Don't Get Old!
Eldercare Robots
Are of Little Help
Turns out, eldercare assistive robots are super difficult to design and build
Don’t get old!
As someone who was a homecare giver to my elderly parents for years—one parent with Alzheimer’s and the other with end-stage Parkinson’s—I’m a pro at sizing up a purported eldercare robot’s ability to perform real care. Sadly, there are none that I have found that are even remotely effective.
Gets me to wondering, who the hell designs these things? Certainly, no one with any real understanding or empathy for what being old and needing help is all about.
Very depressing as well is to Google images of eldercare robots only to see the woeful array of what’s available.
And I’m not alone. James Wright’s piece in MIT Technology Review is equally puzzled when he writes about the lack of success with eldercare robots: “Why haven’t they taken off? The answer tells us something about the limitations of techno-solutionism and the urgent need to rethink our approach to care.”
There’s certainly a need for eldercare robots. According to data from the United Nations, approximately 13.5% of the world’s people were at least 60 years old in 2020, and by some estimates, that figure could increase to nearly 22% by 2050.
Worse still, and frightening, “globally, the number of persons aged 80 or over is projected to triple by 2050, from 137 million in 2017 to 425 million in 2050. By 2100 it is expected to increase to 909 million, nearly seven times its value in 2017.” Wow, nearly a billion people over 80!
That means, of course, that there is a growing need for eldercare robots, “The eldercare assistive robots industry worldwide ($2.3 billion in 2023) is expected to reach a projected revenue of $6.7 billion by 2030. A compound annual growth rate of 14.9% is expected of the worldwide eldercare, assistive robot industry from 2024 to 2030.”
So, there’s an obvious need and a market for eldercare assistive robots. However, sales of $2.3 billion is a pittance in the face of how many elderly need assistive aid. What’s the problem?
More and more, it’s looking like if you are elderly and in need of eldercare, then don’t look to an eldercare robot for much help. In fact, it seems that even some caregivers have grave misgivings about a robot’s ability to deliver quality care to their elderly patients. Home caregivers like myself are not getting any substantive help anytime soon from robots. BTW: There will be 3.8 million unpaid family caregivers, like myself, in the U.S. by 2030. By 2040, unpaid family caregivers will top 11 million in the U.S.
And that’s just in the U.S. Imagine what East Asia is facing with its demographic decline. The situation is critical in China, Japan, and Korea.
Turns out, eldercare assistive robots are super difficult to design and build, which is probably one mega reason why no one seems to want to take on the project, and those that do, fall way short of success.
In need of answers, I went to my local Delphic oracle (ChatGPT) for answers. The response I got from my prompt: “Designing, building, and deploying eldercare assistive robots is challenging due to a combination of technical, practical, social, ethical, and regulatory factors,” was amazing and shocking.
Well, I then prompted, can you give some details about the key challenges?
Here's What ChatGPT Let Us Know About Making Eldercare Robots
Designing, building, and deploying eldercare assistive robots is challenging due to a combination of technical, practical, social, ethical, and regulatory factors. Here are the key difficulties:
Technical Challenges
- Complex and Dynamic Environments:
- Unpredictable Settings: Homes are varied and often cluttered, with furniture, pets, and personal items that can change location frequently.
- Navigation and Mobility: Robots need to navigate tight spaces, uneven flooring, and various obstacles, which requires advanced mobility and sensor technologies.
- Human-Robot Interaction (HRI):
- Natural Communication: Robots must understand and respond to natural human speech, gestures, and expressions, which are/ complex and context-dependent.
- Personalization: They must adapt to individual preferences, habits, and health conditions, requiring sophisticated learning algorithms and adaptability.
- Cognitive Capabilities:
- Context Awareness: Recognizing and interpreting the context of interactions, such as understanding whether a person needs help or is just moving around.
- Decision Making: Making real-time decisions and adapting to new situations based on limited and sometimes ambiguous information.
Practical Challenges
- Reliability and Maintenance:
- Durability: Robots must be robust enough to operate reliably over long periods with minimal maintenance.
- Battery Life: Ensuring sufficient battery life for extended operation without frequent recharging.
- Cost:
- High Development Costs: Developing advanced robotics technology is expensive, and producing cost-effective solutions is challenging.
- Affordability: Ensuring that these robots are affordable for elderly individuals and healthcare providers.
Social and Ethical Challenges
- User Acceptance:
- Trust and Comfort: Elderly individuals may have difficulty trusting or feeling comfortable with robots, especially if they are not familiar with technology.
- Cultural Differences: Acceptance and use of robots can vary significantly across different cultures and personal beliefs.
- Privacy and Autonomy:
- Privacy Concerns: Robots equipped with cameras and sensors may raise concerns about privacy and data security.
- Autonomy vs. Control: Balancing the robot’s autonomy with the user’s need for control and independence.
Regulatory and Standardization Challenges
- Regulations and Compliance:
- Health and Safety Standards: Complying with stringent health and safety regulations, which can vary by country and region.
- Data Security and Privacy: Ensuring that robots adhere to data protection laws and safeguard users’ personal information.
- Interoperability:
- Integration with Existing Systems: Ensuring that robots can seamlessly integrate with existing healthcare systems, smart home technologies, and other assistive devices.
Case Studies and Iterative Design
- Real-world Testing:
- Pilot Programs: Conducting pilot programs and real-world testing to gather user feedback and refine robot designs based on actual use cases.
- Continuous Improvement: Iteratively improving robot capabilities and addressing issues identified during deployment.
Conclusion
Creating eldercare assistive robots requires overcoming numerous challenges, from technical and practical to social and ethical considerations. It involves interdisciplinary collaboration, significant investment, and ongoing innovation. Addressing these challenges is crucial to developing effective and widely accepted elder care robots that can improve the quality of life for elderly individuals.