How Explainable AI (XAI) can turn sickcare into healthcare
In recent years, the rise of transparent and explainable AI (XAI) has created more ethical and equitable uses of artificial intelligence in a range of industries.
Healthcare, however, hasn’t yet seen such benefits. It’s a sector that’s reliant on human specialists diagnosing our ailments rapidly and accurately, provided they manifest themselves in said specialist’s organ of expertise. This dogma of medicine, which trains medical professionals in specific organs/diseases, has been one of society’s great successes, of course, but it has mostly been narrow in focus and reactive by nature, meaning we only ever get human-led healthcare when we are sick. This is precisely why it’s ripe for sustainable digital transformation and an injection of innovation.
While technology has delivered historic breakthroughs in healthcare and has huge potential to do more, the ethical shortcomings of dominant solutions like black-box AI have held it back, and such solutions pose serious concerns for the future. Now, it’s time for a responsible, holistic approach to improving everyone’s well-being by using the data-driven, proactive power of XAI and personalisation to finally transform sickcare into healthcare.
Healthcare, however, hasn’t yet seen such benefits. It’s a sector that’s reliant on human specialists diagnosing our ailments rapidly and accurately, provided they manifest themselves in said specialist’s organ of expertise. This dogma of medicine, which trains medical professionals in specific organs/diseases, has been one of society’s great successes, of course, but it has mostly been narrow in focus and reactive by nature, meaning we only ever get human-led healthcare when we are sick. This is precisely why it’s ripe for sustainable digital transformation and an injection of innovation.
While technology has delivered historic breakthroughs in healthcare and has huge potential to do more, the ethical shortcomings of dominant solutions like black-box AI have held it back, and such solutions pose serious concerns for the future. Now, it’s time for a responsible, holistic approach to improving everyone’s well-being by using the data-driven, proactive power of XAI and personalisation to finally transform sickcare into healthcare.
Leveraging tech advancement for the good of human health
As a society, we’re at a point in time at which a holistic, data-driven approach to human health is possible. Never before have we had the technology to send ECG results directly from our wristwatches to our doctors. Never before have we had the technology to sequence a human genome in one hour for only $100.
We have the AI and Machine Learning (ML) capabilities to transform the ways in which we ethically monitor and manage our health and well-being. We no longer need to rely on algorithmic black-box models that are impenetrable by humans and susceptible to critical errors. We can take a responsible approach with XAI, which allows physicians to trace the steps taken toward a prediction and, crucially, correct errors.
This means that, unlike Amazon’s AI recruiting tool in 2018, which discriminated against women, and Apple’s credit card in 2019, which seemed to offer lower limits to women than men, users can have more trustworthy and justifiable outcomes at their fingertips. They can be confident that the AI’s recommendations are accurate, ethical and explainable because they can be part of its enhancement, but what does that look like in reality?
We have the AI and Machine Learning (ML) capabilities to transform the ways in which we ethically monitor and manage our health and well-being. We no longer need to rely on algorithmic black-box models that are impenetrable by humans and susceptible to critical errors. We can take a responsible approach with XAI, which allows physicians to trace the steps taken toward a prediction and, crucially, correct errors.
This means that, unlike Amazon’s AI recruiting tool in 2018, which discriminated against women, and Apple’s credit card in 2019, which seemed to offer lower limits to women than men, users can have more trustworthy and justifiable outcomes at their fingertips. They can be confident that the AI’s recommendations are accurate, ethical and explainable because they can be part of its enhancement, but what does that look like in reality?
What can Explainable AI (XAI) bring to the healthcare sector?
The idea of introducing AI into healthcare might send the wristwatch heart monitors of many into meltdown, but we believe a completely explainable and ethical approach will prove to be the pacifier.
It will mean heaps of past patient and clinical data can be used not only to enable the AI to inform care plans but also to empower physicians and healthcare professionals to learn from the AI. It will facilitate an efficient, data-led process that reassesses and recalibrates the whole algorithm every time a new treatment becomes available, with traceable, personalised plans for all patients. It will pool data from thousands of patients with almost identical conditions and use them to keep improving its recommendations to physicians.
Octain, our AI-as-a-Service (AIaaS) platform at Kin + Carta, already has in-built capabilities to achieve this for the healthcare industry. It can be used to build and iterate predictive models that provide quicker time-to-value and explainable outcomes for healthcare providers and patients alike, whether their appointments are face-to-face or screen-to-screen.
It will mean heaps of past patient and clinical data can be used not only to enable the AI to inform care plans but also to empower physicians and healthcare professionals to learn from the AI. It will facilitate an efficient, data-led process that reassesses and recalibrates the whole algorithm every time a new treatment becomes available, with traceable, personalised plans for all patients. It will pool data from thousands of patients with almost identical conditions and use them to keep improving its recommendations to physicians.
Octain, our AI-as-a-Service (AIaaS) platform at Kin + Carta, already has in-built capabilities to achieve this for the healthcare industry. It can be used to build and iterate predictive models that provide quicker time-to-value and explainable outcomes for healthcare providers and patients alike, whether their appointments are face-to-face or screen-to-screen.
It can support the current operating model of addressing acute conditions like unexpected fractures and infections at A&E, but, more importantly, it allows healthcare systems to start health monitoring and preventing disease via AI. Healthcare providers can use this new combined model of human and machine learning to pre-empt problems and act swiftly with personalised care plans, rather than waiting for a patient’s health to deteriorate before taking action.
It doesn’t replace the input and experience of healthcare workers, but it depends on them to constantly improve. Moreover, it analyses huge sets of accumulated data that no human could ever manage, no matter how many years they’ve spent in medical training.
Across the Healthcare, Life Sciences and Biotech industries, we stand to benefit from utilising XAI. With it, we can:
- Learn from the data rather than bestowing power to the algorithm;
- Treat patients in an ethical and unbiased way by leveraging a massive amount of academic and medical knowledge;
- Build that knowledge through AI development without losing the human touch;
- Detect diseases earlier and intervene more effectively for faster returns to health; and
- Optimise budgets, timings, inventories and facilities while providing superior health outcomes.
The next paradigm of human health is within reach
Technology is advancing at an exponential rate, and many organisations already leverage that to their advantage when it comes to sustainable digital transformation. As we collectively seek better ways to work in the wake of a tumultuous few years, there’s never been a better time for healthcare providers and companies in the life science/biotech space to do the same.
The crux of the matter is in our understanding of what the machines are doing as part of the healthcare system. While black-box AI is dangerous and can lead to ethical missteps that literally cost lives, XAI is transparent and can facilitate iterative models that quickly and accurately predict all manner of effective outcomes. The value of this to healthcare—in disease prevention, data accessibility, inventory optimisation and more—cannot be underestimated.
To explore the benefits of XAI to patients, physicians and the healthcare industry as a whole, get in touch with our experts today. We’d love to help you build a world that works better for everyone.
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