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Artificial Intelligence in Industry with Daniel Faggella

A lot of AI in the press is CMOs or marketing people talking about what a company can do in a way that really is aspirational.

They've raised upwards of $40,000,000 in the last six years to apply artificial intelligence to the future of customer service, and we speak about the hard challenges of chatbots and conversational interfaces, as well as how long it's going to be until those are actually robust.

We also discuss why companies maybe need to have a realistic expectation about where they can apply AI, as well as why actually innovating and coming up with new AI capabilities on their own might just be wholly unreasonable given their data, their company culture, and their density of AI talent.

Strategic Insights | TripleTree

UNIQUE INSIGHT Our ability to successfully navigate an ever-evolving market requires deep engagement across every facet of healthcare, combined with the ability to decode trends into insights that inform strategies of tomorrow.

The Hidden Challenges of China’s Booming Medical AI Market

In February 2019, a Chinese study found that an artificial intelligence (AI) system trained on data from 1.3 million patient visits to a Guangzhou medical center could outperform some doctors in diagnosing common childhood diseases.

Hospitals across the country have started adopting AI-assisted medical products and services that include not just image-assisted diagnosis, but also range from surgical robots to smart patient health monitoring and virtual medical assistants.

The application of AI in healthcare is a priority as Chinese leaders look for ways to relieve the immense pressure that a rapidly urbanizing and aging population is putting on the country’s healthcare system.

As a result, China’s AI health market is booming, with estimations putting its size at RMB 20 billion (roughly $3 billion) in 2018, nearly double its size in 2017.

Regulators are taking a distinctly conservative approach, with current medical device catalogs favoring the highest risk classification (Class III) for products or solutions as soon as they incorporate deep learning with explicit diagnosis functions.

However, under China’s Cybersecurity Law and related implementation measures, much of the data generated in a medical context are classified as sensitive, potentially subjecting them to strict data localization requirements or security reviews.

Initial healthcare-specific guidelines are requiring medical institutions to store patient information on secure servers within China and to apply for security evaluations if they wish to transfer it overseas.

With the full safety risks of medical AI still unclear and lives potentially at stake, it remains to be seen to what extent Chinese regulators and patients will be comfortable with letting algorithms make complex disease diagnoses and devise treatment plans based on still fragmented and unstandardized medical records.

Businesses that do not have the foresight and resources to deal with these obstacles may struggle to thrive in a market that will face increasing regulatory scrutiny and growing numbers of ambitious Chinese competitors propped up by state funding.

Even with substantial government funding, many Chinese companies currently struggle to close the technology gap between them and their foreign competitors, and fierce competition from smaller start-ups makes the leadership of China’s designated “national champions” far from certain.

At this crucial stage of development, businesses with strong policy expertise also have the unique chance to help Chinese regulators keep a balanced view of the practical risks and benefits of medical AI by sharing best practices.

China’s various AI technical committees and working groups may provide useful channels for providing technical advice on how to approach critical issues surrounding data, safety, and ethics without hindering AI development or disadvantaging US companies. Advocacy efforts should include ensuring unhindered data flow across borders and definitions of “secure and controllable” medical AI that are not based on the nationality of the product or service.

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