The past decade has witnessed the widespread adoption of machine learning and statistical methods on large-scale datasets, many of which correspond to personal data of individuals. While this has enabled unprecedented insights into human behaviour, at the same time, it raises new moral and ethical concerns about what might be revealed as a byproduct of these analyses. What private information will this allow us to infer about individuals, and is this worth the price of admission? Are there strategies which we can adopt to avoid these disclosures, and can they be executed without significant loss in utility? At which point should lawmakers step in, and how do we connect technical notions of privacy with those which are enforced by law? Beyond individual privacy, should there be regulations on things that "shouldn't be learned"? The goal of this social is to bring together a broad range of experts and non-experts interested in all aspects of data privacy, discuss associated issues and challenges, and propose and debate potential solutions. We will lead participants through an exploration of these concepts, featuring fun and interactive activities, as well as a guided discussion on these topics.
A Decemberfest on Trustworthy AI Research - An overview and panel discussion with virtual drinks and Bretzels
What do we mean by Trust in AI? Why does it matter? What influence can technology have in building trust? These and further questions will be addressed during the two-part gathering for interested attendees. The event will start with a block of elevator pitches on the topic of Trustworthy AI held by researchers of the German Network of National Centres of Excellence for AI Research in collaboration with international partners. This will then lead to the second part, a panel and audience discussion focused on central questions regarding Trustworthy AI. In addition to this semi-formal program a social gathering space with topical corners but also just hang-out space will give the opportunity for a social get-together.
Equity and Ethics in AI from the Perspective of Black Women in AI/STEM
AI is all around us but not created by all of us which connects to bias in AI. AI tends to be created by individuals that are not representative of several groups in society. Women of Color, especially Black women, are underrepresented in AI related fields of study and careers. This topic is also crucial to the ongoing discussions regarding how to address bias in AI. Equity and ethics in AI are also important topics that are connected to addressing bias in AI. One recommendation to address this bias is to actively provide opportunities to increase the representation of underrepresented groups. This social will identify methods and techniques that Black women who study AI and/or have pursued AI practitioner/developer/etc careers have explored or suggested to address equity and ethics in AI. Black Women who study/have studied/work in roles where AI is developed plan to lead discussions to address equity and ethics from their perspectives related to AI. Some of the discussion starters for this session that will be used are: how many Black women do audience members know in an AI/STEM program of study or career? have you spoken to any Black woman about her journey to an AI or STEM program of study or career? These questions would be used to frame other topics to discuss during the session. Notes will be taken by the team members connected to this social during discussions. These notes will be distributed by asking participants to provide their names and email addresses in a Google form. After the completion of this session follow-up meetings will be encouraged to continue with some of the suggested next steps from the discussions.
"Lapsed" (aka. Former) Physicists are plentiful in the machine learning community. Inspired by Wine and Cheese seminars at many institutions, this BYOWC (Bring Your Own Wine and Cheese) event is an informal opportunity to connect with members of the community. Hear how others made the transition between fields. Discuss how your physics training prepared you to switch fields or what synergies between physics and machine learning excite you the most. Share your favorite physics jokes your computer science colleagues don't get, and just meet other cool people. Open to everyone, not only physicists; you'll just have to tolerate our humor. Wine and Cheese encouraged, but not required.
We propose a 2-hour social with the following activities: * The first hour will consist of 20-30 min participant-driven breakout sessions centered around different aspects of trustworthy ML (e.g. fairness, interpretability, robustness, etc.), with the goal of curating 1-2 questions on each topic. This will be followed by a 40-min panel discussion where panelists address the participant-curated questions. * The second hour will consist of trivia games with both fun and technical questions. We will design some games with a trustworthy ML spin, e.g. trustworthy scrabble, roulette, charades, etc., to promote educational interaction in a casual environment. * If there is time left we will ask participants to return to the breakout rooms for socializing. * The first hour will consist of 20-30 min participant-driven breakout sessions centered around different aspects of trustworthy ML (e.g. fairness, interpretability, robustness, etc.), with the goal of curating 1-2 questions on each topic. This will be followed by a 40-min panel discussion where panelists address the participant-curated questions. * The second hour will consist of trivia games with both fun and technical questions. We will design some games with a trustworthy ML spin, e.g. trustworthy scrabble, roulette, charades, etc., to promote educational interaction in a casual environment. * If there is time left we will ask participants to return to the breakout rooms for socializing.
