When health-care providers rely on biased technology, there are real and harmful impacts.
AI is often assumed to be more objective than humans.
Current research on bias in AIfocuses mainly on gender and race.
But what about age-related bias can AI be ageist?
Ageist technologies?
It’s free, every week, in your inbox.
The WHO’s campaign to address ageism.
Ageism is defined as a process of systematic stereotyping of and discrimination against people because they are old.
It can beexplicitor implicit, and can take the form ofnegative attitudes, discriminatory activities, or institutional practices.
The pervasiveness of ageism has been brought to the forefront throughout the COVID-19 pandemic.
Digital ageism existswhen age-based bias and discrimination are created or supported by technology.
A recent report indicates that a digital world of more than2.5 quintillion bytes of data is produced each day.
Barriers to technological access can exclude older adultsfrom the research, design and development process of digital technologies.
Even when older adults are included in large datasets, they are often grouped according toarbitrary divisions by developers.
As a result,older adults and their needs can become invisible to AI systems.
They need to direct efforts towards identifying and measuring it.
The next step is to develop safeguards for AI systems to mitigate ageist outcomes.
There is currently very little training, auditing or oversight of AI-driven activities from a regulatory or legal perspective.
For instance,Canadas current AI regulatory regime is sorely lacking.
