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ABSTRACT
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The 1st Workshop on Biased Data in Conversational Agents aims to address the challenges posed by biased data in both Machine Learning and society. Conversational Agents (CAs) have become prevalent in various aspects of our daily interactions, but the data used to train these agents can introduce biases related to racial, sexual, political, or gender matters. Such biases amplify the potential risks that CAs pose to society. This workshop invites researchers to compare different chatbots/corpora, study methods to create or mitigate bias in datasets, assess and remove bias in corpora, and handle bias at the chatbot level through NLP or Machine Learning techniques. Theoretical approaches to addressing bias in CAs are also welcomed.

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TOPICS
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Topics of interest include but are not limited to:

∑ Comparison and Evaluation of Corpora/Conversational Agents on biased data
∑ Assessing and mitigating biased data in corpora
∑ Personalized NLP and Information Retrieval
∑ Sexist, Racist, Political, and Gender Dictionary and Ontology
∑ NLP and Machine Learning methods to recognize and handle biased data
∑ Impact of biased data on Conversational Agents
∑ Topic recognition and repair strategies in biased conversations
∑ Mental Models for biased data
∑ Corpora creation and corpora annotation (automatic methods are accepted)

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SUBMISSIONS
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Authors are invited to submit original, previously unpublished research papers. We encourage the submission of:

(A) Extended abstracts: 2 pages
(B) Short papers: 5 to 7 pages
(C) Regular papers: 8 to 14 pages

The space for references is unlimited. Abstracts and papers must be written in English and formatted according to the Springer LNCS guidelines. All papers must be converted to PDF prior to electronic submission.

Submission site: https://cmt3.research.microsoft.com/ECMLPKDDworkshop2023

All papers need to be 'best-effort' anonymized. Code and data should be made available anonymously, for example, in an anonymous GitHub repository via Anonymous GitHub or in a Dropbox folder. The authors may have a (non-anonymous) pre-print published online, but it should not be cited in the submitted paper to preserve anonymity.

At least one author of each accepted paper must have a full registration and be present to present the paper. Papers without a full registration or in-presence presentation will not be included in the post-workshop Springer proceedings.

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IMPORTANT DATES
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Paper Submission Deadline: June 23, 2023
Paper Author Notification: July 12, 2023
Paper Camera Ready: To be announced