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The Sustainability-Performance Trade-off in AI: The Role of Sustainability Information and Unmet Performance Goals in Sustainable AI Decisions

Author

Listed:
  • Dirk Leffrang

    (Paderborn University)

  • Oliver Müller

    (Paderborn University)

Abstract

Despite the impressive capabilities of Artificial Intelligence (AI), concerns about its environmental impact continue to grow. However, organizations rarely implement sustainable AI practices in real-world settings. Prior research has predominantly focused on promoting sustainability-related information for non-AI products or exploring technical approaches for AI applications. This paper identifies performance uncertainty as a key factor distinguishing AI from prior technologies. Drawing on goal-setting theory, we investigate the impact of sustainability information and an unmet performance goal on AI retraining decisions. We conducted three incentivized online between-subjects experiments with 343 individuals with data science experience. Our results indicate that visualizing sustainability information increases the likelihood of sustainable AI choices. However, presenting an unmet performance goal decreases the likelihood and offsets the beneficial impact of sustainability information. These findings support sustainability initiatives, AI evaluations, and future research by emphasizing that while sustainability matters, achieving it requires appropriate performance goals for AI.

Suggested Citation

  • Dirk Leffrang & Oliver Müller, 2025. "The Sustainability-Performance Trade-off in AI: The Role of Sustainability Information and Unmet Performance Goals in Sustainable AI Decisions," Working Papers Dissertations 135, Paderborn University, Faculty of Business Administration and Economics.
    • Handle: RePEc:pdn:dispap:135
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    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP135.pdf
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    More about this item

    Keywords

    sustainability; artificial intelligence; goal-setting; laboratory experiment;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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