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.
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Responsible AI literacy: A stakeholder-first approach
@article{DominguezStoyanovich23,author={Dominguez, Daniel and Stoyanovich, Julia},title={Responsible AI literacy: A stakeholder-first approach},journal={Big Data and Society},year={2023},keywords={journal,education,rds},doi={https://doi.org/10.1177/20539517231219958},}
Teaching Responsible Data Science
Armanda Lewis, and Julia Stoyanovich
International Journal of Artificial Intelligence in Education (IJAIED) 2022
@article{LewisStoyanovich21,author={Lewis, Armanda and Stoyanovich, Julia},title={Teaching Responsible Data Science},journal={International Journal of Artificial Intelligence in Education (IJAIED)},volume={32},number={3},pages={783--807},year={2022},keywords={journal,education,rds},addendum={Special Issue: The FATE of AI in Education: Fairness, Accountability, Transparency, and Ethics},doi={https://doi.org/10.1007/s40593-021-00241-7},site={https://dataresponsibly.github.io/rds/},}
Responsible Data Science: Charting New Pedagogical Territory
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!
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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
@article{bynum2022interactive,author={Bynum, Lucius E.J. and Khan, Falaah Arif and Konopatska, Oleksandra and Loftus, Joshua R. and Stoyanovich, Julia},title={An Interactive Introduction to Causal Inference},journal={VISxAI: Workshop on Visualization for AI Explainability},year={2022},site={https://r-ai.co/ci-playground},publisher={IEEE},keywords={workshop,education,playground},}
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.
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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
@inproceedings{DBLP:conf/chi/BellNS23,author={Bell, Andrew and Nov, Oded and Stoyanovich, Julia},title={The Algorithmic Transparency Playbook: {A} Stakeholder-first Approach
to Creating Transparency for Your Organization's Algorithms},booktitle={Extended Abstracts of the 2023 {CHI} Conference on Human Factors in
Computing Systems, {CHI} {EA} 2023, Hamburg, Germany, April 23-28,
2023},pages={554:1--554:4},publisher={{ACM}},year={2023},site={https://r-ai.co/transparency-playbook},doi={10.1145/3544549.3574169},keywords={panel,policy,explanability,education,playbook,governance},addendum={peer-reviewed course},author+an={1=self;3=self}}
Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance
@article{bell_nov_stoyanovich_2023,author={Bell, Andrew and Nov, Oded and Stoyanovich, Julia},title={Think About the Stakeholders First! {T}owards an Algorithmic Transparency
Playbook for Regulatory Compliance},volume={5},journal={Data \& Policy},publisher={Cambridge University Press},year={2023},keywords={journal,policy,explainability,education,playbook,governance},}
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.
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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
@article{AllAboard,author={{Arif Khan}, Falaah and Bynum, Lucius and Hurst, Amy and Rosenblatt, Lucas and Shanbhogue, Meghana and Sloane, Mona and Stoyanovich, Julia},title={{All Aboard! Making AI Education Accessible}},journal={Center for Responsible AI, New York University},keywords={panel,education,weareai},year={2023},}
We are AI: Taking Control of Technology
Julia Stoyanovich, and Eric Corbett
Center for Responsible AI, New York University 2021
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.
@article{weareaicomic_vol1,author={Stoyanovich, Julia and Khan, Falaah Arif},title={What is AI?},journal={We are AI Comic Series},volume={1},year={2021},keywords={public,education,comics,english},}
@article{weareaicomic_vol2,author={Stoyanovich, Julia and Khan, Falaah Arif},title={Learning from data},journal={We are AI Comic Series},volume={2},year={2021},keywords={public,education,comics,english},}
Who lives, who dies, who decides?
Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
@article{weareaicomic_vol3,author={Stoyanovich, Julia and Sloane, Mona and Khan, Falaah Arif},title={Who lives, who dies, who decides?},journal={We are AI Comic Series},volume={3},year={2021},keywords={public,education,comics,english},}
@article{weareaicomic_vol4,author={Stoyanovich, Julia and Khan, Falaah Arif},title={All about that bias},journal={We are AI Comic Series},volume={4},year={2021},keywords={public,education,comics,english}}
@article{weareaicomic_vol5,author={Stoyanovich, Julia and Khan, Falaah Arif},title={We are AI},journal={We are AI Comic Series},volume={5},year={2021},keywords={public,education,comics,english},}
@article{weareaicomic_vol5_sp,author={Stoyanovich, Julia and Khan, Falaah Arif},title={We are AI},journal={We are AI Comic Series},volume={5},year={2021},keywords={public,education,comics,english},}
@article{rdscomic_vol1,author={Khan, Falaah Arif and Stoyanovich, Julia},title={Mirror, Mirror},journal={Data, Responsibly Comic Series},volume={1},year={2020},keywords={public,edu,comics,english},}
Fairness and Friends
Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
@article{rdscomic_Vol2,author={Khan, Falaah Arif and Manis, Eleni and Stoyanovich, Julia},title={Fairness and Friends},journal={Data, Responsibly Comic Series},volume={2},year={2021},keywords={public,edu,comics,english},}
@article{weareaicomic_vol1_sp,author={Stoyanovich, Julia and Khan, Falaah Arif},title={What is AI? (Spanish Edition)},journal={We are AI Comic Series},volume={1},year={2021},keywords={public,education,comics,spanish},}
@article{weareaicomic_vol2_sp,author={Stoyanovich, Julia and Khan, Falaah Arif},title={Learning from data (Spanish Edition)},journal={We are AI Comic Series},volume={2},year={2021},keywords={public,education,comics,spanish},}
Who lives, who dies, who decides? (Spanish Edition)
Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
@article{weareaicomic_vol3_sp,author={Stoyanovich, Julia and Sloane, Mona and Khan, Falaah Arif},title={Who lives, who dies, who decides? (Spanish Edition)},journal={We are AI Comic Series},volume={3},year={2021},keywords={public,education,comics,spanish},}
@article{weareaicomic_vol4_sp,author={Stoyanovich, Julia and Khan, Falaah Arif},title={All about that bias (Spanish Edition},journal={We are AI Comic Series},volume={4},year={2021},keywords={public,education,comics,spanish}}
@article{weareaicomic_vol1_gr,author={Stoyanovich, Julia and Khan, Falaah Arif},title={What is AI? (Greek Edition)},journal={We are AI Comic Series},volume={1},year={2021},keywords={public,education,comics,other},}
Teaching Responsible Data ScienceInternational Journal of Artificial Intelligence in Education (IJAIED) 2022
An Interactive Introduction to Causal InferenceVISxAI: Workshop on Visualization for AI Explainability 2022
The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization’s AlgorithmsIn Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023, Hamburg, Germany, April 23-28, 2023 2023
We are AI: Taking Control of TechnologyCenter for Responsible AI, New York University 2021
