The promise of artificial intelligence (AI) to enhance health outcomes captivates some, while others adopt a more cautious stance, fearful of a future where technology surpasses human control. Both perspectives are valid, and the present moment calls for a collective decision on our technological trajectory.
Distinction: AI vs. Health Technology
It is crucial to differentiate between health technology and AI within the healthcare realm, as these concepts are fundamentally distinct from each other.
Understanding Health Technology
Health technology encompasses any device created through human programming to execute specific functions. Examples include Holter monitors that log heart rhythms and pacemakers that respond to cardiac demands.
Despite presenting functionality that resembles intelligence, these systems operate based on human design and guidance. Any operational failures can typically be traced back to errors by programmers or mechanical defects.
Defining AI
AI denotes the ability of machines or software to mimic intelligent human activities, including quick calculations, problem-solving, and real-time processing of new information informed by previously acquired data.
A crucial branch of AI, known as machine learning, empowers systems to recognize patterns and enhance themselves autonomously through experience and data analysis, ultimately evolving without necessitating further human intervention.
Present Applications of AI
Healthcare services are increasingly data-driven, utilizing advanced information technology and analysis. AI applications can significantly streamline record-keeping, enhance patient outcomes, and possibly lower costs.
AI is currently employed to assess data from electronic health records, providing vital clinical support, particularly in the area of medical imaging. Notably, a study by Stanford University revealed that an AI algorithm’s performance in detecting skin cancer matched that of dermatologists.
Algorithms have been applied to preoperative medical data to guide surgical instruments, potentially leading to minimally invasive procedures with shorter recovery times and reduced costs.
Emerging natural language processing technologies can document interactions between healthcare providers and patients during telehealth sessions, cutting down on administrative tasks. Some research indicates these programs can effectively analyze the tone and wording of conversations in emergency calls to ascertain the necessary response.
Challenges Facing AI
Who hasn’t turned to Google for answers about a medical issue, only to find a range of alarming possibilities that are often incorrect? Computers lack the ability to grasp the intricate details of our unique physiology, behavior, environmental factors, or mental states.
Using search engines for health concerns exemplifies AI’s constraints in delivering tailored medical guidance: computational systems overlook the subtleties that define human experience.
During my second pregnancy, at seven months along, I visited my obstetrician due to some discomfort. After attentively listening to my concerns, he simply stated: “I don’t like how you appear. Let’s get you to the hospital for some tests.” A machine cannot interpret a patient’s condition with such intuitive insight.
Human Error in AI
The unique traits that define both patients and healthcare providers can also affect how biases are programmed into AI systems. Unconscious biases may inadvertently influence the data that programmers include or omit.
A recent study evaluating a healthcare algorithm indicated that black patients were less likely to be identified as candidates for advantageous care programs compared to white patients with similar chronic illnesses.
Researchers attributed the discrepancy to labeling categories used in the algorithm’s design, recommending adjustments as a potential fix. However, this raises a crucial point: modifying labels might eliminate one bias while introducing another, thereby complicating algorithmic accuracy.
Ethical Challenges Ahead
Ethics experts stress that before implementing AI in healthcare, it is essential for developers, practitioners, and specialists to evaluate how these technologies might affect medical ethics and humanity overall, weighing negative consequences against potential benefits.
For instance, while AI can accelerate information retrieval, it could disproportionately heighten social inequalities globally or cause local economic disruptions as workers in various roles face job losses or wage reductions.
As healthcare becomes increasingly automated, we must be vigilant that quality of care, patient adherence, and recovery outcomes do not suffer due to the absence of human empathy and the nuanced care provided by healthcare professionals. Specific patient groups, such as those in mental health, obstetrics, geriatrics, and pediatrics, may face additional challenges with robotic care.
Additionally, the reliance on AI necessitates the collection and analysis of vast amounts of sensitive patient information, raising serious concerns over data privacy, protection, and the potential for misuse.
Finding the Balance
As individuals, we must cultivate a distinct perspective on the future we envision. AI could represent a pivotal moment, potentially leading toward a transhumanist agenda that advocates for the use of advanced technologies not only to eliminate aging and disease but also to hasten human evolution.
As some ethicists suggest, transhumanism resembles eugenics and raises intricate questions concerning the nature of humanity—economic considerations (who stands to gain?), sociological implications (will individual autonomy be threatened?), and ethical dilemmas (will there be peer pressure to conform to enhanced capabilities?).
Critical Evaluation is Essential
We must remain vigilant against the politicization of AI and technology in healthcare, as various stakeholders may seek to exploit societal anxieties following recent challenges in healthcare and climate debates to hastily introduce AI solutions.
It’s our responsibility to conduct thorough research and consider the implications of AI and health technology on human experiences rather than allowing developers to dictate the course without scrutiny.
Machine learning algorithms can process 3D imaging at speeds up to 1,000 times faster, supplying nearly instantaneous feedback to surgeons during procedures.
Initial results from deep learning algorithms suggest they may outperform human capabilities in identifying metastasized breast cancer.
VR headsets enable medical professionals to explore human anatomy without jeopardizing patient safety or relying on cadaveric resources.
Additionally, VR serves as a therapeutic method for alleviating chronic pain, managing anxiety, and aiding children with autism in developing coping strategies.
Karel Čapek coined the term “robot” from the Czech word robota, meaning “forced labor.”
Expectations that AI will radically transform healthcare may lead to disappointment since it cannot tackle the fundamental issue: human health behaviors.
This piece was initially published in the January 2024 edition of Thewindowsclubs magazine.
