Company or Institution
Northeastern University, Universidad Nacional Autonoma de Mexico, Pit Policy Lab
Sustainable Development Goals (SDGs)
SDG 5: Gender Equality
SDG 8: Decent Work and Economic Growth
General description of the AI solution
The A.I. Industry has powered a futuristic reality of self-driving cars and voice assistants to help us with almost any need. However, the A.I. Industry has also created systematic challenges. For instance, while it has led to platforms where workers label data to improve machine learning algorithms, my research has uncovered that these workers earn less than minimum wage. We are also seeing the surge of A.I. algorithms that privilege certain populations and racially exclude others. If we were able to fix these challenges we could create greater societal justice and enable A.I. that better addresses people’s needs, especially groups we have traditionally excluded.
To address this problem, we propose an “A.I. For Good” framework. Our framework uses value sensitive design to understand people’s values and rectify harm. We have been using the framework to design A.I. systems that improve the labor conditions of the digital workers operating behind the scenes in our A.I. industry. We have shown that our framework can help digital workers to increase their wages, develop their skills, and create overall fairer digital workspaces.
Our project has been able to connect and work with rural communities in the US and Mexico who are using our A.I. based tools to access better jobs. We have also recently been designing new types of AI tools for women in the global south. Here we are connecting with feminism theory and critical race theory.
To study and connect with rural communities in the US we are working closely with the National Science Foundation (NSF grant FW-HTF-19541) who has provided us with support to design our new A.I. tools to empower the rural workforce in the United States. In Mexico we are working with professor Norma Elva Chavez from the Universidad Nacional Autonoma de Mexico and the Pit Policy lab where we are working together to design and deploy feminist AI technologies for the global south.
Github, open data repository, prototype or working demo
The Global Care Ecosystems of 3D Printed Assistive Devices
Saiph Savage, Claudia Flores-Saviaga, Rachel Rodney, Liliana Savage,
Jon Schull, Jennifer Mankoff
TACCESS: ACM Transactions on Accessible Computing 2022.
Datavoidant: An AI System for Addressing Data Voids on Social Media
Claudia Flores-Saviaga, Shangbin Feng, Saiph Savage
CSCW: ACM Conference on Computer-Supported Cooperative Work 2022.
REGROW: Reimagining Global Crowdsourcing for Better Human-AI Collaboration
Andy Alorwu, Saiph Savage, Niels van Berkel, Dmitry Ustalov, Alexey Drutsa,
Jonas Oppenlaender, Oliver Bates, Danula Hettiachchi
CHI: ACM Conference on Human Factors in Computing Systems 2022 (Paper for organizing a workshop on new AI digital workplaces at the top conference on Human computer Interaction)
Quantifying the Invisible Labor in Crowd Work
Carlos Toxtli, Siddharth Suri, Saiph Savage
CSCW: ACM Conference on Computer-Supported Cooperative Work 2021.
🏆 Impact Award.
Research Methods to Study & Empower Crowd Workers
Saiph Savage, Carlos Toxtli, Eber Betanzos
Book Chapter in Research Methods for Digital Work and Organization,
Oxford University Press 2021.
HPC resources and/or Cloud Computing Services