Aequitas Platform 

- Artificial Intelligence for Social Justice 
 

THE OBJECTIVE

To create an application using AI for social change - wherein the app solves a problem, promotes positive social change, and uses AI as a driving technology.

THE OUTCOME

A solution to help match wrongfully convicted defendants with appropriate innocence projects, by providing insights through artificial intelligence. 

 

 

 

Aequitas Platform 

- Artificial Intelligence for Social Justice 
 

THE OBJECTIVE

To create an application using AI for social change - wherein the app solves a problem, promotes positive social change, and uses AI as a driving technology.

THE OUTCOME

A solution to help match wrongfully convicted defendants with appropriate innocence projects, by providing insights through artificial intelligence. 

 

 

 

Aequitas Platform 

- AI for Social Justice 
 

THE OBJECTIVE

To create an application using AI for social change - wherein the app solves a problem, promotes positive social change, and uses AI as a driving technology.

THE OUTCOME

A solution to help match wrongfully convicted defendants with appropriate innocence projects, by providing insights through artificial intelligence. 

 

 

Innocence Network.001

 

UNDERSTANDING THE PROBLEM. 

The United States has over 2,000 cases where defendants have been wrongfully convicted. That is equal to more than 18,590 years lost. There is reason to believe this number is far higher, however innocence projects are only able to review a few cases. Moreover, each innocence project has its own set of criteria dictating which cases can be reviewed. 

From my research, I found two main problems: first, the process that defendants have to go through to find an appropriate innocence project is long, and fragmented, and requires a form (sometimes 70 pages long) to be physically mailed. Second, innocence projects deploy manual processes to review the cases, and choose appropriate ones to further investigate. 

Aequitas Process.001
AI Final Project.001


SO, HOW DOES IT WORK?

Aequitas functions with two different user flows: 

  1. Sending Defendant's Case Once the defendant has completed a common request form (that I propose is made uniform across all innocence projects), their legal counsel or relative uploads it to Aequitas. From here, Aequitas uses natural language processing to make sense of the defendant's story of innocence.

 

 

SO, HOW DOES IT WORK?

Aequitas functions with two different user flows: 

  1. Sending Defendant's Case Once the defendant has completed a common request form (that I propose is made uniform across all innocence projects), their legal counsel or relative uploads it to Aequitas. From here, Aequitas uses natural language processing to make sense of the defendant's story of innocence.

 

 

SO, HOW DOES IT WORK?

Aequitas functions with two different user flows: 

  1. Sending Defendant's Case Once the defendant has completed a common request form (that I propose is made uniform across all innocence projects), their legal counsel or relative uploads it to Aequitas. From here, Aequitas uses natural language processing to make sense of the defendant's story of innocence.

 

SO, HOW DOES IT WORK?

Aequitas functions with two different user flows: 

  1. Sending Defendant's Case Once the defendant has completed a common request form (that I propose is made uniform across all innocence projects), their legal counsel or relative uploads it to Aequitas. From here, Aequitas uses natural language processing to make sense of the defendant's story of innocence.

2. Matching to Innocence Project: The system matches the defendant's case to innocence projects using keyword analysis, and sends the request to the appropriate project, with insights drawn out.

 

2. Matching to Innocence Project: The system matches the defendant's case to innocence projects using keyword analysis, and sends the request to the appropriate project, with insights drawn out.

 

AI Final Project.014

 

 

TRAINING THE SYSTEM.

There are two main data sources that I see being critical for training Aequitas:

First, the National Registry of Exonerations : which will be used to determine common factors in wrongful convictions, the correlation between race/type of crime/type of evidence used to convict. This is all public data.


Second, the Innocence Network : reviewing the intake criteria for various innocence projects which are connected within the Innocence Network will allow the system to successfully learn keyword analysis. This too, is public data which can be leveraged.  


 

 

 

TRAINING THE SYSTEM.

There are two main data sources that I see being critical for training Aequitas:

First, the National Registry of Exonerations : which will be used to determine common factors in wrongful convictions, the correlation between race/type of crime/type of evidence used to convict. This is all public data.


Second, the Innocence Network : reviewing the intake criteria for various innocence projects which are connected within the Innocence Network will allow the system to successfully learn keyword analysis. This too, is public data which can be leveraged.  

 

 

 

 ...

While this project broke free from my traditional approaches of ethnographic research, it also opened my eyes to the vast possibilities that emerge when approaching issues with a systemic lens. The social impact space is brimming with various ways of incorporating Artificial Intelligence for social good, considering how many issues house complex sets of data - an ideal breeding ground for introducing AI. My next step for Aequitas is to begin testing its value proposition, and finding an Innocence Project to get it in front of. 

 

 

 

CLASS / DURATION

TECHNOLOGIES FOR CHANGE

ONE WEEK

 

 

 

CLASS / DURATION

TECHNOLOGIES FOR  CHANGE

ONE WEEK

 

 

 


TECHNOLOGIES FOR CHANGE

ONE WEEK 


 

 

TECHNOLOGIES FOR CHANGE

ONE WEEK

 

 

SKILLS

INFORMATION ARCHITECTURE

UX DESIGN, RESEARCH

SPECULATIVE DESIGN


 

SKILLS

INFORMATION ARCHITECTURE

UX DESIGN, RESEARCH

SPECULATIVE DESIGN


  

 

 

KEYWORDS

SOCIAL INNOVATION

ARTIFICIAL INTELLIGENCE

INTERFACE 


 


 

 

 

 

NEXT PROJECT

Meals on Wheels

NEXT PROJECT

Meals on Wheels


 

NEXT PROJECT

Meals on Wheels