1. Watson, Daniel BSN, RN-BC
  2. Womack, Joshua BSN, RN, RNC-OB
  3. Papadakos, Suzanne BSN, RN, RNC-OB, C-EFM


Much like other aspects of health care, nursing has become increasingly saturated with technology over the past several decades. Existing technology has advanced nursing in many ways and contributed to patient safety but at the cost of decreasing nurse-patient interaction. As health care technology progresses to the inclusion of artificial intelligence (AI), the future impact on nursing and direct patient care remains largely unknown, unexplored, and difficult to predict. This article aims to explore the relevance of nursing in a technologically advanced postmodern health care system. The relevance of nursing in the future is solidified by the unique nature of nursing that includes the embodiment of human caring and emotional intelligence. Nurses' abilities to intervene before patient deterioration, care for patients holistically, and manage various aspects of care will be heightened by the adoption of AI. Nurses should embrace AI technology, as we predict that it will decrease nurse workload and cognitive overload and allow for increased patient-nurse interaction. Current and future nurses should take the lead on determining how it augments nursing practice.


Article Content

THE NURSING population spans 3 generations with the average age of 51 years.1 The eldest generation of today's nurses is made up of baby boomers (born 1946-1964) who were born during an era that is defined by the dawn of automation (1946) and the inception of artificial intelligence (AI) (1955).2 Modern popular culture disseminated through mass media, otherwise known as pop culture, played a defining role in showcasing AI through fictional storytelling in Hollywood films, comics, books, and television shows. Although pop culture brought AI robots to the forefront of consciousness in American society, AI was depicted in extremes that both captivated and frightened audiences. Rosie the Robot from the Jetsons is an example of an artificially intelligent humanoid that captivated a young baby boomer generation in the 1960s. She performed household duties, used speech and speech recognition, possessed learning capabilities, and showed emotion. Stoking fear in the 1980s and the 1990s, pop culture featured AI in movies such as The Terminator, which depicts an AI robot enhanced with a neural network that gains self-awareness and attempts to eliminate the human species for its own survival and dominance. Smartphones of the 2010s feature low-fidelity AI software with speech recognition but leave much room for improvement and often cause user frustration. Our culture's apprehension to fully embrace AI has been promulgated by the portrayal of AI in pop culture, use of low-fidelity handheld AI, and the robotic automated assembly line from the 1940s that caused many human jobs to become obsolete. There is no wonder why there is a palpable and foreboding apprehension toward AI technologies moving into health care. To nurses specifically, it is difficult to conceptualize how AI can deliver patient care with the same rigor, emotional intelligence, and assessment-based proficiency as a human nurse based on our own past and current exposure to technology.



Artificial intelligence was conceptualized in 1955 when a group of researchers attempted to see whether computers were capable of using language, problem solving, and improving its own performance.2 As AI continued to be developed and improved over the past 70 years, many terms have been coined to describe unique capabilities and its general conceptualization. Machine learning is a type of computer system that improves its own performance based on collected data.3,4 Deep learning refers to a computer system that improves its own performance with the aid of deep neural networks.4 Deep learning is the powerhouse behind the most sophisticated and well-known AI systems. Today, in both literature and mainstream accounts, artificial intelligence or simply AI is a general term referring to several types of computer technologies that possess abilities to learn from data and mimic human capabilities.5 A more recent term to consider with respect to AI is augmented intelligence. Augmented intelligence conceptualizes AI as an augment, rather than replacement, to human intelligence and physical performance. Human-in-the-loop hybrid-augmented intelligence describes AI that requires human interaction6 and appears to distinctly describe the type of AI this article will explore as it pertains to nursing. Using the cues from recent literature, this article will use AI as a broad term to describe technology that uses deep learning, machine learning, human-in-the-loop, or other forms of artificial or augmented intelligence.



Much like AI, the nursing profession has become increasingly saturated with advanced technology. The nursing profession was originally formed using basic scientific principles of the 19th century7 and nurses were full-time hands-on caregivers. Over the years, nursing care has changed with the influx of technology. Technology such as electronic charting, remote vital signs monitoring, and Pyxis machines has increasingly taken nurses away from the beside. Technology has advanced nursing in many ways and increased patient safety, but at the cost of decreasing nurse-patient interaction, which is crucial to ongoing physical and psychosocial assessment that encourages holistic healing. Should nurses fear the rise of the robots in health care, powered by various forms of AI, or should they welcome AI technology to harness and use it to improve nursing practice? The aim of this article is to explore the relevance of nursing in technologically advanced postmodern health care systems.


