Category: Research

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A Congressional Trade Office could resolve all this tariff confusion

 Susan Ariel Aaronson

Congress shares responsibility with the president for trade policy, yet Congress lacks the infrastructure and expertise to set objectives and monitor the administration’s actions. Moreover, because President Trump sees tariffs as his Swiss Army knife for multiple purposes, Congress has been unable to effectively challenge the dramatic changes to trade policy made by the administration. 

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Do Chatbot Developers Act Responsibly toward their Users?

 Susan Ariel Aaronson and Michael Moreno

Please note this paper is forthcoming, to be published by the Balsillie School in February 2026. 

This study evaluates whether leading AI developers—OpenAI, Google, xAI, and DeepSeek—act responsibly toward users when building and deploying chatbots. We assess how each firm defines and implements responsibilities related to user rights and welfare through website claims, technical documentation, and chatbot behavior. Using a mixed-methods comparison, we find that companies publicly emphasize safety but inconsistently discuss accountability, transparency, and protections for users at risk of harm. Technical documents largely explain model architecture rather than how developers mitigate risks to vulnerable users, while chatbot responses vary over time and across firms in addressing self-harm, privacy, and abusive content. Our findings show that AI responsibility remains fragmented, revealing opportunities for policymakers to establish clearer norms for protecting user rights and welfare.

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AI and Trade: The WTO’s Thoughtful but Incomplete Assessment

When the World Trade Organization (WTO) decided in 2024 to produce a report on the trade implications of artificial intelligence (AI), it set out to answer two key questions: How can the WTO help ensure that the benefits of AI are widespread? And, how can the challenges surrounding AI be addressed in a globally coordinated manner? This paper analyses the WTO’s findings and explores how AI is prompting a re-examination of trade rules as well as how and what nations trade. Following an analysis of the trade and technology relationship, the author then discusses how AI poses challenges to how trade is conducted and the current rules system. The author’s recommendations for the WTO include partnering with civil society groups that have expertise in competition policy and data governance; doing research on trade-related global issues; and using trade policy reviews to better understand global data markets.

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Public Concerns About AI Are Getting Lost in Translation

Artificial intelligence (AI) is playing an increasingly important role in people’s lives, which has led to growing calls for AI regulation. Although the public has strong opinions on AI, getting policy makers to listen often leads to citizens’ concerns getting “lost in translation.” This paper looks at whether and how three countries (Australia, Colombia and the United States) sought public opinion on AI governance and offers recommendations on how to improve citizen engagement in AI policy making. The authors found that none of the three countries made much effort to seek public input, resulting in less than one percent of their respective populations participating in the consultative process.

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Do AI Chatbot Firms Practice What They Preach?

This study examines whether leading AI chatbot companies implement the responsible AI principles they publicly advocate. The authors used a mixed-methods approach analyzing four major chatbots (ChatGPT, Gemini, Deep Seek, and Grok) across company websites, technical documentation, and direct chatbot evaluations. We found significant gaps between corporate rhetoric and practice.
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China-U.S. Rivalry Will Split the World into Competing AI Camps

The U.S. and China both put forward plans for artificial intelligence last month. The two have long sought to lead on AI, and their competition has led to technological breakthroughs, lower costs, and wider use of the technology. But as their new plans illustrate, that competition may also divide the world into competing realms of AI products and governance.

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Taking the Wrong Lesson from China’s AI Strategy

Taking the Wrong Lesson from China’s AI Strategy

The United States is mimicking China’s approach to centralized data, risking privacy, security and democratic accountability in the name of AI leadership.

Chinese leaders early on recognized the importance of data for artificial intelligence (AI). In 2015, officials announced incentives to treat data as a key factor of production. More recently, China became the first country to create official markets for data. Chinese policy makers developed standards that enabled private entities to claim data as an asset on balance sheets. But China may have made a data “misstep.” In 2014, Beijing announced that it would allow government agencies to share data about Chinese companies and citizens, create a centralized scoring mechanism to assess the financial creditworthiness of individuals and companies, and use that data to nudge citizens toward state-sanctioned “moral values.” Observers noted that the plan has yielded mixed results, and spillover effects such as corruption and distrust. Nonetheless, on April 1, 2025, the government announced new guidelines on the social credit system, intended to create a “unified national market.”

