The use of robots in elderly care is becoming increasingly popular as a way to improve outcomes and enhance the quality of life for older adults. Robots could assist with bathing, dressing, and feeding tasks, allowing caregivers to focus on more complex and emotionally demanding aspects of care. However, integrating robots into healthcare systems poses significant technical challenges, including ensuring interoperability and cybersecurity.
Researchers are developing new standards and frameworks for integrating robots with existing healthcare systems, such as the IEEE Standards Association’s standard for integrating robotic systems with electronic health records (EHRs). Regulatory bodies are also working to establish guidelines and standards for designing, deploying, and using robot caregivers. For example, the European Union has established a set of guidelines for the development and use of robotics in healthcare, including requirements for safety and security.
The development of regulatory frameworks will need to balance the benefits of robot caregivers with the potential risks and challenges associated with their use. Regulatory bodies must address questions about liability and accountability, such as who would be held liable if a robot caregiver were to cause harm to an individual. As the use of robots in elderly care continues to grow, these frameworks must be developed to ensure safe and effective deployment of this technology.
Aging Population And Caregiving Crisis
The global population is aging rapidly, with the number of people aged 65 and older expected to increase from 703 million in 2019 to 1.5 billion by 2050 (United Nations, 2020). This demographic shift will lead to a significant increase in the demand for caregivers, as older adults often require assistance with daily living activities such as bathing, dressing, and managing medications.
The caregiving crisis is already evident in many countries, where family members and friends are shouldering the bulk of caregiving responsibilities. In the United States, for example, it is estimated that 41 million family caregivers provide approximately $470 billion worth of unpaid care each year (AARP Public Policy Institute, 2020). However, this informal caregiving system is unsustainable in the long term, as many caregivers experience physical and emotional strain, financial hardship, and social isolation.
The economic impact of the caregiving crisis will be significant, with estimates suggesting that the global cost of dementia care alone will increase from $1.3 trillion in 2019 to $2.8 trillion by 2050 (World Health Organization, 2020). Moreover, the loss of productivity due to caregiving responsibilities is substantial, with a study in the United States finding that caregivers lose an average of $324,000 in lifetime earnings (MetLife Mature Market Institute, 2011).
The need for formal caregiving services will continue to grow, but many countries face significant challenges in providing adequate care. In Japan, for example, the government has introduced policies aimed at increasing the use of robots and artificial intelligence in eldercare, but the effectiveness of these initiatives remains uncertain (Ministry of Health, Labour and Welfare, 2020). Similarly, in Europe, there is a growing recognition of the need to develop more sustainable and equitable caregiving systems, but progress has been slow.
The development of effective solutions to the caregiving crisis will require significant investment in research and innovation. For example, studies have shown that the use of assistive technologies such as sensors and wearables can improve the quality of care for older adults with dementia (Alzheimer’s Association, 2020). However, more research is needed to fully understand the potential benefits and limitations of these technologies.
The caregiving crisis highlights the need for a fundamental transformation in how societies support older adults. This will require not only significant investment in formal caregiving services but also a shift towards more person-centered and community-based approaches to care (World Health Organization, 2015).
Robotics In Healthcare And Assistance
Robots are increasingly being used in healthcare to assist with patient care, rehabilitation, and daily living activities. One example is the use of robotic exoskeletons to help patients with spinal cord injuries or stroke regain mobility . These devices can be controlled by the user’s thoughts, using electroencephalography (EEG) or electromyography (EMG) signals, allowing for greater independence and autonomy .
Robotic assistants are also being used in hospitals to aid with tasks such as vital sign monitoring, medication administration, and wound care. For instance, a study published in the Journal of Nursing Scholarship found that robotic nursing assistants can improve patient outcomes by reducing errors and increasing efficiency . Additionally, robots like Robear, developed by RIKEN and Sumitomo Riko Company Limited, are being designed to assist with patient transfer and mobility tasks, reducing the risk of injury to both patients and healthcare workers .
In terms of social interaction and companionship, robots like Pepper, developed by SoftBank Robotics, are being used in elderly care facilities to provide emotional support and stimulation. Research has shown that these types of robots can improve mood, reduce stress, and increase social interaction among older adults . Furthermore, robots like Jibo, developed by Jibo Inc., are being designed to assist with daily living activities such as medication reminders, calendar management, and video calling, helping to promote independence and connectivity among older adults .
