![Harvard ReCompute and EAAMO Collaboration](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716734610008-1M1NSTV0SMLTPA7JP5HS/thumb.png)
Harvard ReCompute and EAAMO Collaboration
We are proud to share the outstanding work of Harvard ReCompute undergraduate students who have collaborated with EAAMO in Spring 2024 semester. Their efforts focused on reading and highlighting critical questions from papers presented at previous ACM EAAMO conferences resulted in “Sociotechnical and System Considerations for End-to-end Fairness: An Annotated Reading List.”
![REDNACECYT-MD4SG 2023 Summer of Science Program](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716734342854-9HU4L9P93S5437W6WVY1/thumb.png)
REDNACECYT-MD4SG 2023 Summer of Science Program
The goal of the Summer of Science Program is to support female students from indigenous communities in Mexico as they design and execute research projects aimed at improving their local communities.
![Data and the Global South](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716734513599-I08BZ7HPYU3VK9UK07L3/thumb.png)
Data and the Global South
This project aims to critically examine and shed light on the complex data ecosystem in the Global South – and to do so in a manner that centers the stories, research, and practices of those from the region.
![AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733816957-X2VM5I0R9BL6E6K68B40/thumb.png)
AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI
The EAAMO Working Groups are dedicated to promoting collaboration across various disciplines, a mission highlighted by the research of Ayşe Gizem Yaşar on ‘AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI.’ This research, conducted with a lot of collaborators, examines the impact of advanced AI technology within the European Union’s Digital Markets Act (DMA).
![Responsible AI in Africa: Challenges and Opportunities](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733690346-4XW82WBC2PBNP5DTXTDM/thumb.png)
Responsible AI in Africa: Challenges and Opportunities
As a part of the Data and the Global South project, our members Chinasa Okolo, Kehinde Aruleba, and George Obaido wrote a chapter in the Social and Cultural Studies of Robots and AI series about the state of responsible artificial intelligence (AI) in Africa.
![Fairness and equity in resource allocation and decision-making: an annotated reading list](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733594309-U1PYJTGARGFZOG13RC30/thumb.png)
Fairness and equity in resource allocation and decision-making: an annotated reading list
Faidra Monachou and Ana-Andreea Stoica wrote the Fairness and equity in resource allocation and decision-making: an annotated reading list for ACM SIGecom Exchanges.
![Fair Ranking: A Critical Review, Challenges, and Future Directions](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733468032-3SR6KPEM62O8Y758KB1M/thumb.png)
Fair Ranking: A Critical Review, Challenges, and Future Directions
Members of our working group Gourab Kumar Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, and Nikhil Garg wrote a position paper on the current state of fair rankings (Fair Ranking: A Critical Review, Challenges, and Future Directions) that has been accepted for presentation at ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2022!
![What makes people donate towards COVID-19 Vaccines?](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733328289-V3FA65LJ1OK363HERRVC/thumb.png)
What makes people donate towards COVID-19 Vaccines?
Simon Finster, Michelle González Amador, and Edwin Lock gather to conduct an experiment about what makes people donate towards COVID-19 vaccines.
![Bridging Mechanism Design and Machine Learning towards Algorithmic Fairness](https://images.squarespace-cdn.com/content/v1/65c1195d7e206913ec94c5ff/1716733206086-K6ILNJZ11830TFIHGOD7/thumb.png)
Bridging Mechanism Design and Machine Learning towards Algorithmic Fairness
Jessica Finocchiaro and Faidra Monachou wanted to share their experiences while working on the project Bridging Mechanism Design and Machine Learning towards Algorithmic Fairness that got published at ACM Conference on Fairness, Accountability, and Transparency 2021.