AI in Healthcare: Concerns and Benefits

With artificial intelligence dominating the headlines across multiple industries, it’s important to understand how this technology affects your specific niche. In the case of the healthcare industry and life sciences, AI algorithms and the associated predictive analytics are being used by medical professionals to improve health outcomes across multiple channels.

Patient care is improving due to more efficient clinical workflows being achieved by the use of AI in healthcare supply chain management, more accurate diagnosis contributing to more efficient population health management, and improved patient outcomes that are made possible.

However, these advancements and advantages don’t come without concerns.

The Roots of Concern

Artificial intelligence is already revolutionizing health care, and changes are happening fast. Understandably, this rapid disruption is causing questions and even concerns to arise throughout the industry as to how AI will continue to impact the need for human interactions where apps and software are starting to encroach. The concerns of medical professionals over the expansion in the use of artificial intelligence lies in the many advantages the technology provides relative to the limits of human proficiency.

Powerful analytical tools allow AI to instantly assess data

Artificial intelligence tools introduce a rapidity into the data analytics process that cannot be matched by employees. AI technology can store more data, access it faster and with perfect recall, and synthesize it with breathtaking efficiency. Its deep learning and automation functionalities allow for next-level image recognition capabilities, making it potentially game-changing as a diagnostic tool in medical imaging.

When it comes to diagnosing breast cancer and skin cancer, for example, AI systems performed better in trials than human doctors and radiologists, picking up a greater number of cases and reducing both false positives and false negatives. Oxford University is currently trialing AI diagnosis for prostate cancer diagnosis, and researchers are hopeful for similar successes.

AI’s ability to rapidly synthesize and analyze diverse sets of data means that AI systems are very, very good at prediction. In fact, in 2019, an AI system developed by the Canadian company Blue Dot, detected a cluster of unusual pneumonia cases near a market in Wuhan China more than a week before the World Health Organization, working with traditional epidemiological models, issued a warning for the novel COVID-19 virus.

AI can be used to improve itself faster than we could iterate improvements 

Some of the most important developments happening right now are in the machine learning algorithms being used as the foundation for AI-driven solutions. Artificial intelligence has been present in health care in various forms since the 1970s, but recent developments in big data, computer processing power, and algorithm development have meant a giant leap forward in AI systems’ ability to teach themselves. Some experts predict that AI will reach a point of singularity–where it equals, then surpasses human intelligence–within the next decade. One couldn’t blame a casual observer for being concerned. 

Using perspective to better understand the impact of AI

Disruptive events always cause concern, and change is, and always has been inevitable. But before panicking, it’s important to adjust one’s perspective.

The 2009 introduction of Grammarly, an AI-enabled cloud-based writing assistant, was revolutionary in its own way. Suddenly, in addition to checking spelling, writers could self-edit for grammar, language use, and register, as well as check for plagiarism. Grammarly uses AI and natural language processing to train itself to adapt not only to the nuances of human language usage, but to the nuances of individual users’ language use.

It’s a powerful tool, but in the more than ten years since its introduction, it hasn’t replaced human editors. Why not? One reason is that an AI system is only as good as the corpus it trains on. AI training on a corpus of imperfect user-generated writing will necessarily generate errors–sometimes quite amusing ones.

Another reason is that, unlike an algorithm, human behaviors–like language use–are sometimes unpredictable, sometimes contrary, and are liable to go off-script. It takes a human editor to recognize sarcasm, semantically significant alternate spellings, and slang. In these cases, the AI-generated alternate suggestions are often laughably inappropriate.

 So while it might be able to craft eloquent and grammatically perfect content, AI will always need some form of human on the other side, double-checking not only for facts and accuracy, but also for tone and adding a human-element. 

What are the benefits of AI in healthcare?

This same requirement for human oversight is true with AI in healthcare settings. Poorly designed algorithms or biased data sets can result in imperfect learning and errors in performance. Moreover, artificial intelligence cannot replicate the therapeutic relationship between practitioner and patient, which is so vital to effective treatment.

AI will never replace medical personnel, but it can be an incredible assistant. As part of a human practitioner’s toolkit, artificial intelligence has the potential to turbocharge healthcare in a number of different ways.

Improving Efficiency

AI systems’ data-crunching virtuosity can help both healthcare organizations and individual practitioners to make the most of their data. Imagine a given practitioner being able to instantly bring vast bodies of knowledge to bear on a given case. Combining and analyzing disparate data can also help practitioners to identify problems they might have missed, or predict issues that might arise.

At the organizational level, harnessing AI’s analytical abilities can increase the efficiency of operational workflows and processes, helping the practice to make the most of its resources.

Relieving Administrative Burden

AI’s ability to store, recall, and synthesize information can go a long way toward helping practitioners and administrators struggling under the burden of excessive paperwork. From optimizing research to highlighting patterns and trends a human may miss, AI has the potential to do the footwork for human practitioners, freeing them to provide patient-centered care. Products like IBM’s Watson Health are already doing all of these things and more.

Optimizing Patient Experience

Properly trained AI can also help to reduce health inequity. Unconscious racial, gender, age, and other biases demonstrably affect both research and care, resulting in poorer outcomes for many patients. Machine analysis of patient data removes human bias from the equation, paving the way for more objective diagnoses and interpretation of research results.

Artificial intelligence can help human practitioners to tailor treatment programs to the needs of individual patients. Just as Grammarly can help to individualize self-editing, AI can combine large datasets with machine learning to provide individualized insights and experiences for patients. By combining data sets, for example patient records, with databases of caseworkers and counselors, AI can help practitioners to put together more complete plans of care and treatment for their patients.

Error Detection

Medical errors result in an estimated 200,000 deaths per year and an estimated annual cost of $1.9 billion. Artificial intelligence systems could potentially reduce both of these figures by spotting errors missed by even the most experienced and competent healthcare professionals, or even predicting them before they happen.