TY - UNPB
T1 - What Should We Optimize in Participatory Budgeting? An Experimental Study
AU - Rosenfeld, Ariel
AU - Talmon, Nimrod
PY - 2021/11/14
Y1 - 2021/11/14
N2 - Participatory Budgeting (PB) is a process in which voters decide how to
allocate a common budget; most commonly it is done by ordinary people --
in particular, residents of some municipality -- to decide on a fraction
of the municipal budget. From a social choice perspective, existing
research on PB focuses almost exclusively on designing
computationally-efficient aggregation methods that satisfy certain
axiomatic properties deemed "desirable" by the research community. Our
work complements this line of research through a user study (N = 215)
involving several experiments aimed at identifying what potential voters
(i.e., non-experts) deem fair or desirable in simple PB settings. Our
results show that some modern PB aggregation techniques greatly differ
from users' expectations, while other, more standard approaches, provide
more aligned results. We also identify a few possible discrepancies
between what non-experts consider \say{desirable} and how they perceive
the notion of "fairness" in the PB context. Taken jointly, our results
can be used to help the research community identify appropriate PB
aggregation methods to use in practice.
AB - Participatory Budgeting (PB) is a process in which voters decide how to
allocate a common budget; most commonly it is done by ordinary people --
in particular, residents of some municipality -- to decide on a fraction
of the municipal budget. From a social choice perspective, existing
research on PB focuses almost exclusively on designing
computationally-efficient aggregation methods that satisfy certain
axiomatic properties deemed "desirable" by the research community. Our
work complements this line of research through a user study (N = 215)
involving several experiments aimed at identifying what potential voters
(i.e., non-experts) deem fair or desirable in simple PB settings. Our
results show that some modern PB aggregation techniques greatly differ
from users' expectations, while other, more standard approaches, provide
more aligned results. We also identify a few possible discrepancies
between what non-experts consider \say{desirable} and how they perceive
the notion of "fairness" in the PB context. Taken jointly, our results
can be used to help the research community identify appropriate PB
aggregation methods to use in practice.
KW - Computer Science - Multiagent Systems
KW - Computer Science - Artificial Intelligence
KW - Computer Science - Computer Science and Game Theory
U2 - 10.48550/arXiv.2111.07308
DO - 10.48550/arXiv.2111.07308
M3 - Preprint
BT - What Should We Optimize in Participatory Budgeting? An Experimental Study
ER -