Physical-assistive robotics

So where are we today? Artificial intelligence already has a presence at the bedside in various forms. Robots outfitted with AI software can augment the physical tasks of nurses. The DaVinci surgeon-controlled robot compensates for the anatomical limitations of human hands during surgery.8 The precision of this assistive robot decreases operating room nurse responsibilities and increases surgeon efficiency while remaining less invasive than human hands alone.9 Xenex robots have proven to significantly reduce the spread of hospital-acquired infections in several health care settings including intensive care units (ICUs) using ultraviolet light to eliminate microorganisms.10 "Carebots" are emerging in the health care industry in response to the nursing shortage for the "silver tsunami". Robear, a carebot (technological device purposed to perform as a caretaker), resembles a polar bear and is capable of transferring patients in and out of bed or a wheelchair and assisting with ambulation.11,12 Using sensors that monitor patient patterns, these carebots can notify patient caregivers or emergency services if their situational awareness detects abnormalities.11 TUG robots address transportation logistics within health care facilities.13 Autonomous battery-powered carts deliver medications, laboratory samples, linen, and food to their designated destination.13


Social-assistive robotics

The fusion of AI software and robotic hardware enables robots to learn, react, and anticipate like humans.8 This type of robot currently works as social support to vulnerable populations such as children, the elderly, and those with disabilities.9 PARO robots in the appearance of harp seals form relationships with patients with dementia to positively alter pain and mood.14 Pepper, a humanoid robot, interacts with the environment and other humans in various settings as a concierge, receptionist, coach, companion, or educator.15 He recognizes several different languages and differentiates if he is speaking to a man, woman, or child.15 Eye sensors help Pepper perceive human emotion and respond appropriately.15 The advent of social robots seems to threaten integrity of human interaction. However, Pepper's seemingly compassionate instincts are merely projected emotions based on recorded cues.


Other platforms

In addition to artificially intelligent robots that support physical and social health care tasks, AI is analyzing big data, making decisions and treatment plans that positively affect patient outcomes. The SAS Institute defines big data as, "data that is so large, fast or complex that it's difficult or impossible to process using traditional methods."16 The predictive accuracy of these platforms is staggering. Some AI systems have been trained to classify medical imaging such as echocardiography with more accuracy than physicians.17 For diagnostic analysis, AI is analyzing radiographs and detecting breast cancer.18 Algorithms have shown excellent accuracy and specificity in classification of benign and cancerous cells.19 Several medical institutions are using AI as modified early warning score systems to identify patients at risk for deterioration.20 The National Health Service England is implementing a national acute kidney injury-automated detection platform.21 This algorithm has performed well at detecting acute kidney injury through tracking creatinine changes.21


Future AI

As the field of AI advances in health care, many companies are developing sophisticated AI systems that assist clinicians to make treatment and logistical decisions. WatsonPaths is a system designed to answer scenario-based questions.22 The answering system is designed to categorize a patient case scenario into multiple facts and explore each to recommend the most likely diagnosis or appropriate treatment.22 The system displays a sequence of reasoning and rationale leading to the most likely conclusion aiding providers in deducing the best treatment approach.22 Automated algorithms are also being proposed to assist with hospital resource management. These systems efficiently predict patient acuity and staffing needs to facilitate resource allocation.23


The ICU has been identified as a care area that can greatly benefit from AI. In an area that is saturated with data from multiple pieces of equipment, analytical systems that can make big data intelligible and useful are essential. Autonomous Healthcare is developing technology that can interface various machines at the ICU bedside, which currently work in isolation.24 The company is prioritizing the development of systems that can continuously manage patient ventilation and fluid titration.24


How AI is integrated into nursing hinges on the identity of the profession. It is obvious that there are facets of nursing that are irreplaceable, but what are they? Artificial intelligence's evident upgrade in patient safety cannot go unnoticed. But, how will the 2 operate for the betterment of nursing practice and patient care?



The nature of nursing as both an art and science is the broadly accepted description of the profession. Today, health care is driven by evidence-based care and research. However, this emphasis on science has reduced nursing's impact on the process of caring. Obscurity of art by science is an inherent problem of the profession when it is defined in such ambiguous and dichotomous terms. When compared with science and the criteria for understanding, art is not as easily defined or measured but innately open to interpretation. As will be further elaborated, the incorporation of science and lessons learned throughout one's nursing career is what precludes the segregation of science and art. Since the 2 are interchangeably reinforcing and dependent upon one another, we cannot talk about one without the other.


