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Personalization, the adaptation of products and services to individual preferences, is crucial for modern businesses seeking to enhance customer satisfaction. With the integration of artificial intelligence technologies, digital systems can now achieve large-scale personalization. Companies like Netflix, Facebook, and Amazon leverage personalization to increase revenue and expand their customer base. In the education sector, personalized technologies are being developed to create tailored learning experiences for each student based on their abilities, background, and preferences. The demand for personalized content extends across various applications, including precision marketing and precision healthcare.
Nudging has been widely used by decision-makers and organizations, both government and private, to influence the behavior of target populations. In the digital world, digital nudging employs user-interface design elements to guide people’s behavior in digital choice environments. Examples include emails encouraging vaccination, text messages promoting counseling services during exam weeks, and marketing messages through various digital media. With the increasing availability of big data, artificial intelligence (AI), machine learning (ML), and data science (DS) technologies have the potential to transform data-driven nudging and decision-making. This workshop aims to create a new community around AI for nudging and explore the state of the art in AI/ML/DS-based systems and applications of digital nudging.
We welcome contributions from researchers across disciplines who are developing AI/ML/DS technologies that impact human behavior based on nudging theory, personalization, or behavioral science solutions. For instance, in the context of public health communications, how can AI/ML address constructing messages incorporating nudges? How can we digitally nudge people toward better healthcare outcomes, improved financial decisions, or increased productivity? Additionally, what are the key challenges related to data, technology, privacy, ethics, adoption, and scaling in nudging and personalization? We’re also interested in case studies that explore the effectiveness of nudges and personalization in maximizing specific outcomes, as well as how AI/ML systems can nudge individuals toward better decisions. Industry insights on how nudging and personalization technologies influence consumer behavior are particularly valuable for our workshop.
This is an open call for papers. We invite both full papers (max 8 pages) describing mature work and short papers (max 4-5 pages) describing work-in-progress or case studies. Only original and high-quality papers formatted using the IEEE 2-column format (Latex Template), including the bibliography and any possible appendices will be considered for review.
All submitted papers will be evaluated by 2-3 program committee members and accepted papers will be included in an ICDM Workshop Proceedings volume, to be published by the IEEE Computer Society Press and will be included in the IEEE Xplore Digital Library. Check the workshop website for submission instructions.
Best research, application, and student paper awards are sponsored by Lirio. The awards committee will select papers for these awards based on relevance, program committee reviews, and presentation quality.
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