CLASS-L Archives

August 2021

CLASS-L@LISTS.SUNYSB.EDU

Options: Use Monospaced Font
Show HTML Part by Default
Condense Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Message-ID:
Sender:
"Classification, clustering, and phylogeny estimation" <[log in to unmask]>
Subject:
From:
Raju Vatsavai <[log in to unmask]>
Date:
Thu, 26 Aug 2021 11:17:39 -0400
Content-Type:
multipart/alternative; boundary="000000000000c0be3c05ca77de9f"
MIME-Version:
1.0
Reply-To:
"Classification, clustering, and phylogeny estimation" <[log in to unmask]>
Parts/Attachments:
text/plain (5 kB) , text/html (19 kB)
*Call for Papers: IEEE ICDM International Workshop on AI for Nudging (WAIN)
2021*
Co-located with IEEE International Conference on Data Mining (ICDM)
(Due to ongoing COVID-19, WAIN-21 workshop will be fully virtual.)

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
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.

We invite contributions from researchers of any discipline who are
developing AI/ML/DS technologies that impact human behavior based on
nudging theory 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? In
addition to algorithmic and systems papers, case studies that shed light on
the effectiveness of nudges at maximizing a specific outcome, how AI/ML
based systems can nudge people to make better decisions, or how industry is
developing and/or using nudging technology to influence behavior of
consumers are of great interest to this workshop.

*Topics of interest include, but not limited to, the following:*

●      Theoretical foundations of nudging

●      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

●      Personalized nudging

●      Challenges for AI in real-time nudging

●      AI-driven interactions encoding behavior change solutions

●      Nudging in conversational AI

●      Evaluation strategies to measure impact and effectiveness of nudging

●      Applications: Healthcare, Precision Medicine, Energy, Environment,
Transportation, Workforce, Education, Advertising, Government, Politics,
Policy, Software Engineering



*Important dates:*

●      Sep. 03, 2021: Paper submission

●      Sep. 24, 2021: Acceptance notification

●      Oct. 01, 2021: Camera-ready deadline and copyright form

●      Dec. 17, 2021: (Due to ongoing COVID-19, WAIN workshop will be fully
virtual)

*Paper Submissions:*

This is an open call-for-papers. We invite both full papers (max 8 pages)
describing mature work and short papers (max 5-6 pages) describing
work-in-progress or case studies. Only original and high-quality papers
formatted using the IEEE 2-column format (Latex Template
<https://www.ieee.org/conferences/publishing/templates.html>), including
the bibliography and any possible appendices will be considered for
reviewing. Submission instructions can be found here
<https://lirio-brell.github.io/wain21/submissions/>.

*Proceedings:*

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 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 the
Lirio <https://lirio.com/>. 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/wain21/

●      If you have questions, please contact us by e-mail to:
[log in to unmask]


ATOM RSS1 RSS2