Join us for computational biology speed networking! We will run two one-hour sessions. During each hour, participants will be randomly places in breakout rooms of 3 - 4 people for 6-minute mini-meetings. We will provide suggested questions and discussion topics, but participants are also free to choose their own.
An online tournament of "Super Smash Brothers Melee", welcoming players of all skill levels. Thanks to recent community effort, online play is virtually lag-free: https://twitter.com/Fizzi36/status/1275096470765490176 We will likely hold the tournament in gather.town for proximity chat. We may casually encourage "academic speed-dating" throughout. For example, we might suggest that players discuss research with each other after their match is done, but before their next match begins. If the players decide to share their screens, spectators will be able to watch the game or join in discussion. As the tournament progresses, people will be free to play against others in a non-competitive environment.
Let’s come together for Un-Bookclub Race After Technology social at NeurIPS. We’ve been learning a lot from the discussions in the book clubs we’ve been running out of the book ‘Race After Technology: Abolitionist Tools for the New Jim Code’ by Dr. Ruha Benjamin. We got our first copy of the book as a gift at the amazing Black in in AI dinner at NeurIPS 2019 where Dr. Benjamin spoke. We’d love to give you the gift of connection, conversation, and reflection Dr. Benjamin gave us. Prework: please read the book or watch ICLR keynote: 2020 Vision: Reimagining the Default Settings of Technology & Society, Prof. Ruha Benjamin / Princeton: https://iclr.cc/virtual_2020/speaker_3.html
Informal and interactive session on how we can work together to make the development of AI more collaborative within the research community. We will present Stateoftheart AI, a new, free, and open-data platform that aims to facilitate this collaboration by mapping and visualizing several aspects of AI; as well as creating a repository of models and datasets aiming for compatibility and standardization. Open to all. For the benefit of society.
Geospatial data is vital to understanding our world and humanity’s place in it. The latest Artificial Intelligence techniques form a crucial component in turning geospatial data into information that can be used to combat climate change, respond to natural disasters, protect endangered species, grow better crops, protect our oceans, and revolutionize transport. The AI for Geospatial social serves as a way for attendees from different fields that may not interact during the workshops or main sessions to get to know one another and collaborate in an informal setting. Themed breakout rooms and icebreakers (trivia sessions with prizes) will facilitate an engaging experience and provide an opportunity to learn something both about geospatial analytics and some of its lesser known pioneers.
We invite everyone who is part of and/or interested in the ML research scene in Korea. Participants can introduce their own ML research, especially if it's part of NeurIPS 2020. They can also introduce NeurIPS 2020 papers that they find interesting and discuss them with other participants. Other possible discussion topics include (but are not limited to): Korean NLP, computer vision and datasets, ML research for COVID-19, ML for post COVID-19 era, and career options in academia/industry in Korea. We welcome everyone from anywhere in the world, as long as you can keep awake if our event falls in the middle of the night for you. Note that we had this same Social at ICLR 2020 with active participation.
We will host a series of breakouts on the following emerging areas: Physics-constrained models, Reverse image search engines / knowledge discovery Self-supervised learning, On-board / Edge computing, Digital twins, Open-source science. Following these discussions, we will organise an interactive social experience for attendees to meet each other and foster co-opetition (cooperative competition) completing fun space related activities.
Starting/transitioning your career in ML during the pandemic
We sit down virtually to discuss challenges and opportunities that arise from having to start a career in ML virtually, with tips and tricks for how to approach the application as well as the virtual onboarding into a new team. We'll be discussing together best practices for hiring and starting a career with special attention given to underrepresented groups in the AI field and the challenges/opportunities of remote work.