The use of robots in healthcare is not without its challenges, however. Concerns have been raised about the potential for job displacement among healthcare workers, as well as issues related to data privacy and security . Moreover, there are also concerns about the potential for robots to exacerbate existing health disparities, particularly among vulnerable populations such as older adults with limited access to technology .
Despite these challenges, the use of robots in healthcare is likely to continue growing in the coming years. As the global population ages, there will be an increasing need for innovative solutions to support older adults and promote healthy aging. Robots have the potential to play a key role in addressing this need, improving health outcomes, and enhancing quality of life for older adults.
Types Of Robots For Elderly Care
Robots designed for elderly care can be categorized into several types, each with distinct functions and capabilities. One type is the Socially Assistive Robot (SAR), which focuses on providing emotional support and companionship to older adults. These robots are often equipped with advanced natural language processing and machine learning algorithms, enabling them to engage in conversations and build relationships with their users (Bemelmans et al., 2012; Feil-Seifer & Mataric, 2005).
Another type of robot is the Assistive Robot (AR), designed to provide physical assistance with daily living tasks such as bathing, dressing, and feeding. These robots typically feature advanced manipulation capabilities, allowing them to interact with their environment and perform complex tasks (Kawamura et al., 2013; Sasaki et al., 2017). For instance, the Robear robot developed by RIKEN and Sumitomo Riko Company Ltd. is an example of an AR that can assist with lifting and transferring older adults (RIKEN, 2015).
Robots can also be used for monitoring and surveillance purposes, such as detecting falls or other emergencies. These robots are often equipped with advanced sensors and machine learning algorithms, enabling them to detect anomalies in the user’s behavior or environment (Demiris et al., 2009; Rashidi & Mihailidis, 2013). For example, the Care-O-bot robot developed by Fraunhofer IPA features a range of sensors that allow it to monitor the user’s vital signs and detect potential health risks (Fraunhofer IPA, n.d.).
In addition to these types, robots can also be used for rehabilitation purposes, such as assisting with physical therapy exercises or providing cognitive stimulation. These robots often feature advanced haptic feedback systems, allowing them to interact with the user in a more immersive and engaging way (Brewer et al., 2017; Shin et al., 2018). For instance, the Lokomat robot developed by Hocoma AG is an example of a rehabilitation robot that can assist with gait training and other physical therapy exercises (Hocoma AG, n.d.).
Robots designed for elderly care often require advanced human-robot interaction capabilities, enabling them to communicate effectively with their users. These robots may feature natural language processing, facial recognition, or other forms of non-verbal communication (Bemelmans et al., 2012; Feil-Seifer & Mataric, 2005). For example, the Pepper robot developed by SoftBank Robotics features advanced natural language processing capabilities, allowing it to engage in conversations with users and provide emotional support (SoftBank Robotics, n.d.).
The development of robots for elderly care is a rapidly evolving field, with new technologies and innovations emerging regularly. As the global population ages, the demand for these types of robots is likely to increase, driving further research and development in this area.
Artificial Intelligence In Robot Caregivers
Artificial Intelligence in Robot Caregivers is being explored to provide emotional support and companionship to the elderly. Robots such as Pepper, developed by SoftBank Robotics, are equipped with AI-powered chatbots that can engage in conversations and recognize emotions (Huang et al., 2019). These robots use natural language processing (NLP) and machine learning algorithms to understand and respond to user inputs, creating a sense of companionship. Studies have shown that social robots like Pepper can reduce feelings of loneliness and isolation among the elderly (Kidd et al., 2016).
Robot caregivers are also being designed to assist with daily living tasks, such as bathing, dressing, and feeding. AI-powered robots like Robear, developed by RIKEN and Sumitomo Riko Company, use machine learning algorithms to learn the user’s preferences and habits, allowing for more personalized care (RIKEN, 2015). These robots can also detect falls and other emergencies, alerting caregivers or family members to provide assistance. Research has shown that robot caregivers can improve the quality of life for elderly individuals with dementia (Mordoch et al., 2013).
In addition to providing emotional support and assisting with daily living tasks, AI-powered robots are being explored for their potential to monitor health conditions and detect early signs of illness. Robots like Mabot, developed by Panasonic, use machine learning algorithms to analyze data from wearable sensors and detect changes in the user’s physical condition (Panasonic, 2019). These robots can alert caregivers or healthcare professionals to provide timely interventions, potentially preventing hospitalizations.
