Call for Papers: 3rd IEEE ICDM International Workshop on AI for Nudging (WAIN-2023)
Co-located with the IEEE International Conference on Data Mining (ICDM), Dec 1 - 4, 2023, Shanghai, China
https://lirio-brell.github.io/wain23/

[Call for Papers]

Important Deadlines 
Paper Submission: September 18, 2023
Acceptance Notice: September 24, 2023
Camera Ready: October 01, 2023
ICDM/Workshop: December 1-4, 2023


Note: Due to ongoing COVID-19 travel impacts, the SSTDM workshop will be held in a hybrid format. Authors who can't travel will be given the option to present their accepted paper remotely.

Nudging has been widely used by decision-makers and organizations (both government and
private) to influence the behavior of target populations, and the concept of nudging is now
being widely used in the digital world. Examples of digital nudging include emails from hospitals
or public health officials encouraging individuals to get vaccinated, text messages from colleges
to stressed-out students to advertise the availability of counseling services during exam weeks,
marketing messages through various digital media, and user interfaces designed to guide
people's behavior in digital choice environments.

The central idea behind nudging is to make small changes to the environments in which citizens
make decisions to encourage better behaviors. Even though nudges have traditionally involved
simple changes that are easy and inexpensive to implement, more complex and sustained
behavior change requires more complex interventions, presenting new challenges for nudging
in the virtual world. Though the concept of nudging has been popularized recently, nudges have
been in use in various aspects of society for a long time, including in healthcare, public health
policy, law, economics, politics, insurance, finance, and advertising. With the increasing availability
of big data from many scientific disciplines, artificial intelligence (AI), machine learning (ML),
and data science (DS) technologies have vast potential to transform data-driven nudging and
decision-making. This workshop seeks to build a new community around AI for nudging and
provide a platform for exploring the state of the art in AI/ML/DS-based systems and
applications of digital nudging.

Adaptation of products and services to individual preferences, called Personalization, has been
at the core of modern businesses to improve customer satisfaction. Modern business and
digital systems coupled with artificial intelligence technologies are poised to enable
personalization on a grand scale. Personalization is key behind many modern
businesses such as Netflix, Facebook, and Amazon to increase their revenue and customer base.
Modern businesses are tailoring content for individual users based on the social, economic, and
cultural profiles mined from the data, as it is shown to increase revenue and attract new
customers. Modern applications ranging from precision marketing to precision healthcare have
shown a clear demand for personalized content.

We invite contributions from researchers of any discipline who are developing AI/ML/DS
technologies that impact human behavior based on nudging theory or personalization or
behavioral science-based solutions. For example, in the context of public health
communications, how can AI/ML be used to address the construction of a message
incorporating nudges; how do you digitally nudge people towards better healthcare outcomes,
better financial decisions, or improve productivity; or how can nudging be personalized? What
are the key data, technology, privacy and ethical, adaptation, and scaling challenges in nudging
and personalization? In addition to algorithmic and systems papers, case studies that shed light
on the effectiveness of nudges and personalization at maximizing a specific outcome, how
AI/ML-based systems can nudge people to make better decisions, or how the industry is developing
and/or using nudging and personalization technology to influence the behavior of consumers is of
great interest in this workshop.

Topics of interest include, but are not limited to, the following:
* Theoretical foundations of nudging and personalization
* Data-driven and evidence-based approaches in nudging and personalization
* Core AI/ML topics including multi-agents, federated learning, active learning, semi-
supervised learning, multi-armed bandits, contextual bandits, reinforcement learning,
deep learning, transfer learning
* Multi-modal data and model fusion
* Representation learning, and embeddings
* Learning from categorical and relational data
* Feature engineering
* Statistical models, A/B testing
* Privacy and Ethical issues in nudging and personalization
* Personalized nudging
* Challenges for AI in real-time nudging
* AI-driven interactions encoding behavior change solutions
* Nudging and personalization in conversational AI systems
* Evaluation strategies to measure the impact and effectiveness of nudging and
personalization
* Applications: Healthcare, Precision Medicine, Energy, Environment, Transportation,
Workforce, Education, Advertising, Government, Politics, Policy, Software Engineering


Paper Submissions:
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 reviewed. Visit the workshop website or use
the link to submit your papers:

http://wi-lab.com/cyberchair/2023/icdm23/scripts/submit.php?subarea=S41&undisplay_detail=1&wh=/cyberchair/2023/icdm23/scripts/ws_submit.php


Proceedings:
All submitted papers will be evaluated by 2-3 program committee members and accepted
papers will be included in an IEEE ICDM Workshop Proceedings volume, to be published by IEEE
Computer Society Press and will be included in the IEEE Xplore Digital Library.

Best Research/Application/Student Paper Awards:
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.

Contact:
* Visit the official workshop website for additional details at: https://lirio-brell.github.io/wain23/
* If you have questions, please contact us by e-mail to: lirio.brell@gmail.com