Category: Publications

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Data Disquiet: Concerns about the Governance of Data for Generative AI

The growing popularity of large language models (LLMs) has raised concerns about their accuracy. These chatbots can be used to provide information, but it may be tainted by errors or made-up or false information (hallucinations) caused by problematic data sets or incorrect assumptions made by the model. The questionable results produced by chatbots has led to growing disquiet among users, developers and policy makers. The author argues that policy makers need to develop a systemic approach to address these concerns. The current piecemeal approach does not reflect the complexity of LLMs or the magnitude of the data upon which they are based, therefore, the author recommends incentivizing greater transparency and accountability around data-set development.

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Facing Reality: Canada Needs to Think about Extended Reality and AI

Although Canada is a leader in becoming the first nation to develop an artificial intelligence (AI) strategy, it is falling behind other countries in extended reality (XR) competitiveness. In this paper, the authors look at why Canada is lagging in this area and what can be done to bring the country up to speed with its peers. The authors argue that more attention and funding should be directed toward the development of XR technology in Canada because XR is already a major contributor to the Canadian and global economy; XR and AI will shape future iterations of the internet; a variant of XR (digital twins, which serve as models of people or objects) can serve as tools to develop mitigating strategies for various types of complex problems; and other nations, such as China and South Korea, are investing heavily in XR technology to gain a competitive edge.

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The U.S.-led digital trade world order is under attack–by the U.S.

The U.S.-led digital trade world order is under attack–by the U.S.

This year, America’s digital trade negotiator made a startling announcement at the World Trade Organization (WTO). The negotiator spoke at the behest of U.S. Trade Representative Ambassador Kathrine Tai. At the time, Congress and various U.S. regulatory agencies were considering new regulations for large tech companies, which meant that the U.S. would no longer support language at the WTO related to cross-border data flows. In the words of the Office of the U.S. Trade Representative (USTR), the U.S. now needs “policy space” to regulate the tech giants.

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XR ASSOCIATION PUBLISHES NEW WHITE PAPER WITH DIGITAL TRADE AND GOVERNANCE HUB AT GWU EXPLORING US COMPETITIVENESS IN IMMERSIVE TECHNOLOGY

Washington, D.C. – On November 8, 2023, the XR Association (XRA), the trade association representing the growing ecosystem of virtual, augmented, and mixed reality companies, announced the release of a white paper co-authored by the Digital Trade and Data Governance Hub at The George Washington University. “Reality Check: Why the U.S. Government Should Nurture XR Development”, compares what China, South Korea, the European Union, the United Kingdom, and the United States are doing to develop and deploy immersive technology (XR).

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How to Regulate AI? Start With the Data

We live in an era of data dichotomy. On one hand, AI developers rely on large data sets to “train” their systems about the world and respond to user questions. These data troves have become increasingly valuable and visible. On the other hand, despite the import of data, U.S. policy makers don’t view data governance as a vehicle to regulate AI.

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Could a Global “Wicked Problems Agency” Incentivize Data Sharing?

Could a Global “Wicked Problems Agency” Incentivize Data Sharing?

Global data sharing could help solve “wicked” problems (problems such as climate change, terrorism and global poverty that no one knows how to solve without creating further problems). There is no one or best way to address wicked problems because they have many different causes and manifest in different contexts. By mixing vast troves of data, policy makers and researchers may find new insights and strategies to address these complex problems. National and international government agencies and large corporations generally control the use of such data, and the world has made little progress in encouraging cross-sectoral and international data sharing. This paper proposes a new international cloud-based organization, the “Wicked Problems Agency,” to catalyze both data sharing and data analysis in the interest of mitigating wicked problems. This organization would work to prod societal entities — firms, individuals, civil society groups and governments — to share and analyze various types of data. The Wicked Problems Agency could provide a practical example of how data sharing can yield both economic and public good benefits.

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Building Trust in AI: A Landscape Analysis of Government AI Programs

Building Trust in AI: A Landscape Analysis of Government AI Programs

As countries around the world expand their use of artificial intelligence (AI), the Organisation for Economic Co-operation and Development (OECD) has developed the most comprehensive website on AI policy, the OECD.AI Policy Observatory.

Although the website covers public policies on AI, Aaronson found that many governments failed to evaluate or report on their AI initiatives. This lack of reporting is a missed opportunity for policy makers to learn from their programs (the author found that less than one percent of the programs listed on the OECD.AI website had been evaluated).

In addition, Aaronson found discrepancies between what governments said they were doing on the OECD.AI website and what they reported on their own websites. In some cases, there was no evidence of government actions; in other cases, links to government sites did not work. Evaluations of AI policies are important because they help governments demonstrate how they are building trust in both AI and AI governance and that policy makers are accountable to their fellow citizens.

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Building trust in digital trade will require a rethink of trade policy-making

Building trust in digital trade will require a rethink of trade policy-making small

In 2019, Shinzo Abe, then Prime Minister of Japan, stated that if the world wanted to achieve the benefits of the data-driven economy, members of the World Trade Organization should find a common approach to combining ‘data free flow with trust’. However, he never explained what these rules should look like and how nations might find an internationally accepted approach to such rules. In this paper, I argue that trade policy-makers must pay closer attention to users’ concerns if they truly want to achieve ‘data free flow with trust’. I begin with an examination of what the most recent digital trade/ecommerce agreements say about trust and discuss whether they actually meet user concerns. Next, I turn to three different examples of online problems that users have expressed concerns about, namely internet shutdowns/censorship, disinformation, and ransomware, describing how these may yield both trade distortions and less trust online. I argue that policy-makers should address these issues if they believe trade agreements should build trust in cross-border data flows. Moreover, I argue how policy-makers respond to user concerns is as important as what they include in trade agreements. Finally, I note that trade negotiators will need to rethink how they involve the broad public in digital trade policy-making, while recognizing that trade policy agreements may not be the best place to address these problems.

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Biden’s New AI Policy Falls Short on a Key Problem

Biden’s New AI Policy Falls Short on a Key Problem

The Biden administration’s new “Blueprint for an AI Bill of Rights” is simultaneously a big step forward and a disappointment. Released last week, the blueprint articulates a set of principles that could address some of the major concerns about artificial intelligence design and deployment. But policymakers will need to do more to achieve an elusive objective: trust in AI.

AI’s trust problems have been apparent for some time. In 2021, the National Institute for Standards published a paper explaining the relationship between artificial intelligence systems and the consumers and firms who use AI systems to make decisions. The AI user has to trust the AI system because of its complexity, unpredictability, and lack of moral or ethical capacity, changing the dynamic between user and system into a relationship. So if AI designers and deployers want AI to be trusted, they must encourage trustworthy behavior by the system as well as trust in the system.

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A Future Built on Data: Data Strategies, Competitive Advantage and Trust

In the twenty-first century, data became the subject of national strategy. This paper examines these visions and strategies to better understand what policy makers hope to achieve. Data is different from other inputs: it is plentiful, easy to use and can be utilized and shared by many different people without being used up. Moreover, data can be simultaneously a commercial asset and a public good. Various types of data can be analyzed to create new products and services or to mitigate complex “wicked” problems that transcend generations and nations (a public good function). However, an economy built on data analysis also brings problems — firms and governments can manipulate or misuse personal data, and in so doing undermine human autonomy and human rights. Given the complicated nature of data and its various types (for example, personal, proprietary, public, and so on), a growing number of governments have decided to outline how they see data’s role in the economy and polity. While it is too early to evaluate the effectiveness of these strategies, policy makers increasingly recognize that if they want to build their country’s future on data, they must also focus on trust.

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