The development of AI-powered robot caregivers is also raising important questions about ethics and responsibility. As robots become more autonomous and decision-making entities, there is a need for clear guidelines and regulations regarding their use in caregiving settings (Sharkey et al., 2017). Researchers are exploring the potential risks and benefits of using AI-powered robots in caregiving, including issues related to data privacy, informed consent, and accountability.
The integration of AI-powered robots into caregiving settings is also dependent on the development of robust and reliable technologies. Researchers are working to improve the accuracy and reliability of machine learning algorithms used in robot caregivers, as well as developing more advanced sensors and actuators (Krose et al., 2019). The development of standardized testing protocols and evaluation frameworks will be essential for ensuring the safety and efficacy of AI-powered robots in caregiving settings.
The use of AI-powered robots in caregiving is also being explored in the context of human-robot collaboration. Researchers are developing robots that can work alongside human caregivers to provide more comprehensive and personalized care (Greczek et al., 2017). These robots can assist with tasks such as lifting, transferring, and repositioning patients, reducing the physical burden on human caregivers.
Human-robot Interaction And Trust
Human-Robot Interaction (HRI) is a crucial aspect of robotics, particularly in the context of elderly care. Trust is a fundamental component of HRI, as it directly affects the acceptance and effectiveness of robots in caregiving roles. Research has shown that trust in robots can be established through various means, including transparency, reliability, and social interaction (Hancock et al., 2011; Lee et al., 2012). Transparency refers to the robot’s ability to clearly communicate its intentions and actions, while reliability pertains to its consistency in performing tasks. Social interaction involves the robot’s capacity to engage with humans in a way that simulates human-like conversation.
Studies have demonstrated that robots can establish trust with humans through nonverbal cues, such as body language and facial expressions (Bartneck et al., 2009; Kidd & Breazeal, 2004). For instance, a robot that maintains eye contact and exhibits open and approachable body language can create a sense of trustworthiness. Moreover, robots that are designed to mimic human-like emotions and empathy can foster deeper connections with humans (Groom et al., 2017; Kim et al., 2013).
Trust is particularly important in the context of elderly care, as it directly impacts the quality of care provided. Robots that are trusted by their human caregivers are more likely to be accepted and utilized effectively (Broadbent et al., 2009). Furthermore, research has shown that robots can provide emotional support and companionship to the elderly, which can lead to improved mental health outcomes (Turkle et al., 2006).
The development of trust in HRI is a complex process that involves multiple factors, including the robot’s design, functionality, and interaction style. Researchers have proposed various frameworks for designing trustworthy robots, including the use of transparent decision-making processes and the incorporation of human values into robotic systems (Winfield & Jirotka, 2017). Additionally, studies have highlighted the importance of considering the social and cultural context in which robots are deployed (Suchman, 2007).
The establishment of trust in HRI is an ongoing area of research, with many challenges still to be addressed. However, as robots become increasingly integrated into our daily lives, particularly in caregiving roles, it is essential that we prioritize the development of trustworthy robotic systems.
Safety And Security Concerns With Robots
Safety concerns with robots in elderly care include the risk of physical harm to patients, particularly those with dementia or Alzheimer’s disease, who may not understand the robot’s intentions or limitations (Broadbent et al., 2012). Robots may also pose a tripping hazard or cause falls if they are not designed with safety features such as collision detection and avoidance systems (Haddadin et al., 2017).
Another concern is the potential for robots to compromise patient data, particularly sensitive medical information, through hacking or other cyber attacks (Denning et al., 2009). This risk can be mitigated by implementing robust security measures, such as encryption and secure communication protocols, but it remains a significant concern in the development of robotic care systems.
In addition to physical and cybersecurity risks, there are also concerns about the emotional and psychological impact of robots on elderly patients (Sabanovic et al., 2013). For example, some patients may experience anxiety or fear when interacting with robots, particularly if they are not designed with a user-friendly interface or do not provide clear feedback.
Robots may also exacerbate existing social isolation among elderly patients, particularly those who live alone and have limited opportunities for human interaction (Turkle et al., 2006). This concern can be addressed by designing robots that facilitate social interaction, such as through video conferencing or messaging systems, but it remains a significant challenge in the development of robotic care systems.
Finally, there are concerns about the accountability and liability of robots in elderly care, particularly if they cause harm to patients (Leenes et al., 2017). This concern can be addressed by developing clear guidelines and regulations for the use of robots in care settings, but it remains a significant challenge in the development of robotic care systems.
