Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI Project

Hupont, Isabelle; Tolan, Songül; Porcaro, Lorenzo; Freire, Ana Paula Coelho Figueira

doi:10.48550/arxiv.2203.01657

“…The AI Watch Index 2021 report by the Joint Research Centre of the European Commission [28] provides a good complementary view by reporting the diversity of participants, namely keynote speakers, authors and Program Committee (PC) members, in 5 top-tier AI scientific conferences in the period 2016-2020. Using the four Biodiversity-inspired indexes proposed by [17], [29] to measure gender, institutional and geographic diversity, the report evidences a slow but increasing diversity trend over the studied conferences.…”

Section: Diversity Studies In Scientific Communitiesmentioning

confidence: 98%

“…Some challenges of measuring diversity are the complexity of defining standard indicators, the lack of curated data (e.g. country, gender, institution type, topics), plus ethical concerns on the labeling of authors with gender information [17].…”

Section: Introductionmentioning

confidence: 99%

Measuring and Fostering Diversity in Affective Computing Research

Hupont

¹

,

Tolan

²

,

Frau

³

et al. 2024

IEEE Trans. Affective Comput.

3

0

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This work presents a longitudinal study of diversity among the Affective Computing research community members. We explore several dimensions of diversity, including gender, geography, institutional types of affiliations and selected combinations of dimensions. We cover the last 10 years of the IEEE Transactions on Affective Computing (TAFFC) journal and the International Conference on Affective Computing and Intelligent Interaction (ACII), the primary sources of publications in Affective Computing. We also present an analysis of diversity among the members of the Association for the Advancement of Affective Computing (AAAC). Our findings reveal a "leaky pipeline" in the field, with a low -albeit slowly increasing over the years-representation of women. They also show that academic institutions clearly dominate publications, ahead of industry and governmental centres. In terms of geography, most publications come from the USA, contributions from Latin America or Africa being almost non-existent. Lastly, we find that diversity in the characteristics of researchers (gender and geographic location) influences diversity in the topics. To conclude, we analyse initiatives that have been undertaken in other AI-related research communities to foster diversity, and recommend a set of initiatives that could be applied to the Affective Computing field to increase diversity in its different facets. The diversity data collected in this work are publicly available, ensuring strict personal data protection and governance rules.

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“…The AI Watch Index 2021 report by the Joint Research Centre of the European Commission [23] provides a good complementary view by reporting the diversity of participants, namely keynote speakers, authors and Program Committee (PC) members, in 5 top-tier AI scientific conferences in the period 2016-2020. Using the four Biodiversity-inspired indexes proposed by [12], [24] to measure gender, institutional and geographic diversity, the report evidences a slow but increasing diversity trend over the studied conferences.…”

Section: Diversity Studies In Scientific Communitiesmentioning

confidence: 98%

Measuring and fostering diversity in Affective Computing research

Hupont¹,

Tolan²,

Frau³

et al. 2022

Preprint

Self Cite

0

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<p>This work presents a longitudinal study of diversity among the Affective Computing research community members. We explore several dimensions of diversity, including gender, geography, institutional types of affiliations and selected combinations of dimensions. We cover the last 10 years of the IEEE Transactions on Affective Computing (TAFFC) journal and the International Conference on Affective Computing and Intelligent Interaction (ACII), the primary sources of publications in Affective Computing. Our findings reveal notable correlations between different types of diversity, such as gender and institutional type, geography and topics, as well as topics and first author’s gender. We also present an analysis of diversity among the members of the Association for the Advancement of Affective Computing (AAAC). Finally, we analyse diversity initiatives that have been undertaken in other AI-related research communities to foster diversity, and conclude on a set of initiatives that could be applied to the Affective Computing field to increase diversity in its different facets. The data collected in this work will be publicly available, ensuring strict personal data protection and governance rules.</p>

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“…There are other fruitful -though less common-initiatives to help improving diversity in conferences. The role of diversity and inclusion chair was first created in the 2016 ISMIR Conference (International Society for Music Information Retrieval Conference 12 ) so as to have a person devoted to take into account diversity in speakers and participants, as well as their inclusion and accessibility needs. Since 2018, some of the largest AI conferences such as NeurIPS, ICML, ICLR and RecSys also incorporate a diversity and inclusion chair in their organising committee.…”

Section: Diversity Affinity Groups and Initiativesmentioning

confidence: 99%

“…Some challenges of measuring diversity are the complexity of defining standard indicators, the lack of curated data (e.g. country, gender, institution type, topics), plus ethical concerns on the labeling of authors with gender information [12].…”

Section: Introductionmentioning

confidence: 99%

Measuring and fostering diversity in Affective Computing research

Hupont¹,

Tolan²,

Frau³

et al. 2022

Preprint

Self Cite

0

View full text Add to dashboard Cite

<p>This work presents a longitudinal study of diversity among the Affective Computing research community members. We explore several dimensions of diversity, including gender, geography, institutional types of affiliations and selected combinations of dimensions. We cover the last 10 years of the IEEE Transactions on Affective Computing (TAFFC) journal and the International Conference on Affective Computing and Intelligent Interaction (ACII), the primary sources of publications in Affective Computing. Our findings reveal notable correlations between different types of diversity, such as gender and institutional type, geography and topics, as well as topics and first author’s gender. We also present an analysis of diversity among the members of the Association for the Advancement of Affective Computing (AAAC). Finally, we analyse diversity initiatives that have been undertaken in other AI-related research communities to foster diversity, and conclude on a set of initiatives that could be applied to the Affective Computing field to increase diversity in its different facets. The data collected in this work will be publicly available, ensuring strict personal data protection and governance rules.</p>

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Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI Project

Cited by 3 publications

References 5 publications

Measuring and Fostering Diversity in Affective Computing Research

Measuring and Fostering Diversity in Affective Computing Research

Measuring and fostering diversity in Affective Computing research

Measuring and fostering diversity in Affective Computing research

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