Our Mission
Want to get involved? Contact Us!
The Problem
Garbage in, Garbage outTechnical Solution
Standard interactive reportsCommunity Solution
Workshops and Conversations

Our Team
We are a group of researchers and technologists working together to tackle the challenges of ethics and governance of Artificial Intelligence as a part of the Assembly program at the Berkman Klein Center at Harvard University & MIT Media Lab.Please note: This project is the work of individuals who participated in the Assembly program. If named, participants' employers are provided for identification purposes only.

Kasia Chmielinski
Project Lead
Sarah Newman
Research & Strategy
Josh Joseph
AI Research
Matt Taylor
Data Science & Workshop Facilitation
Chelsea Qiu
Research CollaboratorCollaborating Organizations
Humanity Innovation Labs
User Experience Research & Design CollaboratorAlums

Frequently Asked Questions
A few questions you might haveQ. Do you have a protoype or more information?
Yes, we do! You can take a look at a live protoype of the Nutrition Label for the Dollars for Docs dataset that our friends at ProPublica have made available to our group. We are also currently working on a paper describing our work, the protoype, and future directions.
Q. What inspired this project?
We believe that algorithm developers want to build responsible and smart AI models, but that there is a key step missing in the standard way these models are built. This step is to interrogate the dataset for a variety of imbalances or problems it could have and ascertain if it is the right dataset for the model. We are inspired by the FDA's Nutrition Facts label in that it provides basic yet powerful facts that highlight issues in an accessible way. We aspire to do the same for datasets.
Q. Whom have you been speaking with?
We have been speaking with researchers in academia, practitioners at large technology companies, individual data scientists, organizations, and government institutions that host or open datasets to the public. If you’re interested in getting involved, please contact us.
Q. Is your work open source?
Yes. You can view our live protoype here, and the code behind the prototype on Github.
Q. Who is the intended beneficiary of this work?
Our primary audience for the Nutrition Label is primarily the data science and developer community who are building algorithmic AI models. However, we believe that a larger conversation must take place in order to shift the industry. Thus, we are also engaging with educators, policymakers, and researchers on best ways to amplify and highlight the potential of the Nutrition Label and the importance of data interrogation before model creation. If you’re interested in getting involved, please contact us.
Q. How will this project scale?
We believe that the Data Nutrition Project addresses a broad need in the model development ecosystem, and that the project will scale to address that need. Feedback on our prototype and opportunities to build additional prototypes on more datasets will certainly help us make strides.
Q. Is this a Harvard/MIT project?
This is a project of Assembly, a program run by the MIT Media Lab and the Berkman Klein Center.