CHIARA LONGONI

Courses a.y. 2023/2024
Courses previous a.y.
Biographical note
I am a social scientist and I conduct interdisciplinary work on the psychology of artificial intelligence theoretically grounded in social psychology and decision science that also draws from marketing, economics, philosophy, ethics, and computer science. I completed a Ph.D. in marketing at New York University’s Stern School of Business. I also hold a M.S. (summa cum laude) from Bocconi University, a M.A. (Honors) in Psychology from New York University, and a M. Phil. in Marketing from New York University’s Stern School of Business. Before joining academia, I worked in strategic consulting and brand management.
Research interests
My primary area of research falls under the realm of investigating consumer psychological responses to applications of artificial intelligence across domains spanning healthcare, recommendation systems, automated content generation, and government service provision. A secondary area of research broadly relates to consumer and societal well-being. My work in this area looks at the determinants of positive behavior change and the drivers of sustainability and climate action.
Working papers
Plagiarizing AI-generated content is seen as less unethical and more permissible
Knowledge of artificial intelligence predicts lower AI receptivity
Selected Publications
Algorithmic Transference: People overgeneralize failures of artificial intelligence in the government
Journal of Marketing Research, 2022
Artificial Intelligence in utilitarian vs. hedonic contexts: the “word-of-machine” effect
JOURNAL OF MARKETING, 2022
News from generative artificial intelligence is believed less
ACM Conference on Fairness, Accountability, and Transparency (FAccT ’22), 2022
National identity predicts public health support during a global pandemic: Results from 67 countries
Nature Communications, 2022
Understanding, explaining, and utilizing medical artificial intelligence
NATURE HUMAN BEHAVIOUR, 2021
Resistance to medical artificial intelligence is an attribute in a compensatory decision process: Response to Pezzo and Becksted
Judgment and Decision Making, 2020
Advertising a Desired Change: When Process Simulation Fosters (vs. Hinders) Credibility and Persuasion
JOURNAL OF MARKETING RESEARCH, 2020
Resistance to medical Artificial Intelligence
THE JOURNAL OF CONSUMER RESEARCH, 2019