Introduction

Generative AI has become an incredibly attractive and widespread tool for people across the world. Alongside its rapid growth, AI tools present a host of ethical challenges relating to consent, security, and privacy, among others. As Generative AI has been spearheaded primarily by large technology companies, these ethical challenges — especially as viewed from the vantage point of ordinary people — risk being overlooked for the sake of market competition and profit. What is needed, therefore, is a deeper understanding of and attention to how ordinary people perceive AI, including its costs and benefits.

The Meta Community Forum Results Analysis, authored by Samuel Chang, James S. Fishkin, Ricky Hernandez Marquez, Ayushi Kadakia, Alice Siu, and Robert Taylor, aims to address some of these challenges. A partnership between CDDRL’s Deliberative Democracy Lab and Meta, the forum enables participants to learn about and collectively reflect on AI. The impulse behind deliberative democracy is straightforward: people affected by some policy or program should have the right to communicate about its contents and to understand the reasons for its adoption. As Generative AI and the companies that produce it become increasingly powerful, democratic input becomes even more essential to ensure their accountability. 

Motivation & Takeaways

In October 2024, the third Meta Community Forum took place. Its importance derives from the advancements in Generative AI since October 2023, when the last round of deliberations was held. One such advancement is the move beyond AI chatbots to AI agents, which can solve more complex tasks and adapt in real-time to improve responses. A second advancement is that AI has become multimodal, moving beyond the generation of text and into images, video, and audio. These advancements raise new questions and challenges. As such, the third forum provided participants with the opportunity to deliberate on a range of policy proposals, organized around two key themes: how AI agents should interact with users and how they should provide proactive and personalized experiences for them.

To summarize some of the forum’s core findings: the majority of participants value transparency and consent in their interactions with AI agents as well as the security and privacy of their data. In turn, they are less comfortable with agents autonomously completing tasks if this is not transparent to them. Participants have a positive outlook on AI agents but want to have control over their interactions. Regarding the deliberations themselves, participants rated the forum highly and felt that it exposed them to alternative perspectives. The deliberators wanted to learn more about AI for themselves, which was evidenced by their increased use of these tools after the deliberations. Future reports will explore the reasoning and arguments that they used while deliberating.
 

Image

^{The participants of this Community Forum were representative samples of the general population from five countries - Turkey, Saudi Arabia, India, Nigeria, and South Africa. Participants from each country deliberated separately in English, Hindi, Turkish, or Arabic.}

Methodology & Data

The deliberations involved around 900 participants from five countries: India, Nigeria, Saudi Arabia, South Africa, and Turkey. Participants varied in terms of age, gender, education, and urbanicity. Because the deliberative groups were recruited independently, the forum can be seen as five independent deliberations. Deliberations alternated between small group discussions and ‘plenary sessions,’ where experts answered questions drawn from the small groups. There were around 1000 participants in the control group, who did pre- and post-surveys, but without deliberating. The participant sample was representative with respect to gender, while the treatment and control groups were balanced on demography as well as on their attitudes toward AI. Before deliberating on the proposals, participants were presented with background materials as well as a list of costs and benefits to consider.

In terms of the survey data, large majorities of participants had previously used AI. There was a statistically significant increase in these proportions after the forum. For example, in Turkey, usage rates increased from nearly 70% to 84%. In several countries, there were large increases in participants’ sense of AI’s positive benefits after deliberating, as well as a statistically significant increase in their interest. The deliberations changed participants’ opinions about a host of claims; for example, “people will feel less lonely with AI” and “more proactive [agents] are intrusive” lost approval whereas “AI agents’ capability to increase efficiency…is saving many companies a lot of time and resources” and “AI agents are helping people become more creative” gained approval. After deliberating, participants demonstrated an improved understanding of some factual aspects of AI, although the more technical aspects of this remain challenging. One example here is AI hallucinations, or rather, the generation of false or nonsensical outputs, usually because of flawed training data.
 