One of the most cited theories in the art of nursing is by Barbara Carper,25 who defined it as patterns of knowing. In this theory, the art is a creative pattern nurses use to recognize and perceive in order to guide care.25 As defined by Carper, esthetic (innate) knowledge is gathered by various humanistic methods of inquiry (empathy, personal, and ethical) a nurse uses to constantly shape the care process.25 In agreement with this definition-and in an attempt to marry both the art and the science of nursing-Bender and Holmes26 define the nature of nursing as a logical process, or a unique way of thinking. In this process, nurses shape the current reality of care by approaching the patient holistically-the sum of all parts (body, mind, and environment)-while remaining sensitive to the lability of human experience.26


The inability to define a nurse's processual approach to care emphasizes its complex and dynamic process. Literature supports the lack of a consensual definition of what the art of nursing looks like in practice, but this problem occurs only when nursing is viewed and researched as one or the other: science or art.26,27 The idea that nursing has a dual nature places a burden to demonstrate which principle is more important to health care outcomes, when in fact, the 2 work in concert. The process of nursing is humanistic, steeped in emotional intelligence (Table), and the embodiment of human caring. The inability to fully define nursing or remove the humanistic aspects insinuates the inability for AI to fully replace it.

Table. Emotional Int... - Click to enlarge in new windowTable. Emotional Intelligence

Historically, nursing has continuously redefined its role in health care: from an apprenticeship model at the bedside to its own science and advanced practices. The nursing profession, in step with its nature, continuously evolves. As technology is progressively incorporated into health care, nursing's approach to its use in care delivery should match that progression as an augmentation of current care.



Fundamentals of Boykin and Savina's Nursing as Caring model31 and Jean Watson's Theory of Human Caring32 are founded on the assumption that humans are caring beings. The caring nature of humanity is germane to nursing. According to Sister Simone Roach's33 5 Cs of caring, competence is caring. Nurses are ingrained with a nursing standard of competence. Patricia Benner's34 model levels competence as the middle ground between novice and expert nurses. A nurse demonstrates competence in practice when his or her actions are attributable to long-range patient care goals that the nurse is able to construct.34 With experience, nurses are able to move from task-oriented, rule-based practice to a holistic context-driven perspective.34 In a world immersed in technology, nurses find themselves responsible for various technologies at the bedside. A nurse's technological competence equates to caring as Rozzano Locsin presented in his Theory of Technological Competency as Caring in Nursing.35


Knowing the patient more fully

Technological competency in nursing strengthens nursing practice. The care that nurses render with technological competence allows the nurse to know the patient more fully.35 Machines at the bedside that provide moment-to-moment patient feedback via AI reveal more about the patient than the nurse gleans from a moment-in-time assessment. The data from AI machines in addition to the nurse's assessment and relationship create a fuller picture of the patient's status allowing for greater engagement.35 The automated function of technology also assumes redundant and time-consuming considerations, allowing the nurse to cede tedious actions that detract from full engagement.35 The relationship granted by moment-to-moment patient feedback via AI enables the nurse and the patient to build the patient's experience of care.35 For example, AI platforms in the ICU are projected to integrate machines such as ventilators and intravenous pumps to work in collaboration providing real-time fluid titration and ventilatory support individualized to the patient's current status.36 The continuous patient feedback provided by AI enables the nurse to exhaustively understand the patient. The nurse can use the data supplied by AI in addition to what the nurse draws from the nurse-patient relationship to care for the patient. Nurses function as jugglers, managing variable patient needs, balancing data and patient values, beliefs, emotions, and preferences.


Task reduction

When nurses employ AI at the bedside, they are able to focus less on tasks and more on care. Artificial intelligence prediction algorithms can alleviate administrative tasks from staff and charge nurses. Algorithms programmed with modified early warning score can pull data from various locations in the electronic health record to flag patients at risk of deterioration. The task of reviewing past patient encounters and opening different chart views to gain a more comprehensive patient profile is extremely time consuming for bedside clinicians. In addition, the nature of rotating care teams can also create gaps between staff thereby detracting from a shared complete clinical picture. Algorithms capable of swiftly sifting through previous and current patient encounters to notify the nurse of high-risk patients sooner improve efficiency and patient safety.20 Prediction algorithms can also alleviate resource management logistics that charge nurses are tasked with. These highly accurate AI algorithms forecast patient acuity for upcoming shifts and predict appropriate staffing needs.23 Artificially intelligent systems grant more time and bandwidth to charge nurses to round on staff and patients allowing them to address patient feedback and staff issues.