Although the Trump administration has worked to thwart China’s AI leadership, it is copying some aspects of China’s data policies by creating a unified federal data set.

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Regrets of the Tech Bros: In a land ruled by the law of the jungle

On his Inauguration Day, Donald Trump sent a message. The founders and CEOs of Apple,Amazon, Google, Meta, Open AI, and Uber, among other giant high-tech companies, sat in the front rows near the Trump family and cabinet nominees. Trump and his staff wanted to use that display of innovation, money, and power to convey that he was supported by America’s most successful companies. In turn, these leaders hoped the administration would ease the regulation of data-driven technologies and the business practices (surveillance capitalism) followed by many of these giant firms.

However, some two months later, many of these tech bros may regret their unabashed support for the future Trump
promised.

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The Dangers of AI Nationalism and Beggar-Thy-Neighbour Policies

As they attempt to nurture and govern AI, some nations are acting in ways that – with or without direct intent – discriminate among foreign market actors. For example, some governments are excluding foreign firms from access to incentives for high-speed computing, or requiring local content in the AI supply chain, or adopting export controls for the advanced chips that power many types of AI. If policy makers in country X can limit access to the building blocks of AI – whether funds, data or high-speed computing power – it might slow down or limit the AI prowess of its competitors in country Y and/or Z. At the same time, however, such policies could violate international trade norms of non-discrimination. Moreover, if policy makers can shape regulations in ways that benefit local AI competitors, they may also impede the competitiveness of other nations’ AI developers. Such regulatory policies could be discriminatory and breach international trade rules as well as long-standing rules about how nations and firms compete – which, over time, could reduce trust among nations. In this article, the author attempts to illuminate AI nationalism and its consequences by answering four questions:

– What are nations doing to nurture AI capacity within their borders?

– Are some of these actions trade distorting?

 – Are some nations adopting twenty-first century beggar thy neighbour policies?

– What are the implications of such trade-distorting actions?

The author finds that AI nationalist policies appear to help countries with the largest and most established technology firms across multiple levels of the AI value chain. Hence, policy makers’ efforts to dominate these sectors, as example through large investment sums or beggar thy neighbour policies are not a good way to build trust.

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G20 AI Strategies

Many nations have started to publish national AI strategies. Since Canada released its strategy in 2017, 11 other G20 members have followed suit, but each nation has approached its AI strategy differently. The Digital Trade and Data Governance Hub has examined these strategies and produced two documents. The first provides an overview summarizing the main goals of each national AI strategy, and the second provides an analysis of how each strategy deals with data governance with respect to AI. Our analysis shows that there is no one formula to achieve a national AI strategy. Thus, strategies range in focus and cover aspects such as funding, research, infrastructure, ethics, jobs, standards, and data governance. These documents are current as of August 2019 and will be updated every 6 months.

G20 National AI Strategies Overview

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G20 AI Strategies on Data Governance

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Below are the G20 countries with each country’s AI strategy.

A more in-depth look at G20 and their data governance strategies can be found in our G20 data governance overview.

Country AI Strategy
Argentina No dedicated plan
Australia 2018-2019 budget announced a four-year investment to support the development of AI in Australia
Brazil No dedicated plan
Canada Pan-Canadian Artificial Intelligence Strategy (2017)
China A Next Generation Artificial Intelligence Development Plan (2017)
France For a Meaningful Artificial Intelligence: Towards a French and European Strategy (2018)
Germany AI strategy (2018)
India National AI Strategy (2018)
Indonesia No dedicated plan
Italy White Paper on Artificial Intelligence at the service of citizens
Japan Artificial Intelligence Technology Strategy (2017)
Mexico Towards an AI Strategy in Mexico: Harnessing the AI Revolution (2018)
Republic of Korea Mid- to Long-Term Master Plan in Preparation for the Intelligent Information Society Managing the Fourth Industrial Revolution
Republic of South Africa No dedicated plan
Russia No dedicated plan
Saudi Arabia No dedicated plan
Turkey No dedicated plan
United Kingdom AI Sector Deal (2018)
United States American AI Initiative (2019)
European Union Communication on Artificial Intelligence (2018)

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