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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Toward Situated Interventions for Algorithmic Equity: Lessons from the Field

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

This paper explores the development of the Algorithmic Equity Toolkit for the practice of situated investigations into fairness, accountability and transparency in algorithmic systems.

Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model Based AI Systems

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

This paper proposes a responsible-AI-by-design reference architecture to tackle challenges for designing foundation model-based AI systems.

Towards Sustainable Conversational AI

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

Writer and conversational UX designer Julia Anderson explores how conversational AI can be made sustainable in this MAIEI column.

Towards Trustable Explainable AI

Source: IJCAI 2020
Media Type: PDF Article
Readability: 
  • Expert
Summary:

This paper explores the advances of rigorous abductive approaches to explainable AI and proffers that absolutely necessary if trustable explainable AI is of concern.

Towards Trustworthy Artificial Intelligence

Source: WisTech AT Advisory Council
Media Type: Video
Readability: 
  • Expert
Summary:

Jutta Treviranus participated in a webinar that gave an overview of the complex relationship between AI and disability and discussed emerging standards and regulations, the CRC Code of Ethics, and promising approaches for trustworthy AI.

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

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

A richer toolbox of mechanisms for AI development can inform developers’ efforts to earn trust, the demands made of AI developers by activists and civil society organizations, and regulators’ efforts to ensure that AI is developed responsibly.

Toyota Pauses Paralympics Self-Driving Buses after One Hits Visually Impaired Athlete

Source: The Guardian
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

During the Paralympics in Tokyo, Toyota has paused their self-driving shuttle service after an athlete who has a vision disability was struck by one of their self-driving buses.

Tracking @stemxcomet: Teaching Programming to Blind Students via 3D Printing, Crisis Management, and Twitter

Source: SIGCSE 2014
Media Type: PDF Article
Readability: 
  • Expert
Summary:

This paper describes the outcomes of a Ruby workshop with blind and visually impaired students and suggests methods for integrating data analysis and 3D printing into programming instruction for blind students.

Trained AI Models Exhibit Learned Disability Bias, IST Researchers Say

Source: Penn State
Media Type: Website Article
Readability: 
  • Intermediate
Summary:

A new paper has analyzed the presence of explicit bias against people with disabilities in AI services that use natural language processing tools. The paper finds that these tools are driven by learned associations that often contain biases against people with disabilities.

Translation, Tracks and Data: An Algorithmic Bias Effort in Practice

Source: CHI 2019
Media Type: PDF Article
Readability: 
  • Expert
Summary:

A case study on lessons on addressing algorithmic bias, including the development of a bias checklist and dashboarding and data efforts for auditing.

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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