Chess can teach us how to Employ AI in Healthcare - Coffee with CIS - Latest News & Articles

Chess can teach us how to Employ AI in Healthcare

It has been over 20 years since Garry Kasparov lost his famous chess game against IBM's Deep Blue, that instills considerably anxious comment about how humankind was shortly to be siphoned from the exceptional processing power of supercomputers. Two years later and our cultural understanding of AI can feel as though it's still stuck in the nineties.

Videos of agile robots in Boston Dynamics steal headlines concerning the AI-apocalypse, although AI's program in different sectors could be all but ignored by the mainstream.

But amid all of the worry about AI taking tasks, there's little informed discussion and nowhere is this more true than health care. So far as the public perception of AI and health, we have fought to move past the concept of robot physicians.

The truth of AI's likely influence in wellbeing is more nuanced and, I'd argue, more exciting. The health care sector is already an integral battleground in the coming AI revolution, with the AI health market expected to reach $6.6 billion by 2021. Jeff Bezos, Warren Buffett and Jamie Dimon have entered the marketplace with much media attention, but may AI send the cost savings that they search while maintaining equivalent or better patient outcomes?

AI in healthcare: Strengths and limits

It's worth mentioning that AI is a collection of unique technologies, which collectively represent a real opportunity to improve efficiency in clinical and administrative healthcare practices. Take Moorfields Eye Hospital in London, the clinic also has awakened with Google DeepMind to significantly boost the detail where they are in a position to examine retinal tests, opening up the potential for earlier diagnosis and cures of painful problems. Meanwhile companies like BenevolentAI are using AI technology very differently, to quickly accelerate the process of drug discovery.

At the other end of the scale, AI-driven chatbot technology is used by Babylon Health to ease the burden on the UK's National Health Service by providing basic diagnoses and appointment scheduling via smartphone apps.

However, Babylon is a case on the basis of AI's weaknesses in addition to its strengths: the program got into trouble lately after discovering that some users are 'overplaying' their symptoms so as to acquire appointments faster. This cuts to a important weakness of AI in healthcare whether it's terrific for research and analysis, healthcare still requires a human contact. How do we reconcile these two conflicting directions?

Lessons from chess

The secret is in finding the right balance, as well as unlikely as it seems, there are lessons from boxing. After Garry Kasparov's infamous defeat against IBM's Deep Blue, he moved on to consider the possibilities provided by playing chess in partnership using computers instead of against them.

As opposed to admitting defeat, he invented a new type of the sport, known as Advanced Chess, by which a person and AI work together. The brute force analysis of the computer system with the strategic thinking of the individual player has taken the sport to heights of skill never seen before, and it's now an active game across the globe.

We are in need of a similar approach in healthcare. It is too simplistic to determine AI technology and human medical professionals as opposed to one another in a battle over tasks. What matters most is individual outcomes and a combination of powerful AI-led analysis with a human context has the potential to deliver gigantic improvements.

While machine learning scanning technologies is able to detect microscopic lesions or tumors on scans better than your eye, so on its own is not enough. Healthcare is a multidisciplinary practice, requiring social, behavioral, and contextual data from the individual for the doctor to make an informed choice about possible therapy.

The one-to-many connection

What does the future look like? I believe it starts with rethinking the way we see the doctor-patient relationship. This relationship, at the base of contemporary medical practice, has traditionally been thought of as one-to-one, which needs to change. Our populations are aging around the planet, placing pressure on healthcare budgets to deliver an excellent standard of care. The one-to-one doctor-patient connection is not sustainable.

Instead we must appear to AI, machine learning, and modern communications technologies to disperse physicians' time more efficiently. Clinical teams may be bolstered with AI technologies to automate more repetitive or non-critical tasks, such as supervising exercises, or assessing test results. As opposed to leading to job reductions, this could free up more time for doctors and therapists to focus on providing the exceptional value they must offer you.

Our health future is smart, and it does not involve robot doctors. Instead, we will see more patients assigned to one doctor or physician, and technologies can allow that one-to-many relationship to happen without significantly impacts on quality of maintenance.

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