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AI-powered Chatbots: Effective Communication Styles for Sustainable Development Goals

Author

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  • Ennio Bilancini
  • Leonardo Boncinelli
  • Eugenio Vicario

Abstract

This paper presents an analysis of two pre-registered experimental studies examining the impact of `Motivational Interviewing' and `Directing Style' on discussions about Sustainable Development Goals. To evaluate the effectiveness of these communication styles in enhancing awareness and motivating action toward the Sustainable Development Goals, we measured the engagement levels of participants, along with their self-reported interest and learning outcomes. Our results indicate that `Motivational Interviewing' is more effective than `Directing Style' for engagement and interest, while no appreciable difference is found on learning.

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  • Ennio Bilancini & Leonardo Boncinelli & Eugenio Vicario, 2024. "AI-powered Chatbots: Effective Communication Styles for Sustainable Development Goals," Papers 2407.01057, arXiv.org.
    • Handle: RePEc:arx:papers:2407.01057
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    References listed on IDEAS

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    1. Valerio Capraro & Joseph Y. Halpern & Matjaž Perc, 2024. "From Outcome-Based to Language-Based Preferences," Journal of Economic Literature, American Economic Association, vol. 62(1), pages 115-154, March.
    2. Jeffrey D. Sachs & Guido Schmidt-Traub & Mariana Mazzucato & Dirk Messner & Nebojsa Nakicenovic & Johan Rockström, 2019. "Six Transformations to achieve the Sustainable Development Goals," Nature Sustainability, Nature, vol. 2(9), pages 805-814, September.
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    4. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers 31122, National Bureau of Economic Research, Inc.
    5. Valerio Capraro & Roberto Di Paolo & Matjaz Perc & Veronica Pizziol, 2024. "Language-based game theory in the age of artificial intelligence," Papers 2403.08944, arXiv.org.
    6. John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," Papers 2301.07543, arXiv.org.
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