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Challenges to Implementation of AI and inclusion

treasure map

In no particular order as part of our roadmap we have been looking at the challenges facing aspects of inclusion for those who come under the umbrella of protected characteristics named in the UK’s Equality Act 2010

In particulary for those with disabilities and those becoming less able due to age or debilitating illnesses, the list seems to grow despite the innovations being developed thanks to the use of clever alogrithms and increasing amounts of data and high powered computing power. This is our first attempt at publishing our ideas…

road barriers

Challenges

Understanding the role and meaning Inclusion

  • Equity v equality

Disability is a Heterogeneous not homogeneous

  • Single ‘Disability’ classification not helpful as every disabled person can have very different needs
  • Small data for individual disabilities compared to big data for all (e.g. remove individuals whose data identifiable)

Skills and Abilities rather than deficit model

  • Looking at what an individual can do rather than focussing on the disabilities/difficulties

Designing for average rather than edge cases and outliers

  • Every disabled person can have very different needs than average person

Assumptions of Stakeholders

  • Changing attitudes
  • Lack of understanding – AI and ethics, data collection, algorithms, transparency  
  • Expectations of experts – will have a magic wand
  • Eugenics issues (e.g. Autism genetic correction)

Few disabled people involved in AI (Nothing about us without us)

  • Disabled people need to be involved in AI decisions
  • More disabled people need to understand AI

Capacity Issues

  • Resources – human, financial, tools
  • Policies and Procedures
  • Lack of general ICT as well as AT/AAC technologies that are regularly used in many settings

Cohesive Approach

  • Collaboration

AT and AAC Market

  • Small Market
  • Localisation issues

Lack of Competencies

  • Knowledge building

Black box non transparent Deep NN machine learning

  • Difficult to understand implications of AI DNN for disabled people

Lack of interest

  • Disabled people’s inclusion of little interest to Turing researchers and Turing research challenges and programmes (lack of knowledge due to lack of undergraduate courses, PhD supervisors, High impact Journals, Research funding etc.)

“We can only see a short distance ahead, but we can see plenty there that needs to be done.”

A. M. Turing (1950) Computing Machinery and Intelligence. Mind 49: 433-460.