin FY 2022 Budget Survey Report.” Technical Report. Stanford CA, July 7, 2021.
LG, Ashish Goel, Kamesh Munagala, and Sravya Yandamuri. “Advertising for Demographically Fair Outcomes.” In arXiv. Online, 2020.
LG, Samuel T. Reamer, and Ashish Goel. “The City of Long Beach FY 2021 Budget Exercise Final Report.” Technical Report. Stanford CA, November 30, 2020.
Chen, Yiling, LG, and Ashish Goel. “The City of Austin FY 2021 Budget Survey Report.” Technical Report. Stanford CA, July 21, 2020.
Fishkin, James, Nikhil Garg, LG, Ashish Goel, Kamesh Munagala, Sukolsak Sakshuwong, Alice Siu, and Sravya Yandamuri. “Deliberative Democracy with the Online Deliberation Platform,” 2. Skamania Lodge, WA, 2019.
LG, Sukolsak Sakshuwong, Nikhil Garg, and Ashish Goel. “Comparing Voting Methods for Budget Decisions on the ASSU Ballot.” Technical Report. Stanford CA: Stanford University, September 3, 2018.