AVI 2020 Workshop
Data4Good: Designing for Diversity and Development
September 28th-October 2nd
Island of Ischia, Italy
***Remote attendance will be facilitated***
As smartphone penetration continues to expand throughout the Global South, and various "AI for/and Social Good" efforts prepare to dominate technology trends in such parts, challenges related to the robustness and utility of data infrastructures become increasingly pressing. For data to be meaningful, they must be collected, stored, understood, analyzed, and visualized, all from a holistic and contextually appropriate perspective. There are challenges encountered in each of these stages, however, given the cultural, technological, and/or infrastructural specificities of multilingually diverse and resource-constrained parts of the Global South. This is also increasingly true for many diverse regions in the North.
Across domains of global development such as global health, education, and agriculture, among others, all prominent focus areas for AI for Social Good efforts in the Global South, the data burden is borne by low-literate workers from socioculturally and economically diverse backgrounds. Low digital expertise and different vantage points mean that these workers lack the kind of data literacies required of them by their employers. Although AI for Social Good as well as Machine Learning for Development (ML4D) conversations are rapidly unfolding in computing venues such as NeurIPS and International Conference on Learning Representations (ICLR), they may benefit from taking a more human-centered approach towards the design, deployment, and evaluation of AI-based technologies in global development contexts. These are the important conversations that our workshop seeks to advance.
July 28th: Submission deadline
August 6th: Notification of acceptance
August 21st: Camera-readies and registration due
September 28th: Half-day workshop, from 14:00 to 18:00
September 28th-October 2nd: AVI 2020 (main conference)
We invite researchers and practitioners in the interdisciplinary domains intersecting HCI, AI, ML, design, and global development to engage in dialog around how a human-centered design perspective might be suitably factored into the technological advancements being researched in upcoming AI- and ML-focused work. We solicit participation across members of the HCI research community who are motivated to address the following topics:
Interfaces and Visualization
- Novel Interfaces for Deriving Qualitative/Quantitative Insights from Data
- Interfaces to support data literacy among Multilingual users
- Information Visualization Tools and Techniques for Data Literacy
- Data Literacy for End-Users in the Global South
Data Infrastructures for Social Good
- Data Collection and Field Research
- Data Quality
- Data Sharing
- Privacy and Transparency in Data Analytics
- Interfaces for Explainable AI
- User-centered Evaluations Techniques and Methods for AI-based Technologies in the Global South
- Study of Public Concerns with AI technologies
Data Literacy in Specific Application Areas, such as:
- Public/Global Health
- Refugee Resettlement
We invite submissions of position papers in the CHI Extended Abstracts format, 2-4 pages in length. PDFs of submissions can be emailed to Luigi De Russis at [log in to unmask] <mailto:[log in to unmask]>.
These will be reviewed by all organisers based on relevance, originality, and overall quality. At least one author of each accepted paper is required to participate in our workshop.
All workshop participants (including non-authors) are required by the conference to register for the workshop (not necessarily for the conference). We do plan to facilitate remote attendance.
Accepted and presented papers will be made available on CEUR Workshop Proceedings, while workshop results will be published on our website. Notifications will be mailed to the authors within 15 days of receipt (and no later than the dates reported above). Workshop results will be summarized and submitted as an article or blog post in Interactions or Communications of the ACM.
Luigi De Russis, Politecnico di Torino, Italy
Neha Kumar, Georgia Tech, USA
Akhil Mathur, Nokia Bell Labs & University College London, UK
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