The artificial intelligence revolution must work for all of us

Mike Hedges – MS for Swansea East

We are now in the fourth industrial revolution, the artificial intelligence revolution. This must work for all of us not just for the rich and powerful.

We are seeing fundamental changes taking place in how the global production and supply network operates, though not only the continual automation of traditional manufacturing and industrial practices, using modern technology, the internet and large-scale machine-to-machine communication but also in the use of machine learning to perform some technical tasks better than humans.

This results in improved communication increased automation, increased self-monitoring, and most importantly the use of smart machines that can analyse and diagnose issues without the need for human intervention.

Machines have for many years improved human efficiency in performing repetitive functions doing it faster and more consistently than people.

Impact

The combination of machine learning and computing power allows machines to conduct increasingly complex tasks.

Artificial intelligence has a wide range of applications across all sectors of the economy. It gained prominence following advancements in deep learning during the 2010s coming to public attention when computers started beating grand masters at chess, solving sudoku faster than humans and finally beating expert Go players.

Its impact intensified in the early 2020s with the rise of generative AI, a period often referred to as the “AI boom” models can engage in verbal and textual discussions and analyse images.

One of the areas that artificial intelligence can be used to improve productivity, efficiency and outcomes is health. Health care has become more expensive due to the cost of patient care and drugs.

Diagnosis

Health care is an area where AI can help increase efficiency. algorithms can analyse medical images, patient data, and other information to assist in diagnosing diseases, often detecting patterns and correlations that might be missed by humans.

For example, AI can help diagnose lung cancer more accurately and predict heart attacks and strokes. We have had publicly reported that the application of AI algorithms in areas such as ophthalmology has ensured increased accuracy in the screening and diagnosis of certain pathologies, such as glaucoma and cataracts.

From published research we know that AI can help develop treatment plans tailored to individual patient needs, considering factors like their specific condition, genetic makeup, and other relevant information.

In a study by Yu et al, AI software used quantitative histopathology characteristics collected from 2,186 whole-slide pathology pictures from the Cancer Genome Atlas to discriminate between primary lung adenocarcinoma and squamous cell carcinoma.

In a multicentre, non-interventional trial, including 120 pulmonologists from sixteen hospitals in five different European countries, Topalovic et al,  showed that AI performed better than pulmonologists in the interpretation of pulmonary function tests. Pulmonologists’ pattern identification of pulmonary function tests met the recommendations in 74.4% of instances, and pulmonologists made proper diagnoses in 44.6% of cases, whereas AI precisely matched the PFT pattern interpretations (100%) and gave a correct diagnosis in 82% of all cases.

We have research telling us that AI-powered devices help surgeons perform minimally invasive procedures with greater precision and accuracy, reducing the risk of errors and complications.

AI is being used during surgery to optimize force, detect positive surgical margins, and even automate specific steps. AI-powered patient monitoring can monitor patient conditions in real-time, providing alerts to healthcare providers if there are changes that require attention.

While it has been reported that currently autonomous robotic surgery appears to be a long way off, cross-disciplinary collaboration will certainly improve AI’s potential to complement surgical treatment.

Already we have had examples of robotics and neuro-navigation technologies assisting in minimally invasive surgery.

Predictions

Personalized patient communication including sending patients schedule reminders, health tips, and suggested next steps, improving patient engagement and adherence to treatment plans.

AI can be used to predict which patients are at risk of becoming frequent users of emergency services, allowing for earlier intervention, and potentially reducing demand on emergency departments.

When people contact financial businesses, the first stage is a chat with AI, only being referred to a human operator when AI cannot answer the question being asked. Why cannot AI be used to produce surgery lists and, answer questions and to contact patients informing them of their date and time of operation.

The third industrial revolution saw the growth of large companies such as Google, Apple, Microsoft, and Facebook.

The area around Silicon Valley hosted a large number of the major companies created as part of the third industrial or ICT based revolution our challenge in Wales, is to become the home of the major companies in the fourth AI led industrial revolution starting with health.