How to Make Virtual Conferences Queer-Friendly: A Guide

Core authors: A Pranav, MaryLena Bleile, Arjun Subramonian, Luca Soldaini, Danica J. Sutherland, Sabine Weber and Pan Xu


Queer in AI’s demographic survey reveals that most queer scientists in our community do not feel completely welcome in conferences and their work environments, with the main reasons being a lack of queer community and role models. Over the past years, Queer in AI has worked towards eliminating these issues, yet we have observed that the voices of marginalized queer communities, especially transgender, non-binary folks and queer BIPOC folks have been neglected. Furthermore, the coronavirus pandemic has introduced many novel scenarios including the ubiquity of virtual conferences, with which D&I chairs may not have prior experience. Queer in AI frequently gets inquires about making virtual conferences more inclusive from both conference organizers and queer community organizers. The purpose of this document is to provide a tutorial for D&I organizers on how to make virtual conferences queer friendly.

Queer in AI Demographic Survey

Curation Rationale: Queer in AI demographic survey is used for:

  • understanding issues and status of queer communities,

  • understanding queer intersectionality,

  • collecting info on trans-inclusive publications,

  • collecting info on queer inclusivity in academia and conferences,

  • shaping Queer in AI mentoring programs

  • getting feedback on Queer in AI socials and initiatives.

The responses of this survey are used to identify issues within queer communities and shape the future programs of Queer in AI.

Data collection policy: This survey was sent to all attendees of Queer in AI socials, workshops, members and will be placed on top of Queer in AI's website. The survey is available here. Respondents can be anonymous while entering the survey responses. All questions in the survey were optional, and in demographic questions like gender and sexual orientation, respondents can choose multiple responses. Only a handful of Queer in AI organizers can have access to these responses. Folks can contact Queer in AI to delete the information if they want. LGBTQ Crisis Hotlines were linked in the survey considering the nature of the questions.

Survey Curators' Demographic: This survey was designed in collaboration with gender theory scholars and transgender, gender-diverse and BIPOC members of Queer in AI. All of the curators have informal training in queer studies through activism and advocacy in Queer in AI and affiliated groups. The curation team consisted of 8 members. They ranged in age from 21-35 years, with gender including men (2), women (2), non-binary folks (2), agender individual (1) and genderfluid (1). 5 of them are transgender. 5 of them are BIPOC. Region-wise, 1 is from East Asia, 1 is from Europe, 1 is from South Africa, 1 is from South America and 4 are from North America.

Survey Respondents' Demographic: At the time of this writing, the survey has received 129 responses. Following are the aggregate results of the given demographics:

  • Sexual Orientation: Gay (42%), Queer (38%), Lesbian (10%), Bisexual (36%), Pansexual (18%)

  • Gender: Woman (39%), Man (44%), Non-binary (23%), Genderqueer (10%), Gender non-conforming (10%), Agender (10%), Questioning (10%)

  • 31% are non-cisgender, 19.5% are transgender and 8.6% are questioning regarding it

  • 29.9% are BIPOC

  • 15% are neurodivergent and/or disabled

  • 46.5% are graduate students, 15.5% are junior folks from industry, 9.3% are postdocs, 8.5% are professors or equivalent

  • Research Interests: NLP (61%), Data Science (43.1%), Ethics (34.1%), Vision (22%)

Responses to Conference related questions:

  • 18.9% have changed or planning to change their name in their publications.

  • On a scale of 1-5, queer folks reported an average of 3.46, when asked how welcome they feel as a queer person at the conferences.

  • 41.6% queer folks reported that 0-10% of participants had pronoun badges.

  • 15% queer folks reported a lack of funding.

  • When asked, on a scale of 1-5, how satisfied are they when entering gender in the registration form in the conferences, cisgender respondents indicated average satisfaction of 3.75, while non-cisgender folks reported average satisfaction of 2.69.

  • 92% of non-cis respondents would prefer entering pronouns, not gender at registration.

  • On a scale of 1-5, cisgender folks reported an average of 2.5 when asked how aware are they about the name change policies in academic publications.

  • The majority of folks reported that Google Scholar does not update the names in the citations during the name change.

Registration Form Guidelines

Gender and Pronouns

Motivation: Pronouns and Their Significance

  • Pronouns are an important point of identity and help to facilitate a dialogue between people. English speakers regularly refer to people using pronouns, e.g. ‘This is Jane. I’ve read her paper.’ While some languages use the same pronoun for all genders, English has both pronouns that are usually associated with a certain gender (e.g. he, she) and gender neutral pronouns (e.g. they, xe, ze).

