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The Stanford Deliberative Democracy Lab, based at the University’s Center on Democracy, Development and the Rule of Law, today released the findings from two national Community Forums on the evolving expectations around privacy and governance of AI-powered wearable devices. In collaboration with Meta, the forum engaged a representative sample of 550 participants — 300 from the United States and 250 from India — to solicit people's perspectives on user controls and societal expectations. The Community Forums were conducted as national Deliberative Polls.

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The Stanford Deliberative Democracy Lab, based at the University’s Center on Democracy, Development and the Rule of Law, today released the findings from two national Community Forums on the evolving expectations around privacy and governance of AI-powered wearable devices. In collaboration with Meta, the forum engaged a representative sample of 550 participants — 300 from the United States and 250 from India — to solicit people's perspectives on user controls and societal expectations. The Community Forums were conducted as national Deliberative Polls.

As AI wearables see rapid adoption worldwide, understanding public attitudes can help to ensure these technologies are developed and deployed responsibly. Three key themes emerged from the forum. Participants in both the U.S. and India indicated the highest levels of support for users having controls over when their wearables passively process environments and actively capture data. U.S. participants consistently favored individual agency over how wearables are used, both in public and private settings, whereas in India, there was a slight preference for governments to decide wearable usage rules in public spaces. Additionally, U.S. participants supported workplaces and schools having the primary authority to decide how AI-powered wearables should be used in those environments, while Indian participants also saw a significant role for governments in these settings.

The forum also revealed important nuances in public perspectives. For example, participants expressed a preference for AI wearables that are tailored to cultural and regional contexts, rather than standardized global designs. There was also broad support for AI agents capable of responding to emotional cues, underscoring the public's desire for personalized, human-centric wearable experiences.

"This global forum provided invaluable insights into how the public's expectations around privacy and governance of wearable AI are evolving," said Alice Siu, Associate Director of the Stanford Deliberative Democracy Lab. "The findings will be essential for policymakers, technology companies, and other stakeholders as they work to ensure these powerful technologies empower users while respecting fundamental rights."

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National community forums in the U.S. and India highlight differences in preferences for privacy, user control, and governance of emerging technologies.

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  • Stanford’s Deliberative Democracy Lab convened national forums in the U.S. and India to examine public attitudes toward AI-powered wearable devices.
  • Participants in both countries strongly supported user control over data collection, with differences in preferences for government and institutional oversight.
  • Findings highlight demand for culturally tailored designs and personalized, human-centered AI features as adoption of wearables grows.
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CDDRL Honors Student, 2026-27
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Daniel Hadi is an Economics and Art History double major from Portland, Oregon, completing an interdisciplinary honors thesis with CDDRL for the 2026–2027 academic year. His research bridges microeconomic evaluation with questions of institutional design, governance, and the politics of place-based development. Daniel has conducted research at the Council on Foreign Relations, the Stanford Technology Ventures Program, and the Hoover Institution. He is a U.S. Department of State Critical Language Scholar who studied Arabic in Oman. After Stanford, he hopes to pursue development economics focused on cultural preservation and entrepreneurship in low- and middle-income countries.

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CDDRL Honors Student, 2026-27
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Anusha Nadkarni is a B.A./M.A. student in Public Policy ('27) focusing on Development and Growth Policies. She is also a double minor in Global Studies and Human Rights, with a particular focus on issues related to South Asia, gender-based violence, international human rights law, and comparative democratic development. Her prior experience working as a nonprofit leader in student-led antiracist education implementation informs her restorative, culturally responsive, and empirically-informed approach to international equity issues.

Anusha's past engagement with these interests includes spending a summer working in Mumbai's courts, an internship analyzing development bank violations of human rights at the Accountability Counsel, and a Student Fellowship with the Huntington Program for Strengthening U.S.-India Relations at the Hoover Institution. In her personal life, Anusha loves to hike, spend time with her loved ones (including a very cute cat), and play the guitar.

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In an unprecedented collaboration, Stanford's Deliberative Democracy Lab has spearheaded the first-ever Industry-Wide Forum, a cross-industry effort putting everyday people at the center of decisions about AI agents. This unique initiative involving industry leaders Cohere, Meta, Oracle, PayPal, DoorDash, and Microsoft marks a significant shift in how AI technologies could be developed.

