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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Topics

  • 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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Media Types

Machine Learning and Class Imbalances

Source: Towards Data Science
Media Type: Website Article
Readability: 
  • Expert
Summary:

An article that looks at the problems caused by imbalanced data in machine learning and how those issues can be addressed.

Machine Learning Catches Multiple Sclerosis-Related Gait Issues

Source: Health IT Analytics
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

A machine learning tool uses gait data to help clinicians monitor the progression of walking problems related to multiple sclerosis.

Machine Learning, Explained

Source: MIT Sloan
Media Type: Website Resource
Readability: 
  • Beginner
Summary:

Explore the basics of machine learning in this helpful introduction provided by MIT Sloan.

Machine Learning Fairness: Lessons Learned

Source: Google I/O 2019
Media Type: Video
Readability: 
  • Beginner
Summary:

A YouTube video from Google I/O ’19 on machine learning fairness, with examples of lessons learned through their products and research and describes techniques, that enables developers to think proactively about fairness in product development.

Machine Learning Glossary: Fairness

Source: Google
Media Type: Website Resource
Readability: 
  • Beginner
Summary:

A glossary of machine learning terms related to fairness and bias.

Machine Learning Mastery

Source: Machine Learning Mastery
Media Type: Website Resource
Readability: 
  • Intermediate
Summary:

Step-by-step machine learning guides written by a machine learning practitioner for people of all knowledge levels.

Machine Learning Tutorial in Python

Source: Edureka
Media Type: Video
Readability: 
  • Beginner, 
  • Intermediate
Summary:

An introduction to machine learning playlist that is part of Eureka's e-learning platform.

Machine Learning Zero to Hero

Source: Google I/O 2019
Media Type: Video
Readability: 
  • Intermediate
Summary:

A YouTube session from Google I/O ’19 that explains machine learning to those with coding experience, including a discussion of the image classification problem and the use of Tensor flow.

Machines That Can Think: Real Benefits, the Apocalypse, or “Dog-Spaghetti”?

Source: CBC
Media Type: Podcast
Readability: 
  • Intermediate
Summary:

A podcast with Dr. Roger Melko about the future and risks of artifical intelligence.

Making Geology Accessible for Blind Students

Source: Inside Higher Ed
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

Finding few resources to support a blind student studying geosciences, a professor at the University of Kentucky created a library of tactile graphics so that others might make their classes more accessible.

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.

Filters

Topics

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Tags

Media Types

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