Unable to flex for the unpredictable

Artificial intelligence is superior to man in accuracy and efficiency in predicting diagnoses and treatments.36 The strengths that AI offers nursing are infallible accuracy and speed that humans sometimes lack. However, the unpredictability of humanity necessitates continuous engagement between the patient and the nurse.35 Locsin argues that constant patient changes require a care plan that is in constant motion.35 When a patient allows a nurse to provide care, they are allowing a sacred trust to transpire. This sacred trust forges a highly emotional human experience that goes further than predicting diagnosis and treatment. The combination of intimate human encounters that occur between nurses and patients and the moment-to-moment patient information that AI provides work in partnership to fully meet patient needs as the patient changes. Unpredictable and unreplaceable, human judgment, critical thinking, and compassion are fundamental to effective care planning and delivery.35


The humanity of patients and the speed and accuracy of AI require coexistence of nurses and technology at the bedside. Reducing task demand while making added information intelligible brings the nurse closer to the patient.35 Technology augments nursing through its ability to accurately predict predictable situations such as diagnoses, staffing, and acuity while nurses remain irreplaceable providers of human care vital to human healing. A harmonious relationship between nurses and AI liberates nurses to do what they are trained to do-care. Locsin proposes a paradigm shift in nursing care to technologically competent nursing care where caring becomes a relationship that is augmented by the benefits of technology.



Modern nursing has become a daily juggling act to ensure that safe and complete care is provided. High nurse-patient ratios have been shown to contribute to nurse burnout.37 If AI is developed and implemented in a way that assists the nurse, there is potential for AI to decrease workload and cognitive overload. As nurses learn more about AI's capabilities, AI will be increasingly valued for its ability to enhance and improve a nurse's human qualities.38 Relief of technical tasks, detection of patient deterioration, and prediction of patient acuity and staffing needs afford nurses more time to engage directly with patients and families. As managers of patient care and future leaders who will incorporate AI into health care, nurses should anticipate the divestiture of tasks to intelligent devices while expanding upon holistic and empathetic treatment.11


As a result of health care technology that has been developed and deployed with nurse-end usability as an afterthought, many nurses view new technology with fear and anxiety, instead of open arms and a welcoming disposition. The opportunity for nurses to reprogram their thoughts on new technology at the bedside appears to be on the horizon, suggesting that the soured nurse-technology relationship could become a sentiment of the past. Historically, nursing has often taken a backseat to advances in health care, especially those related to technology.39 This mentality has long been observed in a profession that is often seen as an extension of medicine but passive in decision making.39 However, nursing is routinely required to be the early adopters of technology in health care but not often as the developers or consultants in the development of emerging technology.


As end users of AI at the bedside, nurses on the front line should be engaged in understanding and influencing emerging technology. Although it may seem unconventional, a bedside clinician's perspective in future AI development is imperative. Only nurses should determine which responsibilities AI can assume in nursing practice, and this requires active participation from the profession as a whole.



There is no doubt that the robots are rising. The presence of AI in health care will continue to multiply. Now is the time for the nursing profession to befriend AI and take the lead to determine how it will augment nursing practice. Quality and productivity are strengthened knowing that artificially intelligent robots and software are extensions of the user-the nurse. The additional data that AI provides to nurses enhance the nurse-patient relationship and improve patient care.


The process of nursing that is difficult to define will also be impossible to replicate in AI. For decades to come, nurses will remain the arbiters of appropriate patient care and intervention delivery that cannot be artificially substituted. Health care without a nurse is just a diagnosis, a prescription, or an unacknowledged order. The threats of a nursing shortage and increasing burnout rates are lessened by AI's assistance in decision making, logistics, and technical tasks. The question is not nurse's relevance today but how nursing can be boosted with the use of AI. Nurses should invite AI into the nursing process and seek opportunities to be active participants in tooling AI specifically for nursing support.




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artificial intelligence; nature of nursing; nursing; robotics; technological competency