AI agents, advanced artificial intelligence systems designed to reason, plan, and act on behalf of users, are poised to revolutionize how we interact with technology. This Industry-Wide Forum provided an opportunity for the public in the United States and India to deliberate and share their attitudes on how AI agents should be deployed and developed.

The Forum employed a method known as Deliberative Polling, an innovative approach that goes beyond traditional surveys and focus groups. In November 2025, 503 participants from the United States and India engaged in an in-depth process on the AI-assisted Stanford Online Deliberation Platform, developed by Stanford's Crowdsourced Democracy Team. This method involves providing balanced information to participants, facilitated expert Q&A sessions, and small-group discussions. The goal is to capture informed public opinion that can provide durable steers in this rapidly evolving space.

As part of the process, academics, civil society, and non-profit organizations, including the Collective Intelligence Project, Center for Democracy and Technology, and academics from Ashoka University and Institute of Technology-Jodhpur, vetted the briefing materials for balance and accuracy, and some served as expert panelists for live sessions with the nationally representative samples of the United States and India.  

"This groundbreaking Forum represents a pivotal moment in AI development," said James Fishkin, Director of Stanford's Deliberative Democracy Lab. "By actively involving the public in shaping AI agent behavior, we're not just building better technology — we're building trust and ensuring these powerful tools align with societal values."

"This groundbreaking Forum represents a pivotal moment in AI development. By actively involving the public in shaping AI agent behavior, we're not just building better technology — we're building trust and ensuring these powerful tools align with societal values.
James Fishkin
Director, Deliberative Democracy Lab

The deliberations yielded clear priorities for building trust through safeguards during this early phase of agentic development and adoption. Currently, participants favor AI agents for low-risk tasks, while expressing caution about high-stakes applications in medical or financial domains. In deliberation, participants indicated an openness to these higher-risk applications if provided safeguards around privacy or user control, such as requiring approval before finalizing an action.

The Forum also revealed support for culturally adaptive agents, with a preference for asking users about norms rather than making assumptions. Lastly, the discussions underscored the need for better public understanding of AI agents and their capabilities, pointing to the importance of transparency and education in fostering trust in these emerging technologies.

"The perspectives coming out of these initial deliberations underscore the importance of our key focus areas at Cohere: security, privacy, and safeguards,” said Joelle Pineau, Chief AI Officer at Cohere. “We look forward to continuing our work alongside other leaders to strengthen industry standards for this technology, particularly for enterprise agentic AI that works with sensitive data."

The perspectives coming out of these initial deliberations underscore the importance of our key focus areas at Cohere: security, privacy, and safeguards. We look forward to continuing our work alongside other leaders to strengthen industry standards for this technology.
Joelle Pineau
Chief AI Officer, Cohere

This pioneering forum sets a new standard for public participation in AI development. By seeking feedback directly from the public, combining expert knowledge, meaningful public dialogue, and cross-industry commitment, the Industry Wide Forum provides a key mechanism for ensuring that AI innovation is aligned with public values and expectations.

“Technology better serves people when it's grounded in their feedback and expectations,” said Rob Sherman, Meta’s Vice President, AI Policy & Deputy Chief Privacy Officer.  “This Forum reinforces how companies and researchers can collaborate to make sure AI agents are built to be responsive to the diverse needs of people who use them – not just at one company, but across the industry.”

Technology better serves people when it's grounded in their feedback and expectations. This Forum reinforces how companies and researchers can collaborate to make sure AI agents are built to be responsive to the diverse needs of people who use them.
Rob Sherman
Vice President, AI Policy & Deputy Chief Privacy Officer, Meta

Through Stanford’s established methodology and their facilitation of industry partners, the Industry-Wide Forum provides the public with the opportunity to engage deeply with complex technological issues and for AI companies to benefit from considered public perspectives in developing products that are responsive to public opinion. We hope this is the first step towards more collaboration among industry, academia, and the public to shape the future of AI in ways that benefit everyone.

“We have more industry partners joining our next forum later this year”, says Alice Siu, Associate Director of Stanford's Deliberative Democracy Lab. “The 2026 Industry-Wide Forum expands our discussion scope and further deepens our understanding of public attitudes towards AI agents. These deliberations will help ensure AI development remains aligned with societal values and expectations.”