Image

Proposals

Participants deliberated on nineteen policy proposals. To summarize these briefly: In terms of whether and how AI remembers users’ past behaviors and preferences, participants preferred proposals that allowed users to make active choices, as opposed to this being a default setting or only being asked once. They also preferred being reminded about the ability of AI agents to personalize their experience, as well as agents being transparent with users about the tasks they complete. Participants preferred that users be educated on AI before using it, as well as being informed when AI is picking up on certain emotional cues and responding in “human-like” ways. They also preferred proposals whereby AI would ask clarifying questions before generating output. Finally, when it comes to agents helping users with real-life relationships, this was seen as more permissible when the other person was informed. Across the proposals, gender was neither a significant nor consistent determinant of how they were rated. Ultimately, the Meta Community Forum offers a model for how informed, public communication can shape AI and the ethical challenges it raises.

How do aging populations reshape health and innovation policies in Asian economies? What role can the private sector play in public health service delivery, and how do individual preferences affect the development of emerging technologies? Mai Nguyen and Jinseok Kim, the 2024-25 Asia health policy postdoctoral fellows at APARC, focus on these questions as part of their research into health care service adaptation and behavioral economics.

At a recent joint seminar, “Health, Aging, Innovation, and the Private Sector: Evidence from Vietnam and Korea,” they offered a comparative look at how Vietnam and South Korea navigate aging populations, rising healthcare demands, and rapid technological change. While Nguyen focuses on health system design in Vietnam and Kim explores innovation diffusion in Korea, they both use discrete choice modeling to understand how individuals make decisions within systems influenced by age, infrastructure, and policy.

Sign up for APARC newsletters to receive updates from our scholars >

Nguyen and Kim’s work is supported by APARC’s Asia Health Policy Program (AHPP), which offers a postdoctoral fellowship each year to an early-career scholar conducting original research on health policy in the Asia-Pacific, particularly in low- and middle-income economies across the region. The fellowship demonstrates the program’s commitment to fostering the next generation of Asia-focused health policy researchers.

Vietnam’s Mixed Health System and the Role of Patient Choice

Mai Nguyen’s research centers around the role of private healthcare providers in Vietnam, especially for patients managing chronic diseases such as diabetes. She studies how patients choose between public and private healthcare providers, and what attributes of care they value most.

To analyze these preferences, she uses a method known as the Discrete Choice Experiment, which allows her to quantify the relative importance of various service attributes — such as appointment flexibility, doctor choice, quality of care, drug diversity, and cost coverage — in influencing patients’ decisions.

Nguyen’s interest in this topic began while she worked at Vietnam’s Ministry of Health. “That earlier work highlighted the growing contribution of the private sector in filling service delivery gaps, particularly in urban areas and for non-communicable diseases such as diabetes,” she says.

Her findings suggest that Vietnam’s private sector has become a necessary complement to public healthcare. “Despite potential downsides, such as increased costs, equity concerns, and profit-driven service delivery, my study finds that private healthcare helps relieve pressure on the public system and meets diverse patient needs.”

At APARC, Nguyen has sharpened the focus of her research under the mentorship of AHPP Director Dr. Karen Eggleston, a leading expert on public and private roles in Asian health systems. Nguyen also values her collaboration with Jinseok Kim. “Dr. Kim’s expertise provides valuable insights into how Korea is addressing the challenges of a rapidly aging population through innovative policy and service delivery models,” she notes.

Her time at Stanford has also broadened Nguyen’s horizons beyond traditional health economics. “I have developed a strong interest in the application of artificial intelligence to enhance the delivery of medical services,” she says. Looking forward, she plans to expand her research to Asian American populations in the United States, exploring how AI and digital health can improve diabetes care while also addressing barriers related to equity and access.

