Computer Science Question

Introduction

Create a PowerPoint presentation that shares your research paper findings with the class

(i have attached research paper below)

This is NOT a posting of your entire paper.

Directions

A good PowerPoint is not about a word for word rewriting of your paper. Share the highlights of your research with videos, pictures, graphs, interviews, and/or any other multimedia content. Please see the complete list of requirements in the rubric below.

12 or more slides. The Introductory slide and the Reference slide do not “count” in the required 12slides.

• Slide 1: Introductory slide with your name and the title of your presentation.Slides 2-13 or more: The following slides present your information. Slide 14 or last slide: ReferencesAt least 4 pictures and/or multimedia content

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WILL HEALTHCARE WORKERS SOON BE REPLACED BY ARTIFICIAL
INTELLIGENCE?
Introduction
Artificial intelligence (AI) has advanced significantly in several fields, notably efficiency
improvement and repetitive task automation. AI is becoming an important tool in healthcare,
especially for keeping patient information and guaranteeing data accuracy to reduce errors in
healthcare procedures. But there’s a big concern about whether AI may eventually take the role of
healthcare professionals. This essay examines the various facets of AI in healthcare. It makes the
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case that, despite technology’s potential to revolutionize the industry, healthcare professionals will
always be essential because of the complex and multidimensional nature of the human-centered
healthcare industry.
Artificial intelligence is undoubtedly changing the healthcare industry, optimizing procedures, and
assisting in more precise decision-making. However, the fundamental components of healthcare—
compassion, empathy, and human connection—go beyond the mechanical functions that AI can
execute. This essay argues that healthcare personnel are irreplaceable due to their innate attributes,
highlighting the limitations of artificial intelligence in emulating the depth of human contact and
emotional support necessary in the healthcare sector.
Compassion in Healthcare Provision
The essential need for compassion in the healthcare industry is one of the key obstacles to AI
replacing human healthcare personnel (Sezgin, 2023). Unlike AI algorithms, healthcare workers—
most notably physicians and nurses—introduce an essential human element into patient care. The
emotional complexities of providing consolation and empathy, especially in times of vulnerability,
are a vital and unique component of the healthcare industry that AI cannot replicate. This
component includes establishing a human connection with patients and recognizing their
emotional needs outside of the clinical setting.
The complex and collaborative atmosphere that healthcare workers foster is evidence of the very
human element that permeates their work. It encompasses a comprehensive approach that
acknowledges patients’ emotional wellbeing, clinical diagnosis, and therapy. People find comfort
in the knowledge of medical interventions and the compassion and understanding of caregivers
during distress. A vital component of the healing process, the dynamic interplay of emotions,
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subtle communication, and true human connection are profoundly ingrained in the healthcare
profession.
Artificial intelligence (AI) has limitations when navigating the vast geography of human emotions
and the nuances of individual experiences, even while it may excel in some data processing and
analysis areas. The human element in healthcare, characterized by empathy and compassion,
continues to be a crucial differentiator between medical personnel and artificial intelligence. As
technology advances, recognizing and maintaining the unique components of human-centric care
becomes essential for patients’ overall well-being.
Limitations of AI Capabilities
Artificial Intelligence (AI) is limited to certain human tasks due to its mechanical nature and
intrinsic limits, even with its great potential (Xiang et al., 2020). Critically sick patients require
complex and individualized care beyond what AI can provide. AI cannot do activities requiring
constant medication modifications, careful monitoring of vital signs, or quick responses to
emergencies like surgery. AI is more robotic than critical thinking; it lacks the nuanced decisionmaking and adaptability required for such settings. Artificial intelligence’s preset algorithms
cannot match the reactivity and intuitive decision-making required by the dynamic nature of
healthcare, particularly in critical care settings. AI’s mechanical characteristics cannot meet the
intricate and constantly changing needs of providing all-encompassing care for critically ill
patients. Understanding AI’s limitations is essential to preserving the integrity of healthcare
procedures and ensuring that human-centric traits remain crucial in circumstances requiring
extreme sensitivity and skill.
Complexity of Healthcare Processes
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The complexity of healthcare procedures, from diagnosis to treatment, requires a degree of
cooperation and judgment that AI might not be able to replicate. Human interaction becomes
crucial, especially in cases where patients require a second or third opinion about their diagnosis,
requiring a level of cognitive flexibility that is now beyond the capability of AI algorithms. If AI
produces consistent results, there is a significant risk of transfer errors, which emphasizes the
necessity of human involvement in these diagnostic phases. Medical assessments are often
complex and require contextual knowledge and considerations beyond the computational
capabilities of artificial intelligence. Thus, human skill is still needed to negotiate the nuances and
ambiguities involved in medical decision-making because of healthcare’s collaborative and
interpretive aspects, particularly in the diagnostic phases.
Hands-On Patient Care
Giving critical care to patients involves more than just medical treatments; it also involves practical
activities like feeding, clothing, and tending to their needs (Okolo et al., 2021, May). Responses
must be prompt and context-sensitive due to the unpredictability of patients receiving critical care,
including incidents such as convulsions or abrupt detachment of medical devices. Human
caretakers are crucial in providing the necessary reaction because of their exceptional capacity to
adjust to unforeseen circumstances. Critical care is dynamic and unpredictable, necessitating
medical knowledge and a practical, intuitive approach that human caregivers only possess. Human
