How do we reinforce climate action?

被引:0
|
作者
Zhao, Jiaying [1 ,2 ]
Radke, Jade [2 ]
Chen, Frances S. [1 ]
Sachdeva, Sonya [3 ]
Gershman, Samuel J. [4 ,5 ,6 ]
Luo, Yu [1 ]
机构
[1] Univ British Columbia, Dept Psychol, Vancouver, BC V6T 1Z4, Canada
[2] Univ British Columbia, Inst Resources Environm & Sustainabil, Vancouver, BC, Canada
[3] USDA Forest Serv, Northern Res Stn, Evanston, IL USA
[4] Harvard Univ, Dept Psychol, Cambridge, MA USA
[5] Harvard Univ, Ctr Brain Sci, Cambridge, MA USA
[6] Ctr Brains Minds & Machines, Cambridge, MA USA
关键词
Operant conditioning; Reinforcement learning; Differential reinforcement; Behavior change; Climate change; Climate policy; PRO-ENVIRONMENTAL BEHAVIOR; DIFFERENTIAL REINFORCEMENT; ALTERNATIVE BEHAVIOR; EXTINCTION; SPILLOVER; HEALTH; REDUCE; TIME; INTERVENTIONS; METAANALYSIS;
D O I
10.1007/s11625-024-01486-6
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Humanity has a shrinking window to drastically reduce greenhouse gas emissions, yet climate action is still lacking on both individual and policy levels. We argue that this is because behavioral interventions have largely neglected the basic principles of operant conditioning as one set of tools to promote collective climate action. In this perspective, we propose an operant conditioning framework that uses rewards and punishments to shape transportation, food, waste, housing, and civic actions. This framework highlights the value of reinforcement in encouraging the switch to low-emission behavior, while also considering the benefit of decreasing high-emission behavior to expedite the transition. This approach also helps explain positive and negative spillovers from behavioral interventions. This paper provides a recipe to design individual-level and system-level interventions to generate and sustain low-emission behavior to help achieve net zero emissions.
引用
收藏
页码:1503 / 1517
页数:15
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