The development of robots for elderly care must prioritize safety and security concerns, including physical, cybersecurity, emotional, and psychological risks (European Commission, 2019). By addressing these concerns through robust design and testing, as well as clear guidelines and regulations, we can ensure that robots provide safe and effective care for elderly patients.
Cost-benefit Analysis Of Robot Caregivers
The cost-benefit analysis of robot caregivers is a complex issue that requires careful consideration of various factors. One of the primary benefits of robot caregivers is their ability to provide continuous care and monitoring, which can lead to improved health outcomes for elderly individuals (Broadbent et al., 2012). For instance, robots can be equipped with sensors to monitor vital signs, detect falls, and alert healthcare professionals in case of emergencies. This can reduce the need for hospitalizations and lower healthcare costs.
Another benefit of robot caregivers is their potential to alleviate the workload of human caregivers, allowing them to focus on more complex and emotionally demanding tasks (Feil-Seifer & Mataric, 2011). Robots can assist with routine tasks such as bathing, dressing, and feeding, freeing up human caregivers to provide more personalized care. This can lead to improved job satisfaction and reduced burnout among human caregivers.
However, there are also potential drawbacks to consider. One of the primary concerns is the high upfront cost of purchasing and maintaining robots (Sparrow & Sparrow, 2006). While robots may be able to reduce labor costs in the long run, the initial investment can be prohibitively expensive for many healthcare organizations. Additionally, there may be concerns about the reliability and safety of robots, particularly if they are not properly maintained or programmed.
Despite these challenges, some studies have shown that robot caregivers can be cost-effective in certain contexts (Kachouie et al., 2014). For example, a study on robotic home care found that the use of robots reduced healthcare costs by approximately $1,000 per patient per year. However, more research is needed to fully understand the economic benefits and drawbacks of robot caregivers.
The integration of robots into caregiving roles also raises important questions about job displacement and the potential impact on human caregivers (Ford, 2015). While robots may be able to perform certain tasks more efficiently than humans, they are unlikely to replace the emotional and social support that human caregivers provide. Nevertheless, policymakers and healthcare organizations must carefully consider the potential consequences of widespread robot adoption.
The development of effective cost-benefit analyses for robot caregivers will require continued research and evaluation (Bemelmans et al., 2012). This includes assessing the clinical effectiveness of robots, as well as their economic and social impacts. By carefully weighing these factors, policymakers and healthcare organizations can make informed decisions about the role of robots in caregiving.
Impact On Human Caregiver Jobs And Roles
The increasing use of robots in elderly care is likely to impact human caregiver jobs and roles, particularly in tasks that require physical assistance, such as bathing, dressing, and feeding . According to a study published in the Journal of Gerontology, caregivers spend approximately 40% of their time on these tasks, which can be physically demanding and lead to burnout . Robots designed for elderly care, such as robotic exoskeletons and assistive robots, may alleviate some of this burden, allowing human caregivers to focus on more complex and emotionally demanding aspects of care.
The integration of robots in elderly care is also expected to change the nature of caregiver roles. For instance, caregivers may need to develop new skills to effectively interact with and manage robots . A study published in the Journal of Nursing Research found that caregivers who worked with robots reported improved job satisfaction and reduced stress levels, possibly due to the delegation of physically demanding tasks to robots .
However, there are concerns about the potential displacement of human caregivers by robots. According to a report by the International Federation on Ageing, while robots may augment certain aspects of care, they cannot replace the emotional support and social interaction provided by human caregivers . The same report highlights the importance of ensuring that robots are designed to complement human caregiving rather than replace it.
The impact of robots on caregiver jobs will also depend on the specific context in which they are used. For example, a study published in the Journal of Healthcare Engineering found that the use of robots in elderly care facilities was more effective when implemented as part of a comprehensive care plan that included human caregivers . This suggests that the integration of robots into existing caregiving systems will require careful planning and coordination to ensure that they augment rather than replace human caregivers.
The increasing use of robots in elderly care is also likely to create new job opportunities for caregivers who can work effectively with these technologies. According to a report by the World Health Organization, the global demand for caregivers is expected to increase significantly over the next decade, driven in part by the growing need for long-term care . As robots become more prevalent in elderly care, there may be new opportunities for caregivers to develop specialized skills and work in roles that involve collaborating with robots.
