Today, we’re diving into a critical conversation about the intersection of technology and healthcare with Faisal Zain, a renowned expert in medical technology. With years of experience in the manufacturing of cutting-edge medical devices for diagnostics and treatment, Faisal has been at the forefront of innovation in the field. In this interview, we explore the rapid rise of artificial intelligence in medicine, its impact on the doctor-patient relationship, the ethical dilemmas it poses, and the broader implications for care in a system often driven by efficiency and profit. Join us as we unpack these complex themes and consider what it means to preserve the human element in healthcare.
How did your journey in medical technology lead you to focus on the implications of AI in healthcare?
I’ve spent much of my career developing medical devices that aim to improve patient outcomes, from diagnostic tools to treatment technologies. But as AI started becoming a dominant force in healthcare, I couldn’t ignore how it was reshaping the very nature of care. I was struck by how quickly these tools were being adopted and the promises they carried—solving burnout, cutting costs, enhancing diagnoses. Yet, I also saw a disconnect. The technology I helped create was meant to support human connection, not replace it. That tension inspired me to dig deeper into how AI is influencing the way doctors and patients interact, and whether we’re losing something essential in the process.
What have you observed about the way AI is changing the dynamic between doctors and patients during clinical encounters?
I’ve seen firsthand how AI tools, like real-time transcription and diagnostic summaries, are altering the flow of appointments. Doctors often turn to screens to review AI-generated notes while a patient is still speaking, which can create a sense of detachment. It’s becoming more common in clinics, especially in larger health systems where efficiency is prioritized. This shift can erode trust—patients feel like they’re not being fully heard, like their story is secondary to the data on the screen. It’s not just about one interaction; it’s about a broader trend where the personal, emotional context of a patient’s experience risks being sidelined.
Why do you think AI is being integrated into healthcare at such an unprecedented pace?
The speed of AI adoption in healthcare is staggering, largely because it’s seen as a solution to systemic issues like physician burnout and rising costs. Hospitals and clinics are under immense pressure to see more patients in less time, and AI promises to streamline tasks like documentation and diagnostics. There’s also a cultural factor—technology is often viewed as inherently progressive, so there’s a rush to embrace it, fueled by hype around efficiency and innovation. But this rapid rollout often overlooks whether these tools are truly addressing the root problems or just providing a quick fix that benefits administrators and corporations more than patients or providers.
You’ve mentioned concerns about AI prioritizing efficiency and profit over genuine care. Can you elaborate on what that looks like in practice?
Absolutely. When AI is deployed in a healthcare system driven by profit, it often becomes a tool for maximizing revenue rather than enhancing care. For instance, AI can suggest billing codes or treatment plans that align with what insurance will reimburse most lucratively, rather than what a patient might actually need. I’ve seen cases where hospitals use predictive analytics to identify “high-cost” patients and limit their care to cut losses. This isn’t about helping people; it’s about the bottom line. It’s a stark reminder that technology isn’t neutral—it’s shaped by the incentives of those who control it.
While AI excels at tasks like diagnostics and data analysis, what are some of the hidden costs of relying on these capabilities?
AI’s strengths, like analyzing images or predicting health risks, are impressive, but over-reliance comes with significant downsides. One major issue is that it can strip away the nuanced, human judgment that’s critical in medicine. If a doctor leans too heavily on AI suggestions, they might miss subtleties in a patient’s condition that aren’t captured in data—like emotional cues or unique life circumstances. Over time, this can also lead to deskilling, where clinicians lose confidence in their own diagnostic abilities because they’re so accustomed to deferring to algorithms. It’s a slow erosion of the art of medicine, which is just as important as the science.
Why is it so crucial for healthcare to capture the emotional and personal dimensions of a patient’s story, which AI often misses?
The emotional and personal aspects of a patient’s experience are at the heart of effective care. When someone is sick or scared, they’re not just presenting symptoms—they’re sharing fears, histories, and vulnerabilities. AI might summarize a conversation perfectly, but it can’t pick up on the tremble in a voice or the hesitation that hints at deeper concerns. Those unspoken elements often guide a doctor to ask the right questions or offer reassurance in a way that builds trust. Without that, care becomes transactional, and patients can feel reduced to a set of data points rather than seen as whole people.
How do you see the biases inherent in AI systems affecting patient care, especially in marginalized communities?
AI isn’t the unbiased tool many assume it to be. It’s built on existing data, which often reflects decades of systemic inequities in healthcare. For example, algorithms might underestimate health risks in certain racial or ethnic groups because the data they’re trained on underrepresents those populations or incorporates outdated, biased metrics. I’ve seen how this plays out with tools like pulse oximeters, which can misread oxygen levels in darker skin tones, leading to delayed care. These biases aren’t just technical glitches; they perpetuate real harm, especially for marginalized communities who already face barriers to access and trust in the system.
What is your forecast for the role of AI in healthcare over the next decade, and how can we ensure it supports rather than undermines genuine care?
I believe AI will become even more embedded in healthcare over the next ten years, potentially as ubiquitous as basic medical tools are today. It could revolutionize areas like personalized medicine and resource allocation if guided by the right principles. But without intervention, there’s a real risk it will deepen existing inequalities and further alienate patients and providers in a profit-driven system. To ensure AI supports genuine care, we need a fundamental shift—prioritizing public investment in health systems, enforcing strict ethical guidelines on AI development, and involving diverse voices in shaping how these tools are used. It’s not just about better technology; it’s about rebuilding a culture of care that values human connection above all.
