{"id":4778,"date":"2026-06-03T01:47:26","date_gmt":"2026-06-03T00:47:26","guid":{"rendered":"https:\/\/blogs.bmj.com\/medical-ethics\/?p=4778"},"modified":"2026-06-03T01:47:26","modified_gmt":"2026-06-03T00:47:26","slug":"the-ontological-shift-why-ai-in-clinical-practice-is-a-question-of-being","status":"publish","type":"post","link":"https:\/\/blogs.bmj.com\/medical-ethics\/2026\/06\/03\/the-ontological-shift-why-ai-in-clinical-practice-is-a-question-of-being\/","title":{"rendered":"The ontological shift: Why AI in clinical practice is a question of being"},"content":{"rendered":"<p>Farid bin Masood<\/p>\n<p>Much has been written for and against AI\u2019s application in healthcare including <a href=\"https:\/\/www.nytimes.com\/2026\/01\/02\/world\/asia\/china-ai-cancer-pancreatic.html\">screening<\/a>, <a href=\"https:\/\/www.news-medical.net\/news\/20260423\/APOLLO-AI-learns-from-25-billion-medical-events-to-predict-future-disease.aspx\">prediction<\/a>, and <a href=\"https:\/\/www.nature.com\/articles\/s43856-025-01283-x\">simulation<\/a>. But there\u2019s a component of clinical work that matters just as much, maybe more: the clinician\u2019s work as a human, including communicating with the patient and making decisions when faced with uncertainty. Much is being <a href=\"https:\/\/www.nytimes.com\/2025\/11\/16\/well\/ai-chatbot-doctors-health-care-advice.html\">written<\/a> on this aspect, and how <a href=\"https:\/\/www.nytimes.com\/2024\/10\/05\/opinion\/ai-chatgpt-medicine-doctor.html\">AI could help<\/a>.<\/p>\n<p>Before we get excited or defensive, a more fundamental question should be raised. Not whether AI works, but what kind of world it brings into being. That\u2019s where Heidegger becomes useful. He <a href=\"https:\/\/www2.hawaii.edu\/~freeman\/courses\/phil394\/The%20Question%20Concerning%20Technology.pdf\">asks<\/a> not what technology achieves, but what kind of reality it sets into motion. For him, technology is not merely a means to an end; it entails a way in which the world comes to appear. In modern technology, that appearing takes a specific form: what he calls \u201cenframing,\u201d a mode of revealing that challenges things to present themselves as \u201cstanding-reserve,\u201d resources always available, ready to be optimized. I apply his framework from \u201c<a href=\"https:\/\/www2.hawaii.edu\/~freeman\/courses\/phil394\/The%20Question%20Concerning%20Technology.pdf\">The Question Concerning Technology<\/a>,\u201d to the inclusion of AI in these two human aspects of clinical practice.<\/p>\n<p>The first issue is the growing claim that AI can communicate with patients <a href=\"https:\/\/www.nature.com\/articles\/s41746-025-01671-6\">as well as<\/a>, or even <a href=\"https:\/\/jamanetwork.com\/journals\/jamainternalmedicine\/fullarticle\/2804309\">better<\/a> than, a doctor. If empathetic communication is the sum of scripts, conventions, and learned forms of reassurance, then whether it comes from a human being or an LLM, the message is what counts. The relief of the patient is what counts. Of course, for clinicians managing high patient loads, relying on LLMs is not a way of avoiding the patient, but often an attempt that some communication reaches them at all.<\/p>\n<p>But Heidegger would ask: what has already happened to care itself such that this argument becomes persuasive at all? For empathy to become transferable in this way, it must first be reduced to something \u201corderable,\u201d produced on demand, measured, and optimized. Care ceases to be primarily a relation, a lived encounter between two vulnerable beings facing uncertainty, and begins to appear instead as a deliverable. Reassurance becomes a resource to be allocated efficiently. Tone becomes a function to be calibrated. This is what Heidegger describes when he says technology reveals reality by \u201csetting upon\u201d it and \u201cchallenging it forth.\u201d Even if the output is successful, something essential is concealed in that success. Heidegger warns that \u201cin the midst of what is correct, the true can withdraw.\u201d Here, the truth of care fades.<\/p>\n<p>This fading steps into the second major issue: clinical decision-making. AI-based Decision Support Systems <a href=\"https:\/\/doi.org\/10.1016\/j.aimed.2025.100529\">are hailed<\/a> as groundbreaking tools for accurate decision-making. The problem is not merely whether AI calculates accurate decisions, but what the act of decision-making itself becomes when healthcare is organized around what can be formalized and fed into calculable systems. Heidegger argues that modern technology demands that nature become \u201corderable as a system of information.\u201d Hence, the process of decision-making comes under intense pressure to report itself in machine-legible form.<\/p>\n<p>This shift matters significantly because medical decision-making is not exhausted by a doctor generating merely an optimized output. The process relies heavily on <a href=\"https:\/\/doi.org\/10.1016\/j.ijdrr.2020.101681\">tacit knowledge<\/a>, the uncodifiable, intuitive grasp of a situation born from lived experience. It demands <a href=\"https:\/\/doi.org\/10.1186\/s12910-021-00581-y\">phronesis<\/a>: practical wisdom related to the timing, the hesitancy to intervene, the sensitivity to what a patient has left unsaid. There is a life in the room that exists beyond the numbers and risk-stratification charts. We risk reducing this tacit, moral dimension to a formalized, calculable output.