Artificial intelligence (AI) allows machines to analyse and solve problems utilizing heuristic, stochastic, fuzzy and other computational paradigms including biological principles (Xu et al., 2019). AI can learn from experiential data to automatically model and solve complex problems that may exceed the capacity of humans. AI-based deep learning algorithms have been found in certain instances to be superior to human clinicians in diagnosis, for example, pathologists in detecting the spread of breast cancer (Ehteshami 322et al., 2017). The current generation of AI systems is widely used in applications that enhance daily human life and those that further sophisticated research. AI and AE researchers could make significant strides in healthcare if AI can generate empathy at appropriate levels to optimize the delivery and effectiveness of healthcare services. Care provision robotics, for instance (as opposed to surgical robots), could ease the current care crisis due to longer life expectancy, the burden of multi-morbidity and shortage of skilled care-provision workforce. But a significant challenge for AI is the possession and deliverance of the human attribute of empathy. In this chapter, we strive to describe the trait of human empathy, analyse the possibility of implementing it using AI, explore the limitations in doing so and briefly discuss the perceivable wide-ranging repercussions of ARTIFICIAL EMPATHY (AE) specifically in the healthcare context while projecting future directions.
|Title of host publication||Artificial Intelligence Applications in Healthcare Delivery|
|Place of Publication||Milton Park|
|Number of pages||6|
|Publication status||E-pub ahead of print - 3 Dec 2020|