AI and Elder Care: A Revolution with Conditions

AI Serving the Elderly: A Promise to Fulfill

Artificial intelligence (AI) has profoundly transformed many aspects of our daily lives, and its potential to improve care for the elderly is immense. With over a billion people aged 60 and older worldwide, and 55 million living with dementia, AI could alleviate the burden on caregivers. However, this transformation requires overcoming ethical and design challenges specific to this user group.

A Unique Design Challenge

Elderly individuals cannot be viewed merely as users needing minor adaptations. They represent a fundamentally different design challenge. A 2025 study highlights that complex interfaces and the fear of making mistakes are major obstacles for this group. Unlike younger users, seniors fear breaking something, which leads to anxiety and resistance.

Often, it is not the elderly individuals themselves who directly use the technology, but their caregivers. This necessitates designing distinct experiences: one for clinical efficiency and another for user comfort. Researchers advocate for individuals with dementia to become active users of technology, but the path forward remains unclear.

What Makes This User Group Different

Elderly individuals are not simply "users with accessibility needs." They represent a fundamentally different design paradigm, meaning that many of the frameworks designers typically use do not quite fit.

• Fear of Making Mistakes: A systematic review from 2025 on designing mobile applications for the elderly highlights several barriers: cognitive overload due to complex interfaces, fine motor difficulties making small touch screens unusable, and, most importantly, a fear of making mistakes. Unlike younger users who grew up with technology, older users tend to be more cautious and genuinely fear breaking something. This fear translates into serious anxiety and resistance.

• They May Not Be Direct Users: Often, the resident is the one being assessed, but it is the caregiver who holds the device and reads the screen. This means you are designing two different experiences simultaneously: one for clinical accuracy and speed, and the other for comfort and dignity. Human-computer interaction researchers have recently begun advocating for technologies where the person with dementia is "an active rather than passive user of technology in managing" their own care, but there is still no clear vision of what this will look like.

• Active Resistance to the Product: Compared to other age groups, elderly individuals tend to show the lowest levels of trust in technology. Observing my own family, I also find that when someone suffers from a chronic illness like dementia, anything unfamiliar can provoke anxiety or even anger. Wearable fall detectors are often removed or turned off. Anything that resembles or feels like surveillance can make them extremely uncomfortable and vulnerable.

Current Issues and Solutions in AI

These constraints push design teams to be more creative. Several AI products are already addressing the biggest issues: undetected pain, falls, and loneliness.

• Undetected Pain: Studies show that pain is significantly underdiagnosed in individuals with cognitive impairments. Traditional pain assessments rely on caregivers observing the patient's facial expressions and body language, which is not only subjective and inconsistent but also vulnerable to racial and gender biases in interpreting expressions.

  • Product: PainChek, developed in Australia, is an app designed to detect pain. A caregiver records a short video of the resident's face. The AI then analyzes tiny muscle movements related to pain expressions. The caregiver then works through guided checklists in five other areas (voice, movement, behavior, activity, body). The app combines AI and human judgment to generate an overall pain score.

• Falls: Falls are one of the leading causes of unexpected hospital admissions among the elderly. Traditional fall detection tools typically require the person to press a button after falling, which many cannot do after a fall.

  • Products: Nobi, a Belgian company, manufactures AI-powered ceiling lamps that detect falls and monitor sleep and behavior. Sensi.AI uses a constantly active audio device—no cameras, no wearables, no screens or interfaces for the elderly user.

Loneliness

Many nursing home residents spend days without meaningful conversation. Some cannot physically or mentally get out of bed to meet people. Social isolation is extremely dangerous for the elderly. Research links it to higher rates of dementia, depression, heart disease, and premature death.

• Design Challenge: For traditional users, companion products often resemble cute pets or objects meant to form bonds with. However, when researchers asked elderly individuals what they wanted, they stated they did not want a toy or a pet. They desired a stationary object that recognizes their presence, engages in conversation, and offers support.