Concern 12 · Working draft · editorial review in progress
Disability bias
Disability bias arises when AI data, design, or evaluation assumes abilities that some users do not have.
Understanding the concern
Speech, movement, vision, or ways of communicating can differ without making a person less capable. A system built around a narrow pattern may misread those differences, fail to offer access, or reproduce stereotypes.
Studies can reveal biased outputs without proving exactly which training examples caused them. The response should therefore include both data review and testing with disabled people. An average accuracy score may hide a service that some people cannot use at all.
An example
A voice-only service may repeatedly reject a person with a speech difference instead of offering another way to communicate.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Training
- The process of using examples to shape how an AI model behaves. Learning patterns from material does not establish that the material is true or fair.
Evidence and its limits
Studies examine disability-related output disparities and resume screening; the interface example illustrates a distinct access issue.
Panda, Agarwal, and Patel · Research preprint
AccessEval: Benchmarking Disability Bias in Large Language Models ↗ (opens in a new tab)Evaluates paired disability-aware and neutral queries across tested models and domains. Results should not be generalized to every user or service.
Glazko and colleagues · Research study
Identifying and Improving Disability Bias in GPT-Based Resume Screening ↗ (opens in a new tab)Resume audit compares disability-related additions in tested GPT-4 settings. It does not establish all real-world hiring outcomes.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Can people use this service on their own terms, with an accessible alternative when needed?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Justice
Justice means fair treatment, fair procedures, and attention to who receives benefits and burdens. It asks whether people with less power can be heard and seek repair.
Look at outcomes across different groups and individual cases. Provide a usable way to challenge decisions and correct harm. Equal wording in a policy does not guarantee equal treatment in practice.
Ask together: Who benefits, who bears the cost, and who can challenge the decision?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
Search for more writing
For more specific or recent material, open a search below or ask for a web summary. AI-generated summaries can contain mistakes; open the original articles to check them.