Automation caregiving: Should we hand over the care of loved ones to robots?

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Automation caregiving: Should we hand over the care of loved ones to robots?

Automation caregiving: Should we hand over the care of loved ones to robots?

Subheading text
Robots are used to automate some repetitive caregiving tasks, but there are concerns they may reduce levels of empathy towards patients.
    • Author:
    • Author name
      Quantumrun Foresight
    • October 7, 2022

    Insight summary

    The integration of robots and automation in caregiving is transforming the industry, potentially reducing costs and improving efficiency but also raising concerns about unemployment and reduced human empathy. This shift could prompt changes in caregiver roles, focusing on psychological support and technical management of caregiving machines while also influencing business models and government regulations. Balancing technological advancements with the need for human touch and privacy protection is crucial in shaping the future of elderly care.

    Automation caregiving context

    As robots and automation software become more commonplace, the caregiving industry faces an uncertain future. While automation may lead to decreased costs and increased efficiency, it can also result in widespread unemployment within the sector and a lack of empathy towards patients.

    Personal assistance occupations (especially in the healthcare sector) are expected to be among the fastest-growing jobs, contributing about 20 percent to all new employment by 2026, according to a 10-year US Bureau of Labor Statistics survey. At the same time, many personal assistance occupations will experience workforce shortages during this same period. In particular, the elderly care sector will already have a shortage of human workers by 2030, when 34 countries are projected to become “super-aged” (one-fifth of the population is over 65 years old). Automation is anticipated to lessen some of the severe consequences of these trends. And as the cost of producing a robot decreases by a projected USD $10,000 per industrial machine by 2025, more sectors will use them to save on labor costs. 

    In particular, caregiving is a field interested in testing automation strategies. There are examples of robot caregivers in Japan; they dispense pills, act as companions for the elderly, or provide physical assistance. These robots are often cheaper and more efficient than their human counterparts. In addition, some machines work alongside human caregivers to help them provide better care. These “collaborative robots,” or cobots, assist with basic tasks like lifting patients or monitoring their stats. Cobots allow human caregivers to focus on providing emotional support and psychological care to their patients, which may be a more valuable service than routine tasks like dispensing medication or bathing.

    Disruptive impact

    Automation in elderly care presents a significant shift in how society approaches caregiving, with far-reaching implications. In the first scenario, where robots perform routine tasks like medication dispensing and basic comfort provision, there's a risk of commoditizing human empathy. This trend could lead to a societal divide, where human care becomes a luxury service, heightening disparities in care quality. As machines increasingly handle predictable tasks, the unique human aspects of caregiving, like emotional support and personal interaction, could become exclusive services, accessible mainly to those who can afford them.

    In contrast, the second scenario envisions a harmonious integration of technology and human touch in elderly care. Here, robots are not just task executors but also serve as companions and counselors, taking on some emotional labor. This approach elevates the role of human caregivers, allowing them to focus on delivering deeper, more meaningful interactions like conversations and empathy. 

    For individuals, the quality and accessibility of elderly care will be directly influenced by how these technologies are implemented. Businesses, particularly in the healthcare and technology sectors, may need to adapt by developing more sophisticated, empathetic robots while also training human caregivers in specialized skills. Governments may need to consider regulatory frameworks and policies to ensure equitable access to quality care, balancing technological advancement with the preservation of human dignity and empathy in caregiving. 

    Implications of automation caregiving

    Wider implications of automation caregiving may include: 

    • Increasing concerns about algorithmic bias that may train machines to assume that all senior citizens and people with disabilities act similarly. This trend may lead to more depersonalization and even poor decision-making.
    • The elderly insisting on human care instead of robots, citing privacy violations and lack of empathy.
    • Human caregivers being retrained to focus on providing psychological and counseling support, as well as the management and maintenance of caregiving machines.
    • Hospices and elderly homes using cobots alongside human caregivers to automate tasks while still providing human oversight.
    • Governments regulating what robot caregivers are allowed to do, including who will be responsible for life-threatening errors committed by these machines.
    • Healthcare industries adapting their business models to integrate advanced training programs for caregivers, focusing on psychological support and technical skills for managing caregiving technology.
    • Consumer demand for transparent and ethical use of personal data in caregiving robots, leading to companies developing clearer privacy policies and secure data handling practices.
    • Policies emerging to ensure equitable access to advanced caregiving technologies.

    Questions to consider

    • If you think caregiving should be automated, what is the best way to go about it?
    • What are the other potential risks and limitations of involving robots in caregiving?

    Insight references

    The following popular and institutional links were referenced for this insight: