In October 2024, Meta, in collaboration with the Stanford Deliberative Democracy Lab, implemented the third Meta Community Forum. This Community Forum expanded on the October 2023 deliberations regarding Generative AI. For this Community Forum, the participants deliberated on ‘how should AI agents provide proactive, personalized experiences for users?’ and ‘how should AI agents and users interact?’ Since the last Community Forum, the development of Generative AI has moved beyond AI chatbots and users have begun to explore the use of AI agents — a type of AI that can respond to written or verbal prompts by performing actions for you, or on your behalf. And beyond text-generating AI, users have begun to explore multimodal AI, where tools are able to generate content images, videos, and audio as well. The growing landscape of Generative AI raises more questions about users’ preferences when it comes to interacting with AI agents. This Community Forum focused deliberations on how interactive and proactive AI agents should be when engaging with users. Participants considered a variety of tradeoffs regarding consent, transparency, and human-like behaviors of AI agents. These deliberations shed light on what users are thinking now amidst the changing technology landscape in Generative AI.

For this deliberation, nearly 900 participants from five countries: India, Nigeria, Saudi Arabia, South Africa, and Turkey, participated in this deliberative event. The samples of each of these countries were recruited independently, so this Community Forum should be seen as five independent deliberations. In addition, 1,033 persons participated in the control group, where the participants did not deliberate in any discussions; the control group only completed the two surveys, pre and post. The main purpose of the control group is to demonstrate that any changes that occur after deliberation are a result of the deliberative event.

Economic growth is uneven within many developing countries as some sectors and industries grow faster than others. India is no exception, where anemic performance in manufacturing has been offset by robust growth in services. Standard scholarly explanations fail to explain this kind of variation. For instance, the factor endowments that are required for services—such as an educated workforce or access to electricity and other infrastructure—should also complement manufacturing. Reciprocally, if a state’s institutions hold back manufacturing, they should also impair growth in services. Why have services in India outperformed manufacturing? We examine India’s performance in the computing industry, where a dynamic software services sector has emerged even as its computer hardware manufacturing sector has flagged. We argue that the uneven outcomes between the software and hardware sectors are due to the variable needs of the respective sectors and the state’s capacity to coordinate agencies. The policies required to promote the software sector needed minimal coordination between state agencies, whereas the computer hardware sector required a more centralized state apparatus for successful state-business engagement. Domestic and transnational political networks were critical for the success of the software sector, but similar networks could not deliver the same benefits to the computer hardware industry, which required more coordination-intensive policies than software. A state’s ability to coordinate industrial policy is thus a critical determinant for effective sectoral political networks, shaping sectoral variations within an economy.

The Chinese government is revolutionizing digital surveillance at home and exporting these technologies abroad. Do these technology transfers help recipient governments expand digital surveillance, impose internet shutdowns, filter the internet, and target repression for online content? We focus on Huawei, the world’s largest telecommunications provider, which is partly state-owned and increasingly regarded as an instrument of its foreign policy. Using a global sample and an identification strategy based on generalized synthetic controls, we show that the effect of Huawei transfers depends on preexisting political institutions in recipient countries. In the world’s autocracies, Huawei technology facilitates digital repression. We find no effect in the world’s democracies, which are more likely to have laws that regulate digital privacy, institutions that punish government violations, and vibrant civil societies that step in when institutions come under strain. Most broadly, this article advances a large literature about the geopolitical implications of China’s rise.

We are on the verge of a revolution in public sector decision-making processes, where computers will take over many of the governance tasks previously assigned to human bureaucrats. Governance decisions based on algorithmic information processing are increasing in numbers and scope, contributing to decisions that impact the lives of individual citizens. While significant attention in the recent few years has been devoted to normative discussions on fairness, accountability, and transparency related to algorithmic decision-making based on artificial intelligence, less is known about citizens’ considered views on this issue. To put society in-the-loop, a Deliberative Poll was thus carried out on the topic of using artificial intelligence in the public sector, as a form of in-depth public consultation. The three use cases that were selected for deliberation were refugee reallocation, a welfare-to-work program, and parole. A key finding was that after having acquired more knowledge about the concrete use cases, participants were overall more supportive of using artificial intelligence in the decision processes. The event was set up with a pretest/post-test control group experimental design, and as such, the results offer experimental evidence to extant observational studies showing positive associations between knowledge and support for using artificial intelligence.

As the Russian government seeks to improve its economic performance, it must pay greater attention to the role of technology and digitalization in stimulating the Russian economy. While digitalization presents many opportunities for the Russian economy, a few key challenges – cumbersome government regulations and an unequal playing field for foreign companies – restrict Russia's potential in digitalization. In the future, how the Russian government designs its technology and regulatory policies will likely have significant impact both on the domestic front, as well as on their international initiatives and relationships. This paper provides an overview of recent Russian digital initiatives, the regulatory barriers for U.S. technological companies in Russia, and the intellectual property challenges for doing business in Russia. This paper also discusses recent digital initiatives from China, the United States, and other countries, and discusses what such programs mean for Russia. In this context, we also discuss Chinese and U.S. efforts to shape the future of global technological standards, alongside new programs from countries like Chile and Estonia, to attract foreign startup companies. Finally, this paper discusses the future challenges that the Russian government needs to address in order to improve its digital business environment. The paper concludes by providing some recommendations for designing market-friendly regulations, creating a level-playing field for foreign businesses in Russia, promoting Russian engagement with Western companies and governments, and undertaking more outreach efforts to make Russia's digital business environment more inclusive.