Artificial Intelligence (AI) has emerged as a game-changer in various industries, and healthcare is no exception. The integration of AI technologies in healthcare has the potential to revolutionize patient care, diagnosis, treatment, and overall healthcare management. However, along with its tremendous benefits, the advent of AI in healthcare also brings forth ethical dilemmas and implications for the workforce.
AI has the capacity to process and analyze vast amounts of data at a mind-boggling speed, enabling healthcare professionals to make faster and more accurate diagnoses. Machine learning processes can identify patterns and trends in medical imaging, aiding in early detection of diseases such as cancer (Liu, 2021).
The dilemma becomes apparent when an error happens. Where does the responsibility lie? What if an AI fails to make an accurate diagnosis, considering the different variables a human body may present (socioeconomic and psychological variance), and we start to rely on them heavily? A delicate balance must be established between technological advances and human expertise. We should embrace AIs capability and its potential for eliminating the time it takes for diagnosing diseases. But we should also be mindful of the different variables that the human body can possess that might affect the diagnosis and actual treatment. We still need social and psychological intuition in assessing patients. As a nurse, I am confident that no amount of artificial intelligence can replace human touch. But how do we prepare as a collective population of workers for the inevitable rise in technological advancement? Advancement that can potentially eliminate the need for different sectors of the workforce. As we embrace this technological shift, it is essential to invest in reskilling and upskilling the workforce. But the technology is moving so fast. Are the vast majority of workers ready and prepared to move as fast as this evolving innovation? Granted, technology can also give way to new job opportunities. Will it be enough to sustain all of us?
Liu, X. F. (2021). A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. . The Lancet Digital Health, 3(6), e401-e412.
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