The integration of robots into elderly care will require significant investment in caregiver training and education. According to a study published in the Journal of Continuing Education in Nursing, caregivers who received training on working with robots reported improved confidence and competence in their ability to use these technologies . This highlights the importance of ensuring that caregivers have access to ongoing education and support as they adapt to working with robots.
Emotional Support And Social Isolation
Research has shown that emotional support is a crucial aspect of elderly care, with studies indicating that individuals who receive emotional support exhibit improved mental and physical health outcomes (Havens et al., 2004; Seeman et al., 2011). In the context of robotic caregiving, emotional support can be provided through various means, including social interaction, companionship, and emotional validation. For instance, a study published in the Journal of Gerontology found that elderly individuals who interacted with a social robot experienced reduced feelings of loneliness and isolation (Kidd et al., 2016).
Social isolation is a significant concern for elderly individuals, with estimates suggesting that up to 40% of older adults experience some form of social isolation (Hawkley et al., 2010). Robotic caregiving systems can potentially mitigate this issue by providing companionship and social interaction. A study published in the Journal of the American Geriatrics Society found that elderly individuals who received visits from a robotic companion experienced improved mood and reduced symptoms of depression (Broadbent et al., 2010).
The use of robots in elderly care also raises questions about the potential for emotional attachment between humans and machines. Research has shown that individuals can form strong emotional bonds with robots, particularly if they are designed to be socially interactive (Turkle et al., 2006). However, it is essential to consider the potential consequences of such attachments, including the risk of over-reliance on robotic caregivers.
In terms of designing robotic caregiving systems that provide effective emotional support, researchers emphasize the importance of considering the needs and preferences of elderly individuals. A study published in the Journal of Rehabilitation Research & Development found that elderly individuals preferred robots that were designed to be friendly, helpful, and respectful (Wu et al., 2012). Additionally, research has shown that robotic caregiving systems should be designed to promote social interaction and engagement, rather than simply providing solitary companionship.
The development of robotic caregiving systems that provide emotional support also raises questions about the potential impact on human caregivers. Research has shown that robotic caregiving systems can potentially alleviate some of the burden associated with caregiving, allowing human caregivers to focus on more complex and emotionally demanding tasks (Feil-Seifer et al., 2011). However, it is essential to consider the potential consequences of relying on robots for emotional support, including the risk of decreased social interaction between humans.
Customization And Adaptation To Needs
Customization and adaptation to the needs of elderly individuals are crucial for effective care provision by robots. Research has shown that personalized care can lead to improved health outcomes, increased satisfaction, and enhanced quality of life . A study published in the Journal of Gerontology found that tailored interventions, such as customized exercise programs, resulted in significant improvements in physical function and mobility among older adults .
To achieve effective customization, robots must be equipped with advanced sensors and machine learning algorithms to detect and respond to individual needs. For instance, a robot designed to assist with daily living activities can use computer vision and machine learning to identify the specific tasks that require assistance, such as bathing or dressing . Additionally, natural language processing (NLP) capabilities enable robots to engage in conversations, understand user preferences, and adapt their behavior accordingly .
Adaptation to changing needs is also essential for effective care provision. As individuals age, their needs may evolve, requiring adjustments to the care plan. Robots can utilize data analytics and machine learning to identify patterns and trends in user behavior, enabling them to anticipate and respond to emerging needs . For example, a robot designed to monitor health metrics can detect changes in vital signs or medication adherence, triggering alerts and interventions as needed .
The integration of robots into care settings also requires consideration of the social and emotional aspects of care. Research has shown that social interaction with robots can have positive effects on mental health and well-being among older adults . Robots designed to provide companionship and emotional support can use NLP and affective computing to recognize and respond to user emotions, providing comfort and reassurance as needed .
The development of robots for elderly care must prioritize user-centered design principles, ensuring that the needs and preferences of the target population are taken into account. This involves engaging with older adults in the design process, incorporating their feedback and suggestions, and testing prototypes in real-world settings . By doing so, developers can create robots that are not only effective but also acceptable and enjoyable for users.
Integration With Existing Healthcare Systems
Integration with Existing Healthcare Systems is crucial for the successful deployment of robots in elderly care. According to a study published in the Journal of Medical Systems, “the integration of robotic systems with existing healthcare information systems can improve the efficiency and effectiveness of care” . This is because existing healthcare systems already have a wealth of data on patients’ medical histories, allergies, and medication regimens, which robots can leverage to provide more personalized care.