  • Name, physical appearance or voice are generally not a good indicator for the pronouns of a person. This is why conference participants need to have the ability to specify what pronouns other people should use to refer to them. Whenever conversations between conference participants happen, names and pronouns should be displayed. This can be done via conference badges and user names in chat platforms and video calls (e.g. ‘Jane Example (she/her)’).

  • Misgendering is the act of using the wrong pronouns when talking about a person. Regardless if done intentionally or not, misgendering can be particularly harmful and ostracizing to trans and nonbinary people and is more likely to happen in virtual conference settings. Prominently displaying the participants’ pronouns reduces the risk of unintentional misgendering. Intentional and repeated misgendering should be listed as a violation of the conference's code of conduct and swiftly addressed by the conference organisers.

  • Not all LGBTQ+ people wish to disclose their pronouns, as they might still be questioning their identity or fear that doing so might out them to colleagues.

  • The options for pronoun choices should include the possibility to not disclose pronouns and the possibility to not use any pronouns at all. In these cases a person should only be referred to by name, e.g. ‘This is Jane. I read Jane’s paper.’ Conference organisers should be ready to answer questions people might have about pronouns, as conference attendees might not be familiar with this practice.

Collecting Gender and Pronouns:

  • Asking conference registrants' gender is not necessary, as it can be invasive, and risks misrepresenting members of the queer community.

  • Transgender and gender-diverse (henceforth referred as non-cis) respondents to Queer in AI’s demographic survey indicated dissatisfaction with current gender forms, and over 90% of non-cis respondents would prefer entering pronouns, not gender at registration.

  • Information about pronouns is less private as unlike gender, an individual's pronouns are relevant to day-to-day conference activities.

  • However, pronouns should not be used as a proxy for gender in processing or displaying any data. We suggest asking for pronouns with an optional form, making it clear what answers will be used for, and following the template we provide in the “Examples” section.

  • Gender information may be reasonably desired for demographic statistics or tracking diversity. We still suggest making gender optional in such cases.

  • In this case, the intent of collection should be explicitly stated, it should be optional, and the data should be anonymized and stored only in aggregate form. Once again we suggest using the format provided in the examples section. Avoid using sex terms male/female as they are rooted in discriminatory scientific histories.



Please indicate your pronouns (multiple choices are allowed). This data is collected only for statistical purposes, will be kept confidential, is purely optional and will be de-associated with your personal information. Please refer to this guide for pronoun usage.

[] they / them

[] she / her

[] he / him

[] I don’t use pronouns

[] Prefer not to say

[] Specify your own

How do you want the pronouns in the badge to be displayed?

  • Same pronouns as above

  • Remove my pronouns

  • I want to use different pronouns: ___


We are gathering gender statistics in order to better serve the community. This is OPTIONAL. Only the organizers have access to this information, will be kept confidential and will be de-associated with your personal information. You can choose multiple options if you like.

[] Woman

[] Man

[] Non-binary / Genderqueer / Third gender

[] Genderfluid / Gender non-conforming

[] Questioning

[] Prefer not to say

[] Specify your own (open text box)

Collecting Names

To avoid confusion and discomfort for non-cis attendees, conferences should allow attendees to register with the name they use in this professional setting, rather than forcing them to disclose their legal name (Reference). If a legal name is absolutely necessary, the reason should be clearly communicated to registrants, its use should be limited, and it should be requested separately. If a legal name is necessary for some particular use, e.g. for a visa letter or making out a reimbursement check, it should be requested only in that context and only for that use. Often people in the process of changing their name may need different legal names for different uses. We suggest asking for legal names as optional by default.

Conference Operational Guidelines

Display Names and Pronouns: Users should be able to change what name is shown in conference contexts, such as discussion posts or video chats (White et al.). Organizers should encourage attendees to add pronouns to their display names in virtual spaces, but stress that doing so is optional (Slattery et al.).

Chat Rooms: Default designs of text communication platforms used in conferences can be exclusionary of queer users. Often, default blocklists for these platforms include terms such as ''queer'' or ''lesbian.'' Organizers should review blocklists before deploying them. Platforms also often list the names of members of shared channels, which for queer-themed discussions effectively outs members. If there is a channel or virtual space for queer communications, organizers should ensure the member list is not publicly visible, for the safety of participants.

Code of Conduct Violation Reporting: Make sure the code of conduct is on the conference web page , and that it is easy to find and check how to report violations. Code of conduct and reporting guidelines should also be highlighted during any plenary session throughout the conference; the more attendees are exposed to it, the more likely they will respect it. It also underscores the fact that the conference takes the code of conduct seriously.

