The Center is pursuing four key directions:
- Investigating community experiences and perceptions of AI: To design systems that communities trust, we must first understand existing experiences and perceptions of AI. We will conduct a series of surveys and focus groups to (1) engage and better learn AI experiences and perceptions across demographics (e.g., race, class, gender), particularly with minoritized communities, and (2) consider and integrate modes of feedback, oversight, and interaction toward less or nonbiased AI systems.
- Investigating new computational methodologies for community-driven AI: To realize trustworthy AI systems, we will innovate in several fundamental AI areas, including: (1) modeling multi-stakeholder preferences; (2) developing causality-based machine learning models to improve robustness; (3) measuring, mitigating, and tracking bias in AI systems; (4) developing new modes of community-AI interactions to co-create, revise, and monitor the system based on accountability metrics and best practices.
- Equitable AI for digital health: With the above innovations, we will investigate human-centered approaches to co-design AI-based digital health applications in two domains: mental health and obesity interventions. Given the socio-economic disparities in the effectiveness of digital health apps, we will design personalized health guidance applications with a focus on algorithmic bias and fairness, providing transparent metrics to measure long-term impacts of interventions by population group.
- AI for discrimination detection: We will apply our community-driven AI framework to detect and characterize instances of discrimination by humans in five domains: hiring decisions, housing, credit markets, mental healthcare, and criminal justice proceedings. Advancing on our team’s work in audit study field experiments and natural language processing, we will develop new methodologies to detect subtle sources of linguistic discrimination in text data — for example, loan officers may provide more accurate and helpful advice to non-minority applicants.
Project Partners
Court Watch NOLA is a non-profit organization dedicated to promoting transparency, equity, and justice in the criminal court system. By training volunteers to observe and report on thousands of criminal court cases a year, Court Watch NOLA works to ensure judges, prosecutors, public defenders, sheriff deputies, police officers, and other criminal justice actors are doing their jobs professionally, transparently, fairly, and economically.
We work with Court Watch NOLA to build data systems that collect, search, and report on criminal court data to improve transparency and oversight.
2022 Poster | 2021 Poster
Eye on Surveillance is a group of community members and organizations working to reduce the use of and improve the oversight of surveillance tools such as facial recognition. We are working with EoS to improve access to City Council meeting proceedings, in order to help citizens be better informed about important issues facing them.
The Data Center is a fully independent, neutral nonprofit organization that brings together data together from multiple sources to support rigorous analysis on issues that matter most to government, business, nonprofit, and community leaders in Southeast Louisiana.
The City of New Orleans Office of Information Technology and Innovation facilitates effective, cost efficient use of technology by spearheading the assessment and deployment of technology based business management solutions, and service delivery strategies. BlightWatch NOLA is a project focused on publicly available blighted property data in New Orleans. Blight, also known as urban decay, refers to properties that have been abandoned by their owners and left to decay. This includes homes, commercial buildings, and even empty lots. Cities experience blight primarily due to economic distress, natural disasters, and depopulation in general. While blight is a symptom of larger societal problems, its presence also causes problems for residents where it is prevalent. Economically, blighted properties decrease the property values of nearby residents and discourage investment in effected neighborhoods.
Families Helping Families is a family-directed resource center that provides information and referral, training and education, and peer-to-peer support on issues related to disability. FHF of GNO is also home to the Louisiana Parent Training and Information Center, a federal education grant that provides training and support to families throughout Louisiana on special education and transition topics.
Our work with FHF was to develop a chatbot tool to enable easier access to information for parents of children with disabilities.
2021 Poster
Summer Research Program
CEAI, in partnership with the Connolly Alexander Institute for Data Science (CAIDS), is pleased to announce the establishment of the Community-Engaged Artificial Intelligence and Data Science Summer Research Program. This innovative program aims to foster research into human-centered artificial intelligence (AI) with a focus on social impact, emphasizing the importance of building meaningful relationships with diverse communities throughout the AI lifecycle. The Community-Engaged AI and Data Science Summer Research Program supports research into AI technologies are developed and deployed in ways that are socially beneficial, inclusive, effective, fair, transparent, and accountable. By involving communities in all stages of the AI process—from design through deployment—the program seeks to create AI solutions that address real-world challenges and promote equity.Application link
The program awarded funds to support three groundbreaking research projects, each receiving $10,000 to advance their work:
PI: Fallon Aidoo, Assistant Professor of Real Estate & Historic Preservation, Tulane University, School of Architecture
Project Overview: This project aims to develop AI tools to identify and protect unregistered national historic landmarks from real estate development threats, preserving cultural heritage and history.
The project will use AI to map and analyze the development of historic properties in the Oak Bluffs Highlands Heritage Project of the African American Heritage Trail of Martha’s Vineyard. By developing AI-enhancements to text recognition and table analysis software, the team will guide community-driven preservation of that ethnic heritage.
PI: Jordan Karubian, Professor, Tulane University, Department of Ecology & Evolutionary Biology
Project Overview: This initiative leverages AI to aid local conservation efforts in one of the world's most biodiverse areas, enhancing the protection of critical ecosystems. The project will co-develop a localized forest monitoring system called Chocó Forest Watch with Fundación para la Conservación de los Andes Tropicales (FCAT), an Ecuadorian grassroots NGO that manages a community-run reserve in the highly threatened Chocó rainforests of Ecuador. Through a human-centered design approach that engages local community members, the project will create a user-friendly, low-cost, and locally-adapted tool that supports FCAT to monitor and respond to deforestation.
PI: Audrey Hang Hai, Assistant Professor, Tulane University, School of Social Work
Project Overview: This research seeks to integrate AI into existing interventions to provide enhanced support for young adults struggling with substance use disorders, aiming to improve outcomes and accessibility. Partnering with the CADA Prevention & Recovery Center, the team will conduct focus groups to assess attitudes towards the use of AI to help guide individuals to available resources to deal with substance use disorders.