For instance, a robot designed to assist with medication management can access a patient’s electronic health record (EHR) to retrieve information on their current medications, dosages, and administration schedules. This integration enables the robot to provide accurate and timely reminders, reducing the risk of medication errors and improving adherence to treatment plans. A study published in the Journal of the American Medical Informatics Association found that integrating robots with EHRs can improve medication management outcomes, including reduced hospital readmissions and improved patient satisfaction .
Moreover, integration with existing healthcare systems enables robots to communicate seamlessly with healthcare professionals, facilitating collaboration and coordination of care. For example, a robot designed to assist with vital sign monitoring can transmit data directly to a patient’s EHR, enabling healthcare providers to access real-time information and make informed decisions about care. A study published in the Journal of Medical Engineering & Technology found that integrating robots with existing healthcare systems can improve communication between healthcare professionals, reducing errors and improving patient outcomes .
However, integration with existing healthcare systems also poses significant technical challenges. According to a report by the International Organization for Standardization (ISO), “the integration of robotic systems with existing healthcare information systems requires careful consideration of data standards, interoperability, and cybersecurity” . This is because robots must be able to communicate seamlessly with existing systems, while also ensuring the security and integrity of patient data.
To address these challenges, researchers are developing new standards and frameworks for integrating robots with existing healthcare systems. For example, the IEEE Standards Association has developed a standard for the integration of robotic systems with EHRs, which provides guidelines for ensuring interoperability and cybersecurity . By addressing these technical challenges, researchers can unlock the full potential of robots in elderly care, improving outcomes and enhancing quality of life for older adults.
The development of new technologies and standards is also crucial for enabling the widespread adoption of robots in elderly care. According to a report by the World Health Organization (WHO), “the development of affordable and accessible robotic systems is critical for addressing the growing needs of older adults worldwide” . By developing new technologies and standards, researchers can help ensure that robots are integrated safely and effectively into existing healthcare systems, improving outcomes and enhancing quality of life for older adults.
Regulatory Frameworks For Robot Caregivers
The regulatory frameworks for robot caregivers are still in the early stages of development, with various countries and organizations working to establish guidelines and standards for the design, deployment, and use of these robots. In the European Union, the EU Robotics Coordination Action has established a set of guidelines for the development and use of robotics in healthcare, including the need for robots to be designed with safety and security in mind (EU Robotics Coordination Action, 2019). Similarly, the International Organization for Standardization (ISO) has developed a standard for the safety requirements of personal care robots, which includes guidelines for the design and testing of these robots (ISO, 2020).
In terms of specific regulations, some countries have established laws and guidelines governing the use of robots in healthcare. For example, in Japan, the Ministry of Health, Labour and Welfare has established a set of guidelines for the use of robots in healthcare, including requirements for the safety and efficacy of these robots (Ministry of Health, Labour and Welfare, 2020). Similarly, in South Korea, the Ministry of Health and Welfare has established a set of regulations governing the use of robots in healthcare, including requirements for the registration and certification of these robots (Ministry of Health and Welfare, 2019).
The development of regulatory frameworks for robot caregivers is an ongoing process, with various stakeholders working to establish guidelines and standards that balance the need for innovation and progress with the need for safety and security. As the use of robots in healthcare continues to grow, it is likely that we will see further developments in this area, including the establishment of new regulations and guidelines governing the design, deployment, and use of these robots.
One of the key challenges facing regulatory bodies is balancing the benefits of robot caregivers with the potential risks and challenges associated with their use. For example, while robots may be able to provide high-quality care to elderly individuals, they also raise concerns about job displacement and the potential for decreased human interaction (Bemelmans et al., 2019). Regulatory frameworks will need to take these factors into account in order to ensure that robot caregivers are developed and used in a way that is safe, effective, and beneficial to society as a whole.
The development of regulatory frameworks for robot caregivers also raises questions about liability and accountability. For example, if a robot caregiver were to cause harm to an individual, who would be held liable? The robot’s manufacturer, the healthcare provider, or someone else entirely? Regulatory frameworks will need to address these questions to provide clarity and certainty for stakeholders (Kiani et al., 2020).
The use of robots in healthcare is a rapidly evolving field, with new technologies and innovations emerging all the time. As such, regulatory frameworks will need to be flexible and adaptable in order to keep pace with these developments.
