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Introducing “Health Communication AI”: The Next Iteration of Opinion Leader for the Age of Artificial Intelligence

Authors: Amelia Burke-Garcia, PhD, AM, Director, Center for Health Communication Science and Program Area Director, Digital Strategy & Outreach, NORC at the University of Chicago; and Rebecca Soskin Hicks, MD, NORC at the University of Chicago.

Today, we find ourselves in one of the most challenging communication environments ever faced – characterized by a fragmented ecosystem, driven in large part by mis- and disinformation, a loss of institutional trust and a widening digital divide.

The emergence of artificial intelligence (AI) and large language models (LLMs) is exacerbating these issues.

AI-generated misinformation increases the spread and exposure to misleading health and medical information, posing a major challenge to health and well-being (Monteith et al., 2023). This may include factual errors, fabricated sources, and dangerous advice – all of which can impact lives.

It is not all bad news though.

Early research suggests that AI models can be used to deliver accurate health information – and in an empathetic way. Some models have been shown to surpass general human emotional awareness, scoring near maximum possible scores on Levels of Emotional Awareness Scales (LEAS) testing (Elyoseph et al., 2023); and work by Ayers et al. (2023) and Liu et al. (2023) suggests that in some cases, patients may prefer empathetic AI-authored responses to physician-authored ones.

We posit that while AI models are contributing to this problem of misinformation, they can also be part of the solution.

To realize the potential that lies in AI solutions for health communication, we need to invest in a new scientific agenda we are calling, “Health Communication AI,” which we define as,

“An approach that blends the authenticity of social media influencers with AI’ s technological scale capabilities informed by accurate and up-to-date health- and health communication-related expertise” (Burke-Garcia & Soskin Hicks, in press). 

This idea is predicated on an understanding of the role of opinion leaders in health promotion programs and uses Burke-Garcia’s (2019) work as a blueprint.

Researchers have been examining opinion leadership and health promotion for decades (Becker, 1970; Centola, 2021; Dearing, 2009; Rogers, 1962; Rogers, 2003; Valente, 2012; Valente & Pumpuang, 2007; Burke-Garcia et al., in press) and central to their role is the prima facie credibility they have with their communities (Valente & Pumpuang, 2007; Burke-Garcia, 2017). This comes from both their trustworthiness and expertise as perceived by their communities (Hovland et al., 1953) and the emotional intensity and intimacy between them and their communities (Gatignon & Robertson, 1986; Granovetter, 1973; Burke-Garcia, 2017).

Burke-Garcia’s (2019) work builds on this, positing that social media influencers are modern-day opinion leaders, as they have that same prima facie credibility and trust with their followers.

The promise of “Health Communication AI” lies in the potential for AI to establish this same prima facie credibility with individuals. Recent research at Google demonstrated their LLM to outperform primary care physicians on measures of empathy, perceived honesty, and accuracy in digital diagnostic conversations when rated by both patient actors and specialty physicians (Tu et al., 2024).

Perhaps most powerfully, however, is the reality that AI can do this at scale.

Currently, much of the communication of reliable health information depends on human interactions, either face-to-face or through digital interactions. This solution does not scale effectively to address the problem of health misinformation.

Human health communicators simply cannot interact quickly or comprehensively enough to engage with the millions of users participating in health-related digital conversations each day. Worldwide, users search for health content on Google Search at a rate of 70,000 queries per minute and up to 90% of Americans regularly search for health information on social media (Bishop, 2019). Additionally, human engagement on social media is often driven by high emotion and disagreement, thus making maintaining empathetic interactions challenging (Berger, 2011; Messing & Weisel, 2017).

“Health Communication AI” addresses these issues, making it the natural next step in the evolution of opinion leadership.

Achieving the vision of “Health Communication AI” requires several foundational shifts. First, the fields of public health and medicine need to embrace AI solutions as tools to support health communication. We need to work with technology innovators to ensure that model design and training is done with unbiased domain and health communication expertise.

The recent challenges experienced with the World Health Organization’s (WHO) newly launched Smart AI Resource Assistant for Health (S.A.R.A.H.) (Gil, 2024) demonstrates the importance of developing health related AI systems vis a vis a robust scientific agenda with rigorous testing to prove safety prior to launch.

AI’s dual role as both a challenge to and potential solution for the dissemination of credible and timely health information in tailored and empathetic ways underscores the urgent need to responsibly leverage its capabilities.

As we stand at this technological crossroads, the time to act is now.

References

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