Your fortnightly newsletter of AI news from around the world
21 September 2018
This week we have compiled a healthcare special edition, a selection of important pieces on AI and healthcare - brought to you this week by our researcher Maximilian.
AI Policy in the NHS
This report illustrates the areas where artificial intelligence could help the NHS become more efficient and deliver better outcomes for patients. It also highlights the main barriers to the implementation of this technology and suggests some potential solutions.
This ‘state of the nation’ report looks to the future of health and care and envisions what can be achieved when the vast potential of AI is unlocked. The report is based on a survey conducted by NHS England and the AHSN Network AI Initiative, and it underlines the potential for AI to contribute to improved care.
This review by Eric Topol marks a historic opportunity for the NHS to learn from research, innovation and best practice in digital technologies for healthcare, while considering the implications for the education and training of its workforce. It is essential that all healthcare professionals are ready for the digital future, a future which puts care at the forefront of healthcare.
The code outlines 10 key principles for safe and effective digital innovations, and 5 commitments from the Government to ensure that the health and care system is ready and able to adopt new and innovative technology at scale. These are based on a significant amount of engagement with industry, research and academia, and are designed to create a trusted environment for data-driven technologies.
The Ethics of AI in Healthcare
This report highlights how AI could be used in the near future, and what ethical, social, and political challenges these current and prospective uses present. It also includes the views of patients, their representatives, and members of the public.
The use of AI raises ethical issues, including: the potential for AI to make erroneous decisions; the question of who is responsible when AI is used to support decision-making; difficulties in validating the outputs of AI systems; inherent biases in the data used to train AI systems; ensuring the protection of potentially sensitive data; securing public trust in the development and use of AI technologies; effects on people’s sense of dignity and social isolation in care situations; effects on the roles and skill-requirements of healthcare professionals; and the potential for AI to be used for malicious purposes.
We need to consider the ethical challenges inherent in implementing machine learning in healthcare if its benefits are to be realised. Some of these challenges are straightforward, whereas other have less obvious risks but raise broader ethical concerns.
The nationwide implementation of electronic medical records (EMRs) resulted in many unanticipated consequences, even as these systems enable most patient data to be gathered in one place and make those data readily accessible to clinicians caring for that patient. The redundancy of the notes, the burden of alerts, and the overflowing inbox has led to the “4000 keystroke a day” problem and has contributed to, and perhaps even accelerated, physician reports of symptoms of burnout.
A Global Perspective on AI and Healthcare
Discussing the use of artificial intelligence for cancer care in low- and middle-income countries (LMICs) might seem like a paradox, but new technologies have sometimes reached LMICs faster than cancer drugs on the WHO Essential Medicines List. One example of AI already starting to take hold in cancer care in some LMICs is Watson for Oncology, developed by IBM in partnership with the Memorial Sloan Kettering Cancer Center (MSKCC, New York, NY, USA).
Artificial intelligence may still be in its infancy, but it’s moving fast. Nowhere is this more apparent than in the data-rich health sector. AI has the potential to provide more precise, personalised care, as well as help us to shift our focus from treatment to prevention and tackle some of the world’s biggest global health issues.
The pressing question today is: Can new technologies slow or even reverse the exponentially rising costs to help truly democratise healthcare? The wealthiest patients today benefit not only from being able to afford the top medical services - but also maybe even to fly somewhere to get the opinion of more than one of the top doctors in the world.
Artificial intelligence in healthcare is no longer the preserve of rich countries — it could be on the verge of transforming medical care across the global south. Using AI in a networked hospital system in the US is different from providing care in the community in a resource-poor setting.
Medical Education and Changing Professions
Noteworthy changes coming to the practice of medicine require significant medical education reforms. While proposals for such reforms about, they are insufficient because they do not adequately address the most fundamental change - the practice of medicine is rapidly transitioning from the information age to the age of artificial intelligence.
Faced by machines that outperform us in many areas, some clinicians fear that AI will render them redundant. However, this is to underestimate the role and value of the doctor to the patient and society. Yes, AI has the potential to precipitate one of the greatest changes in the role of the doctor to date, but this is not something to be feared.
Media stories abound describing how technology is going to change healthcare. We’ve heard about robots that can undertake complex surgery and care for older people, and chatbots that claim to outperform GP trainees. We might wonder whether a robot might replace GPs?
A Critical View on AI in Healthcare
Like any technology at the peak of its hype curve, artificial intelligence faces criticism from its sceptics alongside enthusiasm from die-hard evangelists. Despite its potential to unlock new insights and streamline the way providers and patients interact with healthcare data. AI may bring considerable threats of privacy problems, ethics concerns, and medical concerns, and medical errors.
Artificial intelligence could be a great thing in medicine. It could make healthcare safer and faster. It could make medicine more satisfying to practise and less unpleasant to receive. But we must test a hypothesis before we roll it out to the public.