The 2026 Industry-Wide Forum expands our discussion scope and further deepens our understanding of public attitudes towards AI agents. These deliberations will help ensure AI development remains aligned with societal values and expectations.
Alice Siu
Associate Director, Deliberative Democracy Lab

For a full briefing on the Industry-Wide Forum, please contact Alice Siu.

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In an unprecedented collaboration, Stanford's Deliberative Democracy Lab has spearheaded the first-ever Industry-Wide Forum, a cross-industry effort putting everyday people at the center of decisions about AI agents.

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We propose an improved theoretically-grounded method to test for efficient risk pooling that allows for intertemporal smoothing, non-homothetic consumption, and heterogeneous risk and time preferences. Applying this method to recent panel data from Indian villages generates important new insights while confirming some earlier findings. Year-to-year smoothing of consumption takes place much more at the village level than at the individual level and occurs primarily through financial assets. While there is proportionally more smoothing of food than non-food consumption, accounting for differences in income elasticities between the two statistically eliminates this difference, indicating that risk pooling does not distort consumption choices in our study area. Finally, we find that consumption smoothing is affected jointly by income and liquid assets, and that there is no excess sensitivity to earned income.

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Journal of Development Economics
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Marcel Fafchamps
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February 2026, 103685
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Motivation & Overview


India’s services sector is internationally renowned and has helped propel the country’s economic growth. Indeed, in recent years, a majority of the value added to India’s GDP has been concentrated in services. Especially noteworthy are India’s software and computing services, which include large multinational conglomerates like Infosys and Tata Communications Services. 

Yet as Indian software has flourished, the growth of its computer hardware and manufacturing has been sluggish. Tellingly, India is still a net importer of hardware and other electronics. At first glance, this divergence is puzzling because both the software and hardware sectors should have benefited from India’s educated labor pool and infrastructure. How can these different sectoral outcomes be explained?
 


 

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Fig. 1: Electronics production value compared to software and software service revenues

 

Fig. 1: Electronics production value compared to software and software service revenues.
 



In “Comparing Advantages in India’s Computer Hardware and Software Sectors,” Dinsha Mistree and Rehana Mohammed offer an explanation in terms of state capacity to meet the different functional needs of each sector. Their account of India’s computing history emphasizes the inability of various state ministries and agencies to agree on policies that would benefit the hardware sector, such as tariffs. Meanwhile, cumbersome rulemaking procedures inherited from British colonialism impeded the state’s flexibility. Although this disadvantaged India’s hardware sector, its software sector needed comparatively less from the state, building instead on international networks and the efforts of individual agencies.

The authors provide a historically and theoretically rich account of the political forces shaping India’s economic rise. The paper not only compares distinct moments in Indian history but also draws parallels with other landmark cases, like South Korea’s 1980s industrial surge. Such a sector-based analysis could be fruitfully applied to understand why different industries succeed or lag in emerging economies. 

Different Sectors, Different Needs


In order to become competitive — both domestically and (especially) internationally — hardware manufacturers often need much from the state, what the authors call a “produce and protect regime.” This can include the construction of factories and the formation of state-owned industries (SOEs), as well as tariffs to reduce competition or labor laws that restrict union strikes. Perhaps most importantly, manufacturers need a state whose legislators and bureaucrats can coordinate with each other in response to market challenges. Such a regime is incompatible with excessive “red tape” or with the “capture” of regulators by narrow interest groups. Because customers tend to view manufactured goods as “substitutable” with each other, firms will face intense competition as regards price and quality.
 


 

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Fig. 2: Inter-agency coordination required for sectoral success

 

Fig. 2: Inter-agency coordination required for sectoral success.
 



The situation is very different for service providers, whose success depends on building strong relationships with customers. States are not essential to this process, even if their promotional efforts can be helpful. Coordination across government agencies is similarly less important, as just one agency could provide tax breaks or host promotional events that benefit service providers. Compared with manufacturing, customers tend to view services as less substitutable — they are more intangible and customizable, which renders competition less fierce. Understanding India’s computing history reveals that the state’s inability to meet hardware manufacturers’ needs severely constrained the sector’s growth. 

The History of Indian Computing


Although India inherited a convoluted bureaucracy from the British Raj, the future of its computing industry in the 1960s seemed promising: political elites in New Delhi supported a produce-and-protect regime, relevant agencies and SOEs were created, and foreign computing firms like IBM successfully operated in the country. 

Yet by the 1970s, some bureaucrats and union leaders feared that automation would threaten the federal government’s functioning and India’s employment levels, respectively. Strict controls in both the public and private sectors were thus adopted, for example, requiring trade unions — which took a strong anti-computer stance — to approve the introduction of computers in specific industries. The authors make special mention of India’s semiconductor industry. It arguably failed to develop due to lackluster government investment, the need for manufacturers to obtain multiple permits across agencies, decision makers ignoring recommendations from specialized panels, and so on.

Meanwhile, implementing protectionist policies proved challenging. For example, decisions to allow the importation of previously banned components required permission from multiple ministries and agencies. After India’s 1970s balance-of-payments crisis, international companies deemed inessential were forced to dilute their equity to 40% and take on an Indian partner. IBM then left the Indian market. At the same time, SOEs faced growing competition over government contracts and workers, owing to the growth of state-level SOEs.

The mid-1980s represented a partial turning point as Rajiv Gandhi became Prime Minister and liberalized the computing industry. Within weeks, Rajiv introduced a host of new policies and shifted the government’s focus from supporting public sector production to promoting private firms, which would no longer face manufacturing limits and would be eligible for duty exemptions. Changes to tariff rates and import limits would not require approval from multiple agencies. Meanwhile, international firms reengaged with Indian markets via the building of satellite links, facilitating cross-continental work, such as between Citibank employees in Mumbai and Santa Cruz.

However, this liberalizing period was undermined and partially reversed after 1989, when Rajiv’s Congress Party (INC) lost its legislative majority and public policy became considerably more fragmented. Anti-computerization forces, especially the powerful Indian trade unions, worked to stymie Rajiv’s reforms. Pro-market reformists were forced out of their positions in Indian bureaucracies. Rajiv was assassinated in 1991, after which Congress formed a minority government with computer advocate P. V. Narasimha Rao as PM. Yet all of this occurred at a delicate time, as India was at risk of defaulting and had almost completely exhausted its foreign exchange.

By the late 1990s, both the hardware and software sectors should have benefited from the rising global demand for computers, yet India’s history of poor state coordination hindered manufacturers. Meanwhile, software firms were able to take advantage of global opportunities given their comparatively limited needs from state actors and political networks — for example, helping European Union banks change their computer systems to Euros. Ultimately, the Indian state has powerfully shaped the fortunes of these different sectors.

*Research-in-Brief prepared by Adam Fefer.

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We conduct an interactive online experiment framed as an employment contract. Subjects from the US, India, and Africa are matched within and across countries. Employers make a one-period offer to a worker who can either decline or choose a high or low effort. The offer is restricted to be from a variable set of possible contracts. High effort is always efficient. Some observed choices are well predicted by self-interest, but others are better explained by conditional reciprocity or intrinsic motivation. Subjects from India and Africa follow intrinsic motivation and provide high effort more often. US subjects are more likely to follow self-interest and reach a less efficient outcome on average, but workers earn slightly more. We find no evidence of stereotypes across countries. Individual characteristics and stated attitudes toward worker incentives do not predict the behavioral differences observed between countries, consistent with cultural differences in the response to labor incentives.

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Games and Economic Behavior
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Marcel Fafchamps
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December 2025, Pages 175-199
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Chinese Foreign Minister Wang Yi traveled to New Delhi this week, marking the first visit of a high-level Chinese official to the Indian capital since the two countries agreed to disengage along their Himalayan border last October. Deadly border clashes in the Galwan Valley in 2020 had previously sent bilateral relations into a deep freeze.

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When it comes to managing the administrative tasks that are required to run a home and raise a family, women bear the brunt of the responsibility. According to one study of women in the United States, mothers take on 7 out of 10 so-called mental load tasks, which range from planning meals to scheduling activities for children.

All that extra work takes a toll, including on society: Women who carry more mental load are less interested in national politics (men who carry more mental load also report less political interest, but fewer men are in that position).

Read the full story in the Stanford Report.

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Political science professors Lisa Blaydes, Beatriz Magaloni, and James Fearon are among researchers at the King Center on Global Development addressing challenges such as gender-based violence and low labor participation, with the aim to inform supportive policy interventions.

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