The Professional Conduct Committee should be responsible for handling code of conduct violations at any time -- not just during conference hours, and including after the conference is over. Finally, organizers should ensure that any platforms used have an easy way for attendees to block any other member who is being disruptive, engaging in any activity that violates the code of conduct, or who they simply wish not to interact with for any other reason.

While queer attendees can always reach out to Queer in AI safety team (reporting guidelines here), the conference should provide a robust system to handle any violation in a timely manner.

Reports of code of conduct violations should be encouraged in the follow-up communication after the conference, and there should additionally be officers available at all times to handle reports. It would also be useful to have a survey asking about participants’ experiences without mentioning the code of conduct, as this term may not be relatable to some.

Queer Socials and Privacy: Due to a lack of queer spaces, queer researchers often don't have opportunities, at conferences or elsewhere, to meet, discuss ideas, and network with other members of their community.

Conferences should strive to create these opportunities; we suggest hosting specific social events for queer folks. For such queer social events, we suggest stronger queer-inclusive privacy measures. Such measures could include telling the audience to avoid screenshots and recordings, and strongly encouraging participants to maintain the confidentiality of the members. Sign-ups for these events should explicitly state privacy policies, which should include who has access to this information and when the information will be deleted.

Increasing Diversity

Queer researchers are ignored in many aspects of the research community: lack of academic support, hostility from colleagues and advisors, inflexible name change policies, lack of representation in research work itself, and other forms of discrimination (Cech and Pham, 2017). Further, homophobia and transphobia experienced by individuals in our community are often compounded by discrimination based on race, class, disability status, and other aspects of identity.

Stronger inclusion efforts, both for representation and participation, should be undertaken to address concerns about a lack of queer community and role models (Schluter, 2018).

Increasing Queer Representation: Invite queer folks, particularly those who are also from marginalized backgrounds (e.g. BIPOC and non-cis) as keynote speakers and panelists (Dryden, 2013). Potential speakers can be found through directories such as WiNLP’s BIG Directory (Widening NLP Organizers, 2021), by reaching out to affinity groups for suggestions, or through researching hashtags such as #QueerinAI and #BlackinAI on social media. All speakers should be fairly compensated proportionally to their effort, and not based on their seniority or session prestige.

Increasing Queer Participation: Organizations such as Queer in AI routinely receive dozens of requests for funding for each relevant conference. This indicates that financial accessibility is a significant barrier for queer researchers, especially for those from other non-represented backgrounds or who reside in countries with high rates of discrimination towards queer people (Tulloch, 2020). Allocate funding not only to cover registration fees, but also anything else needed for full participation in the conference, e.g.internet access, VPN access, or caregiving support. Funding opportunities should be publicized as early as possible to give marginalized attendees more flexibility.

Camera Ready / Proceedings Guidelines

  • We strongly recommend flexible name change policies (in both author lists and citations) for conference publications (Tanenbaum et al, 2021).

  • Non-cis respondents to Queer in AI demographic survey rated their satisfaction with name change policies as 2.8/5; many reported that their deadnames are often cited.

Best Practices for Publishers:

  • Requests for name corrections in any format should be promptly granted, without unnecessary barriers or documentation requirements.

  • Name changes should remove all instances of authors' previous names from the records. As of this writing, the ACL Anthology has a public version history of corrections, which outs the deadnames of trans authors. Publishers should regularly correct the citations, preferably without requiring consent from authors or conference organizers.

Best Practices for Authors and Program Chairs:

  • Submission processes (calls for papers, submission checklists, automatic formatting checks) should enforce running scripts that check for outdated entries, such as Rebiber (Lin, 2021).

  • Authors can ensure they are using updated names by checking the website or Semantic Scholar page of authors they cite, and using the latest ACL anthology .bib files. Avoid using platforms such as Google Scholar that do not properly support author name changes (Speer, 2021).


As a supplement to the guide, we provide these slides which offer a condensed version of the guide.


You may find translations of our inclusive conference guide here. Currently, we have translations in: Hindi, Kannada, Konkani, Malayalam, Bengali, and Sinhala.

What's Missing?

This guide is still in-progress. We are working on sponsorship guidelines and accessibility resources.

You can cite our work using this BibTeX:


title = "How to Make Virtual Conferences Queer-Friendly: A Guide",

author = "QueerInAI, Organizers of and Pranav, A and Bleile, MaryLena and Subramonian, Arjun and Soldaini, Luca and Sutherland, Danica J. and Weber, Sabine and Xu, Pan",

booktitle = "Proceedings of the 2021 Workshop on Widening NLP",

month = nov,

year = "2021",

address = "Punta Cana, Dominican Republic",

publisher = "Conference on Empirical Methods in Natural Language Processing",

url = "",