How Effective Altruism Can Help Psychologists Maximize Their Impact.

Izzy Gainsburg, Shiva Pauer, Nawal Abboub, Eamon T Aloyo, Jean-Christophe Mourrat, Alejandrina Cristia
Author Information
  1. Izzy Gainsburg: Ross School of Business, University of Michigan.
  2. Shiva Pauer: Department of Social Psychology, University of Amsterdam.
  3. Nawal Abboub: RisingUp, Paris, France.
  4. Eamon T Aloyo: Institute of Security and Global Affairs, Leiden University.
  5. Jean-Christophe Mourrat: Courant Institute of Mathematical Sciences, New York University.
  6. Alejandrina Cristia: Laboratoire de Sciences Cognitives et de Psycholinguistique, Département d'Etudes Cognitives, École Normale Supérieure (ENS)/Ecole des Hautes Études en Sciences Sociales (EHESS)/Centre National de la Recherche Scientifique (CNRS), Paris Sciences et Lettres (PSL). ORCID

Abstract

Although many psychologists are interested in making the world a better place through their work, they are often unable to have the impact that they would like. Here, we suggest that both individuals and psychology as a field can better improve human welfare by incorporating ideas from effective altruism, a growing movement whose members aim to do the most good by using science and reason to inform their efforts. In this article, we first briefly introduce effective altruism and review important principles that can be applied to how psychologists approach their work, such as the importance, tractability, and neglectedness framework. We then review how effective altruism can inform individual psychologists' choices. Finally, we close with a discussion of ideas for how psychology, as a field, can increase its positive impact. By applying insights from effective altruism to psychological science, we aim to integrate a new theoretical framework into psychological science, stimulate new areas of research, start a discussion on how psychology can maximize its impact, and inspire the psychology community to do the most good.

Keywords

MeSH Term

Humans
Altruism
Psychology

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