Innovation Adoption and the Aging Consumer in South Korea

Jinseok Kim investigates how aging affects new technology adoption and consumer behavior in South Korea, a country facing one of the fastest demographic shifts in the world.

“My current research involves looking at population aging and innovation diffusion, specifically in the context of the rapid aging trend in Korea,” Kim says. He studies how age influences consumer preferences in choosing new technologies such as electric vehicles, telemedicine, and generative AI platforms like ChatGPT.

Understanding these preferences, Kim argues, is critical for both policy and market strategy. “By working out the relationship between consumer choice and population aging, I forecast the effect of the population aging trend on the diffusion of innovative products and provide the potential policy and marketing implications for government policy and corporate management.”

The challenge, he says, lies in making sense of a wide range of behaviors across age groups and product types. “The biggest challenge I had in my studies was finding the overarching trend in the relationship between consumer choice for particular innovative products and population aging and then translating this finding into meaningful implications for society and the economy.”

Kim credits his time at APARC, especially participating in the Stanford Next Asia Policy Lab (SNAPL) meetings, with broadening his perspective. “Working as a member of SNAPL gave me insights and perspectives I didn’t have before,” he says.

SNAPL, directed by Professor Gi-Wook Shin, is an interdisciplinary research initiative housed within APARC addressing pressing social, cultural, economic, and political challenges in Asia through comparative, policy-relevant studies. The lab cultivates the next generation of researchers and policy leaders by offering mentorships and fellowship opportunities for students and emerging scholars.

Kim sees APARC’s model as effectively bridging academia and policy. “There are so many opportunities to interact with other scholars, policymakers, and practitioners,” Kim says. “Scholars here not only research and write, but they also get to share their voice and research findings in real-world policy.”

His advice to early-career researchers is straightforward. “Be more down-to-earth with your studies and thinking,” Kim says. “Sometimes scholars tend to get caught up in their way of thinking and perspective, but it may not be practical in real life. That is why I think it is important to just get outside and observe real consumer choice and behavior.”

Kim plans to continue researching questions related to innovation and demographic change to help governments and businesses adapt to aging populations and shifting consumer needs.

Ground-Level Data, Big-Picture Impact

Mai Nguyen and Jinseok Kim approach shared societal challenges through distinct yet complementary lenses. Nguyen’s research reveals how patient preferences can guide more effective public-private collaboration in healthcare, ultimately shaping systems that are more responsive to real-world needs. Meanwhile, Kim examines how patterns of technology adoption — especially among older adults — can influence the trajectory of innovation in aging societies.

Both scholars emphasize the value of ground-level data in addressing large-scale issues. By centering real behaviors and preferences, their work helps inform smarter, more adaptive policy, whether in designing patient-centered care or planning for technology's role in future societies. At APARC, their research bridges theory and practice, offering fresh insight into how Asian countries can navigate the twin forces of demographic change and rapid innovation.

Maturing our Community Forum Program

Beyond the findings of any one Forum, the Deliberative Democracy Lab and Meta have heard important feedback from stakeholders and have implemented several programmatic changes to mature our program. These include:
 

• More disclosure around the impact of results: Meta will share more information about how results are being actioned within the company on its Transparency Center page, which will be updated throughout the year.
• Following up with participants: We heard the importance of going back to participants to explain what we learned from their input and what we are doing with it. The Deliberative Democracy Lab will be hosting calls with participants from each of our past Community Forums, dating back to 2022, to update them on the findings from the Forum and Meta’s response.
• Supporting AI deliberation: A team of Meta AI experts has begun partnering with the Deliberative Democracy Lab to conduct research on how AI might further scale deliberation and optimize the Community Forum process. This includes, but is not limited to, using AI to aggregate themes that are emerging in discussions in real time and support engagement between participants and experts in plenary sessions.
• Supporting external research: Meta is supporting a consortium of independent researchers from around the world who will evaluate the data from its Forums and publish research papers on the deliberations and results. This will culminate in an academic conference later this year.