<\/p>\n<p>Heidegger\u2019s idea of <em>poiesis<\/em> offers a helpful lens. <em>Poiesis<\/em> is the natural act of bringing\u2011forth, like a blossom unfolding, where revealing happens \u201cin itself\u201d (<em>en heaut\u014di<\/em>), arising from within the being. Medical decision\u2011making similarly allows the situation to disclose itself. It does not (and should not) force a diagnosis onto the patient as the patient is a locus of being and happening, not raw material awaiting form. It holds open space for uncertainty, ambiguity, and temporal unfolding. In this sense, clinical judgment is a bringing\u2011forth that respects the patient\u2019s own way of being and the manner in which illness reveals itself.<\/p>\n<p>AI\u2011driven decision\u2011making, by contrast, increasingly redefines good judgment as whatever can be secured, calculated, regulated, and rendered auditable. AI does not merely assist judgment as a neutral tool; it reshapes the horizon within which judgment occurs. What becomes institutionalized as \u201cgood judgment\u201d risks narrowing to efficiency, defensibility, reproducibility, and algorithmic compliance. What recedes are precisely those dimensions that resist full formalization: the tacit, the intuitive, the affective, and the spiritual. This is why Heidegger\u2019s examples move beyond rivers and coal resources and \u201cthe supply of patients for a clinic.\u201d<\/p>\n<p>The result is more tragic. Heidegger claims that enframing gathers even technology\u2019s masters into its logic. Contemporary clinicians face <a href=\"https:\/\/doi.org\/10.1007\/s11606-024-08956-8\">increasing documentation demands<\/a>, time constraints, and administrative overhead. AI systems are introduced to relieve these pressures, yet in this process, doctors are themselves \u201cchallenged forth\u201d as standing\u2011reserves. Heidegger warns: \u201cWe are delivered over to technology in the worst possible way when we regard it as something neutral.\u201d The doctor who believes to be master of the tool is already shaped by a prior demand to keep making patients, language, time, and even oneself available for further ordering.<\/p>\n<p>The critique of AI in healthcare should not stop at <a href=\"https:\/\/hms.harvard.edu\/news\/researchers-discover-bias-ai-models-analyze-pathology-samples\">bias<\/a>, <a href=\"https:\/\/jnm.snmjournals.org\/content\/early\/2025\/11\/06\/jnumed.125.270653\">hallucinations<\/a>, <a href=\"https:\/\/www.hipaajournal.com\/lawsuit-ai-platform-illegally-recorded-patient-clinician-conversations\/\">privacy violations<\/a>, or <a href=\"https:\/\/news.harvard.edu\/gazette\/story\/2026\/01\/ai-is-speeding-into-healthcare-who-should-regulate-it\/\">insufficient regulation<\/a>, as important as those concerns are. It must ask what happens to the being of patient and physician with AI permeating clinical practice. When both the patients and doctors are lost to enframing in the clinic, what remains is an efficient and ordered system with the truth of care withdrawing.<\/p>\n<p>And that, finally, is what Heidegger is warning about. Enframing is not the only way of revealing. There are other modes in which things come to presence. The question is whether we can still recognize them, or whether we have become so deeply ordered by the demand to order that we can no longer see beyond it.<\/p>\n<p><strong>Author:<\/strong> Farid bin Masood<\/p>\n<p><strong>Affiliation: <\/strong>Centre of Biomedical Ethics and Culture, SIUT, Karachi, Pakistan<\/p>\n<p><strong>Conflict of interest declaration: <\/strong>None declared<\/p>\n<p><strong>Social Media<\/strong>: <a href=\"https:\/\/www.linkedin.com\/in\/faridbinmasood\/\">LinkedIn<\/a><!--TrendMD v2.4.8--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Farid bin Masood Much has been written for and against AI\u2019s application in healthcare including screening, prediction, and simulation. But there\u2019s a component of clinical work that matters just as much, maybe more: the clinician\u2019s work as a human, including communicating with the patient and making decisions when faced with uncertainty. Much is being written [&#8230;]<\/p>\n<p><a class=\"btn btn-secondary understrap-read-more-link\" href=\"https:\/\/blogs.bmj.com\/medical-ethics\/2026\/06\/03\/the-ontological-shift-why-ai-in-clinical-practice-is-a-question-of-being\/\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":522,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8068,8076],"tags":[],"class_list":["post-4778","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-decision-making"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>The ontological shift: Why AI in clinical practice is a question of being - Journal of Medical Ethics blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.bmj.com\/medical-ethics\/2026\/06\/03\/the-ontological-shift-why-ai-in-clinical-practice-is-a-question-of-being\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The ontological shift: Why AI in clinical practice is a question of being - Journal of Medical Ethics blog\" \/>\n<meta property=\"og:description\" content=\"Farid bin Masood Much has been written for and against AI\u2019s application in healthcare including screening, prediction, and simulation. 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