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Artificial intelligence (AI) and machine learning (ML) technologies will revolutionise the treatment of diseases, aged care, and even aging itself – but a new Monash University study is warning it may also entrench ageism and inequality.
Monash University report finds AI fuels ageism in aged care
The paper, published in the Journal of Applied Gerontology, reveals the unmet value of AI in solving aged care issues like loneliness through chat, video and image sharing through medical diagnosis and assessment tools.
The study found pushing AI technology – from robots to voice assistants – into aged care environments can exacerbate ageist views due to the choices of carers on how best to use technology for older people in these settings.
“AI can perpetuate ageism and exacerbate existing social inequalities,” lead author Dr Barbara Barbosa Neves said.
“When implementing AI technologies in aged care, we must consider them as part of a suite of care services and not as isolated solutions.”
Artificial Intelligence (AI) design entrenches bias
The study reveals more work is needed to better incorporate older people’s needs in the design and implementation of AI technologies.
Monash University found ageism can be generated by designing AI models based on the views of carers, for example, that older people are dependent, incompetent or disinterested in technology.
Both AI developers and aged care staff assume a lack of interest and ignore the capacity of older people to use the technology.
This further ignores the need to be accessible and non-discriminatory to aged care residents.
AI and ML are critical to finding solutions for ageing population
The study reveals the need to change stereotypes about aged care residents and the attitudes of staff and create technologies that are designed for and inclusive of older people.
Aged care staff and advocates may be concerned that AI will replace humans with robots, or they might have to be responsible for machinery failures.
“The use of AI in aged care must be done with consideration of the potential impact of these technologies on wellbeing, autonomy, and dignity of older residents,” Dr Neves said.
Ethical pitfall for aged care: manifestation bias
AI systems are often designed and developed based on using vast amounts of data, which then ‘trains’ the AI’s decision-making process.
However, if the data used for training is biased, the AI will subsequently exhibit these biases in its decisions.
For example, if an AI system is trained on data suggesting older people have a lower recovery rate than younger people, the system may be predisposed to opt for alternative treatments for older patients, even when it might not be the best decision for the individual.
This is where ageism can subtly trickle into the provision of care.
Dr Neves, the lead author, emphasizes the need to be mindful of ageism while exploring future technological advancements in caring for older people.
In the world of AI and aged care, AI and ML technologies should be integrated as part of a holistic approach rather than standalone solutions.
Embracing the perspectives of older individuals during the design and implementation of AI technology can help break down stereotypes.
Mitigating the risks of AI in aged care
The industry must integrate AI with care and could use techniques like employing diverse data sets for training AI or ML.
The care industry could also emphasise the importance of compassionate human interaction and care in addition to technology.
It must also monitor the impact of AI and discrimination.
Including older adults’ voices during the development and deployment of AI systems will provide valuable insights to prevent unintended ageist consequences.
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