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NeurIPS 2022 Affinity Events

Hicham Hammouchi · Nedjma OUSIDHOUM · Wafaa Mohammed

North Africans in ML is a joint effort led by North African organizations and groups to promote artificial intelligence and machine learning in North Africa and to increase North African presence in top conferences. The goal of the group is to join forces to highlight AI research in North Africa and shed light on North African problems

Michael Running Wolf · Mason Grimshaw

[ Room 286 ]

Indigenous In AI’s vision is to build an international community of Native, Aboriginal, and First Nations who will collectively transform their home communities with advanced technology. By elevating the voices of Indigenous ML researchers we will inspire future impactful work and break stereotypes. Additionally, this group will strive to educate the broader NeurIPS on contemporary indigenous issues relevant to information technology and practices.

Sudha Jamthe · Susanna Raj · Pariya Sarin · Yashaswini Viswanath

[ Room 287 ]

The Global South in AI workshop will run for 1 hours. Join us in-person or via virtual and ask a question in the chat.


1. keynote by Bonaventure Dossou (McGill University, past Mila Institute and Google AI) - on their research about building technologies for African Languages
2. keynote by Jazmia Henry on operationalizing bias reduction in post production (Remember AI needs to keep learning continuously, how to get that chatbot to take my input when it failed to understand me this time?)
2. Design thinking workshop led by Sudha Jamthe (Stanford University) and Susanna Raj (AI4Nomads) live + a hybrid zoom session including two of our accepted authors Ogbuokiri Blessing (York University) and Ricardo Alanis (CodeandOMexico)

Join us as global south innovators to arrive at actionable insights about commons problems, potential solutions and identifying shared resources for open datasets for translations, transliterations, language model generators, benchmarks and speech recognition for Global south languages. For more information, please visit the Global South in AI website.

Don't miss our poster sessions at the joint poster sessions following this workshop at 4.30pm in Hall J

And our 12 peer-review double blind selected authors representing 8 languages/12 countr

Mariam Arab · Konstantina Palla · Sergul Aydore · Gloria Namanya · Beliz Gunel · Kimia Nadjahi · Soomin Aga Lee

[ Hall I-2 ]

Register for our workshop on 11/28/2022 here
Join us for a night of food, music, and networking on 11/27/2022 and RSVP here

The Women in Machine Learning (WiML) workshop started in 2006 as a way of creating connections within the small community of women working in machine learning to encourage mentorship, networking, and the interchange of ideas. The workshop has attracted representatives from academia and industry, whose talks showcase some of the cutting-edge research done by women. In addition to technical presentations and discussions, the workshop aims to incite debate on future research avenues and career choices for machine learning professionals.

[ Virtual ]

In order to visit a specific poster in Topia, it's recommended to visit the corresponding physical workshop, find the paper and follow the Topia link.

Or visit the Topia World. See the Help Menu above for how to visit a Topia Poster Session.

Maria Luisa Santiago · Juan Banda · CJ Barberan · MIGUEL GONZALEZ-MENDOZA · Caio Davi · Sara Garcia · Jorge Diaz · Fanny Nina Paravecino · Carlos Miranda · Gissella Bejarano Nicho · Fabian Latorre · Andres Munoz Medina · Abraham Ramos · Laura Montoya · Isabel Metzger · Andres Marquez · Miguel Felipe Arevalo-Castiblanco · Jorge Mendez · Karla Caballero · Atnafu Lambebo Tonja · Germán Olivo · Karla Caballero Barajas · Francisco Zabala

[ Room 298 - 299 ]

Mariam Arab · Konstantina Palla · Sergul Aydore · Gloria Namanya · Beliz Gunel · Kimia Nadjahi · Soomin Aga Lee

[ Virtual ]

Register for our workshop on 11/28/2022 here

The Women in Machine Learning (WiML) workshop started in 2006 as a way of creating connections within the small community of women working in machine learning to encourage mentorship, networking, and the interchange of ideas. The workshop has attracted representatives from academia and industry, whose talks showcase some of the cutting-edge research done by women. In addition to technical presentations and discussions, the workshop aims to incite debate on future research avenues and career choices for machine learning professionals.

Victor Silva · Foutse Yuehgoh · Salomey Osei · Blessing Ogbuokiri · Idriss Cabrel Tsewalo Tondji · Deborah Dormah Kanubala · Lyse Wamba

[ Room 288 - 289 ]

The Black in AI workshop is a one-day hybrid event with invited speakers, oral presentations, and posters from individuals in the community. The event will bring together faculty, graduate students, researchers, and engineers to network, share ideas, foster collaboration, and discuss initiatives. There will be a mix of highlighted talks and keynote presentations, which can be delivered in person or online, as well as keynote sessions where an invited person speaks on a predefined topic to a broad audience of Black in AI, which can also be delivered in person or online. All presentations will be broadcast online, so online participation is possible. This will be an opportunity to learn about the diverse work of community researchers, and everyone is invited to attend.

Workshop
Sarthak Arora · Jaidev Shriram · Evan Dong · Divija Nagaraju · Kruno Lehman · Yanan Long · Nenad Tomasev · Ashwin S · Hang Yuan · Ruchira Ray · Claas Voelcker

[ Room 283 ]

The Queer in AI workshop at NeurIPS asks its participants to question the status quo of machine learning research and applications in society, in a world ravaged by queerphobia, heteropatriarchy, corporate hegemony, racial disparity and global economic inequality. The Queer in AI membership survey shows that nearly 70% of queer scientists are not publicly out and many have faced discrimination or even violence due to their existence. We call on our community to face these challenges head-on, to advocate for and build a future where technological progress empowers marginalized people and does not ossify the status quo of the past and present.

In the last months, large language models have made impressive progress on well-established AI benchmarks, to a point where some believe that the continuous increase in the size of language models can bring about AGI. This vision ignores the real and well-documented harms that this paradigm presents for marginalized communities and concentrates power in the hands of corporations and other actors who can afford to collect data and scale systems without considering the lives of those impacted. It also silences those who work diligently to explore the weaknesses, problems and short-coming of these models.

As such, it is …