By Ritu Raj
June 10, 2021
The second part of our month-long series, Technology in HHS, looks at AI, the buzzword everywhere, but a technology that is making waves now in the Health and Human Services space as well. Read on to find out more.
In the age of Big Data, the old adage of “it’s not what you have, but what you do with it that counts,” comes to mind. Yes, we’ve got the “data,” but how is it being processed? How can it practically improve your day-to-day life? In the Department of Health and Human Services (HHS), this concern is even more pressing, as the health and well-being of citizens are at stake. This is where artificial intelligence (AI) comes in. Not quite the talking, scary masterminds we see in movies, AI can prove very useful when it comes to managing, processing, and making sense of data. Below are some reasons why AI is particularly well suited in the work of HHS.
Artificial intelligence is a broad term that encompasses computers that appear to “simulate” human intelligence. It can accomplish this through “learning,” or organizing and adapting to data on its own, such as self-driving cars. This cutting-edge technology can be employed in a variety of fields, from sequencing the genome, to writing music. The key here is that AI can see patterns or solutions that were previously invisible by analyzing vast amounts of data.
Just a few months ago, the Department of Health and Human Services issued a report that outlines a plan for incorporating AI into its operations. In this report, HHS not only argues that, in order to make full use of its partnerships with academia and the private sector, it needs an AI literate workforce, but that it is actively seeking insights from AI data processing and its ability to automate certain administrative functions.
There are many possibilities for AI in HHS. One of the most promising aspects is AI’s ability to automate routine operations, leaving more time for caseworkers to focus on more pressing matters. As with most large agencies, there is a lot of paperwork. Beyond simply automating some of this, AI can greatly reduce the threat of duplication and fraud by streamlining and routinizing the entire process. The added benefit of machine learning here can help identify potential areas that did not at first appear to be capable of being automated. In this sense, AI can help with both the “knowns” and the “unknowns.”
Additionally, AI can be very beneficial in instances of predictive intervention. In the case of child welfare, AI-aided predictive analytics can improve case outcomes by providing tools to caseworkers during their decision-making processes, such as risk scores and pattern identification.
However, AI in healthcare is still in its early stages, as these instances have yet to be scaled up and come with a few challenges.
At first glance, it may seem a little unsettling to have AI in the fields of “human” services. This is not entirely unwarranted. There are a few challenges and problems associated with AI in HHS.
Ultimately, AI is another technology, and not some evil robot, but even with this assurance, we are all too familiar with buggy rollouts, system crashes, and simply poorly designed products. Imagining these technical issues being widespread throughout an important sector should cause a little pause.
Besides the legal issue of culpability, there is also an issue associated with the predictive capacity of AI. If given enough data, AI can find patterns and correlations that were previously “hidden.” Because of this, the predictive capacity of AI is unparalleled. One can imagine in HHS or healthcare fields that, if provided with enough data about the citizen, AI can accurately begin predicting and inferring aspects about their life that should remain private.
Connected with this is the technical requirement for more and more data. There are legitimate concerns that this need for data would begin to create a problematic environment where privacy is not respected.
With all these legitimate concerns, it is easy to be discouraged. However, with the responsible use of technology, the right oversight, and the understanding that this technology should be compared to the field as it exists right now (and not some dystopian future), AI offers a large step forward in cost savings, efficiency, and overall ability of the HHS.
Here at Cardinality, we have been developing many use cases on AI, such as our Redbird AI engine, which powers our HHS platforms.
While it is hard to predict the future, AI in HHS is here to stay.
Schedule a 30-minute call with me to know more about how we are harnessing AI for the HHS space.