In behavioural public policy, the external validity of interventions remains a key concern. Behavioral solutions that have proven effective in one context may falter in another, posing significant challenges for policymakers. Traditional approaches to addressing this problem – such as extensive literature reviews – are both time-consuming and resource-intensive.
To address this gap, the ‘PREDICT’ project aims to use machine learning (ML) algorithms to create a digital advisory tool. This tool aims to recommend optimal behavioural actions tailored to specific scenarios. The methodology includes a systematic compilation of relevant literature on sustainable behavioural interventions. Using a prediction algorithm based on natural language processing (NLP), the project aims to identify patterns between experimental setups and their outcomes, leading to accurate prediction capabilities.
Ultimately, the goal is to provide policymakers with a streamlined, evidence-based decision-making process based on a comprehensive analysis of existing research.
Micha Arne Kaiser works as a Senior Research Associate at both the El-Erian Institute at Cambridge Judge Business School and the YNOT Institute at Queens’ College. He is also an External Lecturer at Copenhagen Business School with a focus on artificial intelligence and machine learning.
Prior to joining Cambridge Judge Business School in October 2022, Micha contributed to course development in machine learning, statistics, and consumer research as an Assistant Professor in Copenhagen. His research interests center on exploring questions related to health policy, consumer behaviour, and behavioural public policy.
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