AI

The next healthcare revolution will have AI at its center

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Image Credits: Kilito Chan (opens in a new window) / Getty Images

Kai-Fu Lee

Contributor

Kai-Fu Lee is a co-author of AI 2041: Ten Visions For Our Future.

The global pandemic has heightened our understanding and sense of importance of our own health and the fragility of healthcare systems around the world. We’ve all come to realize how archaic many of our health processes are, and that, if we really want to, we can move at lightning speed. This is already leading to a massive acceleration in both the investment and application of artificial intelligence in the health and medical ecosystems.

Modern medicine in the 20th century benefited from unprec­edented scientific breakthroughs, resulting in improvements in every as­pect of healthcare. As a result, human life expectancy increased from 31 years in 1900 to 72 years in 2017. Today, I believe we are on the cusp of another healthcare revolution — one driven by artificial intelligence (AI). Advances in AI will usher in the era of modern medicine in truth.

Digitization enables powerful AI

The healthcare sector is seeing massive digitization of everything from patient records and radiology data to wearable computing and multiomics. This will redefine healthcare as a data-driven industry, and when that happens, it will leverage the power of AI — its ability to continuously improve with more data.

When there is enough data, AI can do a much more accurate job of diagnosis and treatment than human doctors by absorbing and checking billions of cases and outcomes. AI can take into account everyone’s data to personalize treatment accordingly, or keep up with a massive number of new drugs, treatments and studies. Doing all of this well is beyond human capabilities.

AI-powered diagnosis

I anticipate diagnostic AI will surpass all but the best doctors in the next 20 years. Studies have shown that AI trained on sizable data can outperform physicians in several areas of medical diagnosis regarding brain tumors, eye disease, breast cancer, skin cancer and lung cancer. Further trials are needed, but as these technologies are deployed and more data is gathered, the AI stands to outclass doctors.

We will eventually see diagnostic AI for general practitioners, one disease at a time, to gradually cover all diagnoses. Over time, AI may become capable of acting as your general practitioner or family doctor.

From an autonomy standpoint, because human lives are at stake, AI will first serve as a tool at doctors’ disposal or will be deployed in situations where a doctor is unavailable. Over the coming decades, we can expect medical diagnosis to evolve from an AI tool that provides analysis of options to an AI assistant that recommends treatments. After this we could see a doctor rubber-stamping AI assistant recommendations, which could eventually lead to autonomous AI medical diagnosis.

As AI takes over diagnostics and most physicians move to a role resembling compassionate caregivers, human-AI symbiosis could be achievable.

Toward prevention: Alerts, monitoring, health exams and longevity

Beyond diagnosis, we can expect other aspects of healthcare to be transformed as well. Smart rooms with sensors for temperature, smart toilets, beds, toothbrushes, pillows and all kinds of invisible gad­gets will regularly sample vital signs and other data and detect possible health crises. Aggregated data from wearable devices will accurately identify serious conditions, whether it is a fever, a stroke, arrhythmia, apnea, asphyxiation or injuries from a fall. Sudden changes in condition may trigger an alert to you, your next of kin or call for emergency assistance.

All this data will be combined with other healthcare information such as medical history, contact-tracing records and infection-control data to predict and warn about future pandemics. Advances in privacy will also allow for this data to be used for AI without sharing personal information.

These advances will also enable health examinations that could include full-body MRIs, blood tests and genetic sequencing. AI can be used to compare this data against billions of other cases and recommend personalized changes in lifestyle, sleep, food, nutrients and medicines to keep every patient healthy.

Precision medicine stands to become increasingly feasible as more information becomes available. AI is suited to deliver this kind of individualized optimization and can be applied to longevity, where each person can be compared to others of different ages and be suggested ways to reduce the gap with younger people.

AI could also use big data and individualized data to deliver “precision longevity” by pre­paring personalized nutrition, supplement, exercise, sleep, medication and therapy plans. Rejuvenation biotechnology will no longer be limited to the ultrarich but made available for all.

AI drug discovery

AI doctors can be quite controversial, but AI drug discovery is much less so. Today, it costs $1 billion to $2 billion and takes many years to get a successful drug or vaccine through the development process. AI can be used to fold proteins and propose targets to attach a treatment mole­cule. AI models can narrow the search for a drug by identifying patterns within the data and proposing lead candidates. Scientists can use these tools to significantly reduce the cost of drug discovery.

In 2021, biotechnology company Insilico Medicine announced the first AI-discovered drug for idiopathic pulmonary fibrosis. Insilico’s AI saved 90% of the cost of two major steps in drug discovery. When such AI tools are made available to scientists, drugs will be invented at much lower costs, making it worthwhile for pharmaceuticals to pursue treatments for rare diseases and research multiple drugs for common diseases.

Besides the above “in-silico” approach to drug discovery, “in-vitro” wet-lab experimentation, which involves testing the proposed drugs on human cells in petri dishes, can also expedite drug discovery. These experiments can now be conducted more efficiently with robotics than lab technicians to generate massive amounts of data. A scientist can program these robots to iterate a series of experiments 24/7 without human intervention. This will accel­erate the speed of drug discoveries greatly.

Surgical and nano-robots

Even complex surgeries, which rely on sophisticated judgment and nimble movement, will be increasingly automated over time. Robot-assisted surgeries have increased from 1.8% of all surgeries in 2012 to 15.1% in 2018, and semi-autonomous surgical tasks, such as colonoscopy, suturing, intestinal anastomosis and teeth implants, are within reach for robots under doctor supervision.

As AI is trained on more data, robotic surgeries could go from a human surgeon operating a robot, to a surgeon supervising a robot and delegating some tasks, and eventually to fully autonomous surgical robots. Extrapolating from this trend, we can expect all surgeries will see some amount of robotic participation in 20 years, with fully autonomous robotic surgeries increasingly accounting for the majority of procedures.

Finally, the advent of medical nanobots will offer numer­ous capabilities that surpass human surgeons. These miniature (1 to 10 nanometer) bots could repair damaged cells, fight cancer, correct genetic deficiencies and replace DNA molecules to eradicate dis­ease.

Issues and concerns with AI healthcare

But rolling out AI, automation and robotics requires dealing with many major issues. Some people will find it morally objectionable for machines to ever make decisions that affect human health and human lives, even if AI-powered healthcare could save millions of lives over time.

Today, when a human doctor or surgeon causes fatalities, they answer to judicial and regulatory processes that decide if they acted properly and, if not, determine the consequences. But what happens if AI causes the fatality? Can AI explain its decision-making in a way that is comprehensible, and legally and morally justifiable?

AI is hard to explain because it is often trained from data, and AI’s answer is a complex math equation, which may need to be simplified dramatically to be comprehensible to people. Some AI decisions will look downright stupid (because AI lacks common sense), just as some human decisions sometimes look stupid to AI.

And if there is a fatality involving AI, who is held ac­countable? Is it the equipment manufacturer? The AI algorithm provider? The engineer who wrote the algorithm? The doctor providing supervision? We need laws and regulations that enshrine accountability and protect people from unsafe software, but we also need to ensure technological improve­ment does not stall due to excessive indemnities.

In conclusion

A 2019 study shows that AI healthcare markets will grow 41.7% annually to $13 billion by 2025, in such areas as hospital workflow, wearables, medical imaging and diagnosis, therapy planning, virtual assistants, and, most significantly, drug discovery. COVID-19 is accelerating this growth rate.

AI healthcare is not just a market — it represents a tidal wave of transformations that will change the entire industry. AI-powered healthcare will enable us to have longer and healthier lives.

This article is an excerpt from AI 2041: Ten Visions For Our Future.

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