Artificial Intelligence (AI) is a broad area of computer science involving technologies that can learn to make decisions and perform tasks that previously required human action.1 At its core, AI depends on two things – data and the models used to train algorithms to behave in certain ways based on the data. AI can manipulate the algorithms by learning behavior patterns from the data set. Greater quantities and higher quality data sets result in higher performance from the AI.
Some AI applications, such as facial recognition software, social media algorithms, and self-driving cars have gained notoriety and raised legal and ethical concerns. More commonly, however, AI is being used to accomplish undertakings impractical for humans, such as discerning patterns and predicting outcomes from massive amounts of data, or to perform routine tasks that take valuable time from workers whose talents might be put to better use.
Some AI applications drive common consumer experiences, such as personalized shopping recommendations, chatbots and voice assistants, spam filters, and GPS technologies. Businesses use AI for employee recruitment, security and fraud prevention, transportation logistics, and personalized marketing, to name just a few examples.
Many AI applications are built on foundational, or large language models, which can be adapted to a wide range of downstream tasks. Generative AI systems, such as ChatGPT and GPT-4, are being used to generate foundational content for reports, articles, scripts, and even musical scores.
AI technologies are advancing quickly, and the use of AI in business has been growing steadily. Since 2017, the number of organizations that report using AI has increased 2.5 times.3 Many, industries are using AI in some form today, as well as planning to expand its applications going forward, including the healthcare and workers’ compensation sectors.
Currently, AI is being used by hospitals and healthcare systems in multiple ways, including adverse-event prediction, schedule optimization, and inventory control.4 Healthcare providers are using AI for such applications as chronic disease management and personalizing the patient experience. However, overall adoption is still in early stages. Only 14% of healthcare professionals report using AI today, and 33% believe that AI will hurt the healthcare industry more than it helps.5 Industry analysts disagree, however. According to McKinsey, “AI represents a meaningful new tool that can help unlock a piece of the unrealized $1 trillion of improvement potential present in the [healthcare] industry.”4
Projections for the future of AI in healthcare are optimistic. The global market for healthcare-specific AI applications was valued at $16.5 billion in 2022 and is expected to reach $198 billion by 2030.6 The anticipated rapid growth is attributed to multiple factors, including the COVID-19 pandemic (which put excessive pressure on the healthcare system and accelerated the need for automated solutions), increasingly large volumes of patient information available through electronic health records (EHR) and other data sources, and expanding opportunities to develop AI applications using the revolutionary ChatGPT and GPT-4 technologies.
There is no question that the healthcare industry needs solutions to combat staffing shortages and rising costs. AI holds the promise of significant help, as well as some risks.
As noted, AI is already being used in healthcare but is nowhere near reaching its full potential. New and expanded ways that AI might improve healthcare delivery abound, including:
For all its benefits, the use of AI in healthcare also comes with questions and risks regarding transparency, accountability, bias, and privacy.
AI technology is advancing quickly and many concerns about potential misuse and unintended consequences have been raised. As of today, few laws or regulations specific to artificial intelligence exist. However, legislators at the both the state and federal levels are actively investigating the issue and numerous AI-related rules and regulations have been proposed or are pending.
Please see State of the States in this issue for more details
Any improvements to healthcare accessibility, quality, and cost is bound to have a positive impact on workers’ compensation medical care. Reliably accurate diagnostics, better informed clinical decision support, improved medication management, expanded remote care, and higher levels of personalization and efficiency would all positively affect workers’ comp on their own. In combination, the impact could be life changing for injured workers and a game changer for workers’ comp payers.
In addition to the promise of better care, AI may help workers’ compensation medical care programs to:
This is hardly an exhaustive list. AI technology is advancing rapidly with new applications being discovered every day, not only to the medical aspects of claims, but to all of workers’ compensation claims management. Exactly which applications will be developed and succeed in the near future remains to be seen. Exactly which applications will be developed and succeed in the near future remains to be seen.