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.
What is the Role of AI in Human Resource Management?
- Intermediate
Here the author talks about how AI improves the HR department.
What Is the Transportation Standard?
The Transportation Standard of the AODA requires transportation service providers to make the features and equipment on routes and vehicles accessible to passengers with disabilities.
What Makes Us Human Makes Us Also AI (ir)Responsible: When and How to Inject Your AI with R?
- Intermediate
Slides from a World Summit AI 2019 presentation about the link between human and AI irresponsibility and the resources available to help make developers and their algorithms more responsible.
What’s in a Name?: Reducing Bias in Bios without Access to Protected Attributes
- Expert
This article proposes a method for reducing bias in machine learning classifiers without relying on protected attributes. In the context of occupation classification, this method discourages a classifier from learning a correlation between the predicted probability of an individual’s occupation and a word embedding of their name.
What’s New in Android Accessibility
- Intermediate
A video from Google I/O '18 that covers the latest feature additions to Android P, provides an update on accessibility testing and best practices, and discusses new APIs that developers can use to create more accessible app experiences.
What's New in WCAG 2.2 Working Draft
This page lists the proposed new success criteria for Web Content Accessibility Guidelines (WCAG) 2.2.
What’s the Difference Between Data Science, Machine Learning, and Artificial Intelligence?
- Beginner
An introduction to the differences between data science, machine learning and AI, and how they can be used together.
What’s Wrong with “Explainable A.I.”
- Intermediate
Explainable AI has an explainability problem, especially in healthcare. Explainable AI methods being sold by companies are often faulty and misleading, and they reveal a larger problem: deep learning algorithms used in healthcare settings are rarely subjected to rigorous testing, such as the approval process for prescription drugs.
What the New GPT-4 AI Can Do
- Intermediate
OpenAI released GPT-4 last week, an updated version of OpenAI's text-generating AI program. GPT-4 can produce more natural-sounding text and solve problems more accurately, but it's still vulnerable to issues like displaying bias and making up falsehoods.
What the White House’s “AI Bill of Rights” Blueprint Could Mean for HR Tech
- Intermediate
President Biden's recently unveiled blueprint flags employment as a "sensitive domain" that warrants enhanced data and privacy protection.