How the science and practice of compassion in healthcare can inform a new era of human-AI intelligent caring.
Copyright: elizabethmmorrow.wixsite.com – “Human-AI Intelligent Caring”
This post draws on new research by a multidisciplinary team of researchers and technologists in the UK and USA to examine how the science and practice of compassion in healthcare can inform a new era of human-AI intelligent caring. The evidence shows that AI technologies can generate and support compassion in healthcare systems in a range of ways from increasing empathetic awareness and empathetic response, to improving communication, and providing patients with tailored information, health coaching or treatments. Future research and development into human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.
Why compassion?
Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviours benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored.
New research into the global technology landscape offers a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion. A systematic scoping review following five steps of Joanna Briggs Institute methodology identified 197 studies and articles relating to both compassion and AI (including AI concept and design studies in the healthcare space). The findings show that the number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan–Aug 2022 n = 35 articles) indicating a growing interest in the potential of using AI to generate or support compassion in healthcare.
What are the main developments and debates?
Emerging debates centre on concerns about AI ethics, healthcare jobs, and potential loss of empathy in healthcare settings. There is a growing body of evidence on the benefits of human-centered design of AI technologies for healthcare. As well as optimistic speculation that AI technologies will address care gaps in health systems associated with ageing populations. These arguments have fuelled discussion and interrogation of what it means to be human and to care. Overall there is recognition of future potential of AI for patient monitoring, virtual proximity, and widening access to healthcare. Other debates focus on the need for curricula development and healthcare professional education as well as implementation of AI applications to enhance health and wellbeing of the healthcare workforce.
How can AI technologies enhance compassion?
Themes in the literature demonstrate at least 10 ways that AI can enhance compassion in healthcare. These are:
- Empathetic awareness
- Empathetic response and relational behaviour
- Communication skills
- Health coaching
- Therapeutic interventions
- Moral development learning
- Clinical knowledge and clinical assessment
- Healthcare quality assessment
- Therapeutic bond and therapeutic alliance
- Providing health information and advice
What are the current gaps in knowledge?
Currently, the main gaps in knowledge are to do with the educational effectiveness of AI-assisted learning; understanding patient diversity and AI technologies; implementation challenges associated with adopting AI technologies in education and practice settings; as well as uncertainties about the safety and clinical effectiveness of specific AI technologies and when used in combination. Key areas for the development of human-AI intelligent caring are:
- Enriching education, learning and clinical practice
- Extending healing spaces
- Enhancing healing relationships
Reconceptualising compassion in an age of AI
The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring (illustrated by the figure above) comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering.
Conclusion
The association between AI technologies and compassion in healthcare is attracting more interest internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance components of compassion. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.
Implications
In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.
Read the full systematic scoping review here:
Morrow, E., Zidaru, T., Ross, F., Mason, C., Patel, K. D., Ream, M., Stockley, R. (2023) Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. Frontiers Psychology., 17 January 2023. Sec. Human-Media Interaction. Vol 13 – 2022. https://doi.org/10.3389/fpsyg.2022.971044
Der Beitrag Human-AI Intelligent Caring erschien zuerst auf SwissCognitive, World-Leading AI Network.