We Count: Artificial Intelligence Inclusion Projects from Inclusive Design Research Centre

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.

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  • AI and disability, small minorities and outliers (for the general public)
  • Work for people with disabilities in data science
  • AI ethics and policy
  • AI design and methods (for AI experts)
  • ICT Standards and Legislation

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How Cognitive Diversity in AI Can Help Close the Disability Inclusion Gap

Source: World Economic Forum
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

This World Economic Forum article discusses the high unemployment rate among people with disabilities and how AI can address the challenges and discrimination that people with disabilities face daily.

How Could Equality and Data Protection Law Shape AI Fairness for People with Disabilities?

Source: ACM Transactions on Accessible Computing
Media Type: PDF Article
Readability: 
  • Expert
Summary:

This article looks at the application of equity law and data protection law governing AI fairness. The article also emphasizes how fairness can provide people with disabilities with new opportunities in advancing their rights.

How Different Groups Prioritize Ethical Values for Responsible AI

Source: MAIEI
Media Type: Website Article
Readability: 
  • Expert
Summary:

AI ethics guidelines argue that values such as fairness and transparency are key to the responsible development of AI, but less is known about the values a broader and more representative public cares about. This paper surveys a US-representative sample and AI practitioners about their value priorities for responsible AI.

How Do Fair Decisions Fare in Long-Term Qualification?

Source: NeurIPS 2020
Media Type: Website Article
Readability: 
  • Expert
Summary:

A paper that studies the dynamics of population qualification and algorithmic decisions to analyze the long-term impact of static fairness constraints on the equality and improvement of group well-being.

How Do You Lip Read a Robot? – Recruitment AI has a Disability Problem

Source: Zero Project conference 2021
Media Type: Video
Readability: 
  • Intermediate
Summary:

A webinar that explores the unacknowledged risks to the more than 1.3 billion persons with disabilities that are triggered by the fast-growing use of AI-powered recruitment tools.

How Facebook Got Addicted to Spreading Misinformation

Source: MIT Technology Review
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

In this article, read how Facebook's appetite for growth isn't often compatible with making the platform's AI algorithms more responsible, ethical and fair.

How Humans and AI Can Work Together to Create Better Businesses

Source: TED Talks
Media Type: Video with Transcript
Readability: 
  • Intermediate
Summary:

Business technologist Sylvain Duranton advocates for a human plus AI approach in his Ted Talk "How Humans and AI Can Work Together to Create Better Businesses."

How I'm Fighting Bias in Algorithms

Source: TED Talks
Media Type: Video with Transcript
Readability: 
  • Beginner
Summary:

An introduction to algorithmic bias in machine learning systems, such as facial recognition technologies and predictive policing.

How Innovation Sets Me Backwards

Source: Immerse
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

Technology may be developing at light speed, but not all users, such as those with disabilities, are benefitting from technological advances.

How Microsoft and Google Use AI Red Teams to “Stress Test” Their Systems

Source: Emerging Tech Brew
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

Since 2019, some Big Tech companies, like Microsoft, Google and Meta, have used AI red teams to test their AI systems for bias, security flaws and shortcomings. Find out how they work in this article.

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.

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Topics

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