caregivers are crucial in providing comprehensive care for critically ill patients, going above and
beyond clinical procedures to ensure the patient’s comfort in everyday activities or responding to
unexpected medical crises.
Collaboration and Cognitive Flexibility in Healthcare
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Because of the intricacy of healthcare procedures, from diagnosis to treatment, decision-making
and collaboration are required at a level that exceeds what AI is currently capable of. When patients
seek a second or third opinion about their diagnosis, human intervention becomes crucial since it
requires cognitive flexibility that AI algorithms do not yet possess. When AI produces the same
outcomes in complex medical decision-making settings, the risk of transfer errors increases,
highlighting the critical need for human intervention. In the complex world of healthcare, where
every patient’s situation is different, it is critical to be flexible and understand small details. Even
though AI systems are adept at handling enormous volumes of data, they fall short in simulating
human thought’s complex and dynamic aspects. Patients frequently need more than one diagnosis;
instead, they frequently need a team effort combining a variety of viewpoints, which is a feature
that is fundamental to human cognitive flexibility.
Furthermore, when AI algorithms provide identical answers, there is a significant chance of
transfer errors, which could have a cascading influence on subsequent medical judgments. When
making decisions, human healthcare providers have a more nuanced grasp of the situation and
consider patient-specific information and contextual aspects that AI’s more inflexible and
standardized approach may miss. The complexity of healthcare necessitates a degree of cognitive
flexibility and sophisticated judgment that AI systems are currently incapable of providing. The
possibility of transfer errors is a sobering reminder of how essential human interaction is when
negotiating the complexities of medical diagnosis and treatment regimens. Accurate,
individualized, and context-aware medical treatment cannot be provided unless human
professionals’ distinct cognitive capacities are acknowledged and preserved, even as healthcare
advances.
Responsiveness to Contingent Occurrences
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AI’s intrinsic limits are highlighted by its inability to adequately respond to unanticipated
occurrences, such as the requirement for patient separation during contagious diseases
(Doraiswamy et al., 2020). Healthcare professionals always have to make vital decisions in the
moment while handling unforeseen circumstances. Conversely, AI’s preprogrammed and coded
solutions fall short when handling the various and unpredictably occurring problems that arise in
healthcare environments. Because the healthcare industry is dynamic, it requires adaptable and
context-sensitive solutions—a feature that artificial intelligence is presently unable to provide. The
delicate and adaptable decision-making needed in such situations—whether for quick
modifications to isolation measures or attending to an emergency patient’s needs—is evidence of
the vital role that human healthcare professionals play in these situations. When considering the
complicated and unpredictable nature of healthcare, the limitations of AI become very clear,
highlighting the ongoing need for human skill in managing the intricacies of medical treatment.
Accountability and Emergency Response
The differences in behavior between algorithms and human caregivers become especially apparent
when emergency situations call for critical thinking (Robert, 2019). The necessity for human
oversight is highlighted by the accountability gap that AI systems have, which makes them prone
to error propagation with possibly lethal effects for patients. This includes the need for specific
equipment to meet a range of healthcare requirements, especially while managing crises brought
on by natural catastrophes. The unique ability of humans to make quick, context-sensitive
decisions is essential for preventing and lessening the effects of unanticipated difficulties. AI
algorithms’ preset and inflexible nature contrasts sharply with the interactive and adaptive nature
of human responses to situations. Healthcare involves a broad range of conditions, each requiring
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special considerations. In the face of intricate, dynamic, and high-stakes situations, human
caregivers are indispensable in ensuring the safety and well-being of the individuals they care for.
Behavioral Disparities and the Need for Human Oversight
The behavioral distinctions between algorithms and human caregivers are most noticeable in
emergency settings that require critical thinking. The spread of mistakes in an AI system that could
be lethal to patients is unaccountable. Specialized equipment for a range of medical
requirements—including emergencies brought on by natural disasters—highlights the importance
of human supervision and decision-making in the medical field.
Closing Paragraph
In conclusion, the core of providing compassionate and empathic treatment remains firmly
entrenched in human capacities, even as artificial intelligence advances and redefines processes in
the healthcare industry. The complexities of patient care, the demand for complex decisionmaking, and the unpredictability of healthcare situations make healthcare workers indispensable
and require their continual presence. To ensure comprehensive and patient-centered healthcare in
the future, it will be essential to balance the advantages of artificial intelligence (AI) and the
indispensable traits of human caregivers as technology advances.
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References
Doraiswamy, P. M., Blease, C., & Bodner, K. (2020). Artificial intelligence and the future of
psychiatry: Insights from a global physician survey. Artificial intelligence in
medicine, 102, 101753.
Okolo, C. T., Kamath, S., Dell, N., & Vashistha, A. (2021, May). “It cannot do all of my work”:
community health worker perceptions of AI-enabled mobile health applications in rural
India. In Proceedings of the 2021 CHI Conference on Human Factors in Computing
Systems (pp. 1-20).
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Robert, N. (2019). How artificial intelligence is changing nursing. Nursing management, 50(9),
30.
Sezgin, E. (2023). Artificial intelligence in healthcare: Complementing, not replacing, doctors
and healthcare providers. Digital Health, 9, 20552076231186520.
Xiang, Y., Zhao, L., Liu, Z., Wu, X., Chen, J., Long, E., … & Lin, H. (2020). Implementation of
artificial intelligence in medicine: Status analysis and development suggestions. Artificial
Intelligence in Medicine, 102, 101780.