Education stands as the cornerstone of our work at the Center for Responsible AI. Understanding the profound implications of AI on society necessitates a comprehensive and inclusive approach to education. We conduct cutting-edge research, offer a wide range of courses, and develop educational material geared towards students, professionals, and the broader community. Our goal is to empower learners with the knowledge and critical thinking skills to actively shape the trajectory of AI technology.

Responsible data science

Responsible Data Science is a comprehensive technical course for university students. This course tackles the issues of ethics, legal compliance, data quality, algorithmic fairness and diversity, transparency of data and algorithms, privacy, and data protection. This course was developed and offered for the first time in Spring 2019. Since then, it has been offered every Spring to undergraduate and graduate students in data science, computer science, and related disciplines at New York University.

The most recent offering of the course was in Spring 2023. The course will be offered again in Spring 2024. You can find the most recent lecture slides, lab notebooks, and readers on the course website. All course materials are publicly available online.

Read more about this course
  1. Responsible AI literacy: A stakeholder-first approach
    Daniel Dominguez, and Julia Stoyanovich
    Big Data and Society 2023
  2. Teaching Responsible Data Science
    Armanda Lewis, and Julia Stoyanovich
    International Journal of Artificial Intelligence in Education (IJAIED) 2021
  3. Responsible Data Science: Charting New Pedagogical Territory
    Mary Oliver
    Medium Feb 2020

The causal inference playground

What is causal inference? And how can we use causal inference techniques to answer questions about the real world? Take a tour through our Causal inference playground for a rigorous and fun introduction to this topic!

Read more about this course
  1. An Interactive Introduction to Causal Inference
    Lucius E.J. Bynum, Falaah Arif Khan, Oleksandra Konopatska, Joshua R. Loftus, and Julia Stoyanovich
    VISxAI: Workshop on Visualization for AI Explainability 2022

The algorithmic transparency playbook

Welcome to 2033, the year when AI, while not yet sentient, can finally be considered responsible. Only systems that work well, improve efficiency, are fair, law abiding, and transparent are in use today. It’s AI nirvana. You ask yourself: “How did we get here?”

You may have played a major role! As more organizations use algorithmic systems, there is a need for practitioners, industry leaders, managers, and executives to take part in making AI responsible. In our Algorithmic Transparency Playbook course, we detail how to influence change and implement algorithmic transparency in your organization.

Read more about this course
  1. The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization’s Algorithms
    Andrew Bell, Oded Nov, and Julia Stoyanovich
    In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023, Hamburg, Germany, April 23-28, 2023 2023
  2. Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance
    Andrew Bell, Oded Nov, and Julia Stoyanovich
    Data & Policy 2023

We are AI: Taking control of technology

Artificial Intelligence (“AI”) refers to a growing world of sophisticated computer programs that “learn” from data in order to make decisions. Many of these AI systems are invisible to the public, yet the results of the decisions they make (or help humans make) have a huge impact on modern life.

Because of how important AI is in our lives, we should understand how it works so that we can control it together! NYU R/AI has partnered with P2PU, a public education non-profit, and with the Queens Public Library to develop We are AI: Taking control of technology, a public education course on AI.

This course is designed to be run as a learning circle: a facilitated study group for people who want to meet regularly and learn about a topic with others. There are no teachers or students in a learning circle—it is a group where everyone learns the material together.

The goal of the course is to introduce the basics of AI, discuss some of the social and ethical dimensions of the use of AI in modern life, and empower individuals to engage with how AI is used and governed.

We have also partnered with the NYU Tandon Ability Project to improve the accessibility of AI education across abilities and levels of expertise. The result of this work is our All Aboard! primer on making AI education accessible.

Read more about this course
  1. All Aboard! Making AI Education Accessible
    Falaah Arif Khan, Lucius Bynum, Amy Hurst, Lucas Rosenblatt, Meghana Shanbhogue, Mona Sloane, and Julia Stoyanovich
    Center for Responsible AI, New York University 2023
  2. We are AI: Taking Control of Technology
    Julia Stoyanovich, and Eric Corbett
    Center for Responsible AI, New York University 2021

Responsible AI comics

Responsible AI is an intimidating topic. We have been developing comics for AI enthusiasts, practitiners and the public at large, to bring humor into the conversation, and help us – humans – take ownership of the debate about the role that AI should play in our lives.

You can read the complete We are AI comics in English and Spanish. The first volume of We are AI is also available in Greek. Our Data, Responsibly comics are available in English (vol. 1 and vol. 2), French, Spanish, and Brazilian Portugueze.

Read the comics (English)
  1. What is AI?
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  2. Learning from data
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  3. Who lives, who dies, who decides?
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series 2021
  4. All about that bias
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  5. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  6. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  7. Mirror, Mirror
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series 2020
  8. Fairness and Friends
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    Data, Responsibly Comic Series 2021

Read the comics (Spanish)
  1. What is AI? (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  2. Learning from data (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  3. Who lives, who dies, who decides? (Spanish Edition)
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series 2021
  4. All about that bias (Spanish Edition
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  5. Mirror, Mirror (Spanish Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series 2020

Read the comics (other languages)
  1. What is AI? (Greek Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series 2021
  2. Mirror, Mirror (French Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series 2020
  3. Mirror, Mirror (Portugueze Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series 2020