Resources
Support your learning through our searchable research library and discover valuable resources about many topics in artificial intelligence and data analytics, such as AI ethics, bias and data tools.
Select the We Count at Large tag to view a selection of speaking engagements and presentations by IDRC team members. Many of these resources showcase the efforts of IDRC Director Jutta Treviranus, whose pioneering work and insights in AI and inclusive AI continue to inspire and lead the field.
IBM Design for AI: Fundamentals
- Beginner
A guide for non-technical people on the basics of AI.
ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics
- Intermediate
This code is designed to be a comprehensive framework for self-regulation for those engaged in market, opinion and social research and data analytics with the aim of maintaining public confidence in research, ensuring researchers and analysts meet their ethical and legal responsibilities, and safeguarding the right of researchers to seek, receive and impart information.
Identifying and Improving Disability Bias in GPT-Based Resume Screening
- Expert
A 2024 paper presents a bias-focused resume audit study, in which the authors ask ChatGPT (specifically, GPT-4) to rank a resume against the same resume enhanced with an additional leadership award, scholarship, panel presentation, and membership that are disability-related. They find that GPT-4 exhibits prejudice towards these enhanced CVs and that this bias can be quantifiably reduced by training a custom GPTs on principles of DEI and disability justice.
IEEE
IEEE home page.
If Not AI Ethicists like Timnit Gebru, Who Will Hold Big Tech Accountable?
- Intermediate
An article that stresses the importance of AI ethicists and how ethical AI research can help make such systems more safe, fair and transparent.
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
- Expert
To address identified issues with Twitter's saliency model used to crop images, the Twitter team is proposing the removal of saliency-based cropping in favour of a solution that better preserves user agency.
Imagining Artificial Intelligence as a Public Good for K-12 Learning
- Expert
The Learning Accelerator's Beth Rabbitt has contributed this article to our FLOE project's AI in Education collection, supported by the Hewlett Foundation in partnership with Etika Insights. Beth's article challenges us to shape AI as a public resource rather than accepting a future dictated by private interests. The AI in Education collection examines AI’s role in education, highlighting both opportunities and risks while emphasizing the importance of responsible implementation.
Improving Accessibility in Procurement
An overview of how Public Services and Procurement Canada aims to improve accessibility in procurement.
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
- Expert
Through 35 semi-structured interviews and an anonymous survey of 267 ML practitioners, the first systematic investigation of commercial product teams’ challenges and needs for support in developing fairer machine learning systems is presented.
In AI (Can) We Trust?
- Intermediate
An article that explores whether AI decision-making can be trusted.