How AI and Behavioral Science are Addressing Vaccine Hesitancy

摘要： Recently, nearly 25 percent of unvaccinated adults said that they definitely will not get vaccinated. Meaning, herd immunity will become very challenging to reach. Fortunately, however, the healthcare industry is trying to find ways to leverage AI and behavioral science to combat vaccine hesitancy and boost efforts to hit the herd immunity threshold.

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Thankfully, COVID-19 vaccination efforts are underway in countries around the world. And while there continues to be bits of promising news as vaccination rates continue to rise and new infection rates decline, one major challenge still remains as the world tries to get the COVID-19 pandemic officially under control: vaccine hesitancy.

With that in mind, here is how AI and behavioral science are being combined to help the healthcare space tackle vaccine hesitancy.

Assuaging Safety Concerns

Thanks to innovations in technology and science, COVID-19 vaccines have been produced in a fraction of the time that vaccines typically require. This is obviously significant in terms of both helping humanity overcome this virus quickly but also represents a watershed moment for vaccine production as well. However, given this rapid production timeline, some individuals remain skeptical about whether or not the vaccine is safe.

To combat this, government and healthcare companies are deploying AI to gather data on any side effects or adverse outcomes from patients that have been vaccinated. From there, the AI is being used to analyze data points and to detect any relevant patterns and flag them in far less time than it would take to do so manually. This is allowing the healthcare industry to provide more peace of mind to individuals that are unsure about the safety of getting vaccinated and to provide additional context around reported side effects.

Enabling Positive Global Outcomes and Collaboration

At the core of overcoming vaccine hesitancy is to ensure that patient outcomes — both in terms of immediate vaccine efficacy and mitigating post-vaccination side effects — are as positive as possible.

Unfortunately, tracking results and patient progress is a painstaking process for the healthcare industry and government health organizations — especially when it comes to doing so on a global basis. However, by embracing AI, healthcare companies and governments are making the tracking, analysis and collaboration much more efficient than has ever been possible before. For example, AI tools can facilitate a constant stream of real-time data analysis and trend detection that can help doctors, healthcare industry stakeholders and governments better understand how vaccine efforts are progressing. Moreover, it can help them detect any sort of anomalies and why they may have arisen much more rapidly than if they were using less sophisticated technology. This type of global collaboration and data set provides individuals with much deeper “proof” that vaccines are safe and effective, which in turn can further drive up vaccination rates.

Understanding Hesitancy Drivers

AI and data are incredibly powerful tools in raising awareness and building trust. However, as was proven early in the pandemic, having access to strong data does not automatically mean that individuals will be driven to act.

There is a common misperception that humans will always make the rational decision regardless of things like emotion. However, sometimes, despite having all of the data, emotion and “irrationality” do reign supreme when humans make decisions. Therefore, simply relying on data as the key to persuading humans to take a certain action does not always work. So, how do we make the data that we have ultimately translate into action? By pairing it with behavioral science insights.

The human brain is one of the most powerful machines on the planet. In fact, many of the complex processes we are now trying to have AI tackle have already been solved by the human brain through evolution. Therefore, AI professionals are beginning to look at behavioral science for clues — such as how emotions like fear or anxiety might influence human data perception and decision-making — and join it with data to develop a comprehensive approach to make sure that data is presented in the most effective way possible. From there, AI tools can become more informed and look for key insights that may reveal more about why individuals are or are not choosing to get vaccinated.

After what has been one of the most challenging years in modern history, glimpses of hope are finally arising as individuals begin to get vaccinated. However, significant challenges still remain in terms of trying to reach herd immunity. By embracing AI and behavioral science together, healthcare providers can better tackle any lingering concerns around getting vaccinated and build trust among patients for future vaccination efforts as well.

轉貼自： Inside Big Data

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