On a Mission

Partners-3

 

TRAILS: Trustworthy AI in Law and Society

TRAILS is a partnership between the University of Maryland, George Washington University, and Morgan State University.

Funded by a $20 million award from the National Science Foundation and the National Institute of Standards and Technology, the institute is focused on transforming the practice of AI from one driven primarily by technological innovation to one that is driven by ethics, human rights, and input and feedback from communities whose voices have previously been marginalized.

In addition to UMD, GW, and Morgan State, another participation in TRAILS comes from Cornell University and private sector organizations like the DataedX Group, Planet Word, Arthur AI, Checkstep, FinRegLab, and Techstars.

 

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TRAILS is part of a cohort of National Artificial Intelligence Research Institutes funded by the National Science Foundation. The NSF, in collaboration with government agencies and private sector leaders, has now invested close to half a billion dollars in the AI institutes ecosystem—an investment that expands a collaborative AI research network into almost every state.

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Trustworthy AI
developers working on code

Our MISSION

In the U.S. and internationally, many organizations aim to encourage trustworthy artificial intelligence systems—iterations of AI that users, developers, and deployers see as accountable, responsible, and unbiased. However, the researchers at TRAILS believe that there is no trust or accountability in AI systems without participation of diverse stakeholders.


 



 

Our Strategy

TRAILS researchers will work to ensure that future AI systems enhance human capacity, respect human dignity, and protect human rights.




 

 

 
New Methods

Methods

 

Developing new methods that promote AI trustworthiness.

 

 

Empowerment

 

Empowering users to make sense of AI systems.

 

Empowerment
 
Governance

Governance

 

Analyzing and promoting inclusive governance strategies to build trust and accountability in AI systems.

 

 

Training

 

Training a multidisciplinary next generation of talent.

 

Training
 
Inclusion

Inclusion

 

Centering voices that have been marginalized in mainstream AI.