The Digital Trade and Data Governance Hub

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Details: The BRICS countries – Brazil, Russia, India, China, and South Africa – play an increasingly important role in the global digital economy. With forty percent of the world’s population and twenty-five percent of global GDP, these nations  contribute to the digital economy supply chain from data  and chips to algorithms and telecommunications infrastructure. These nations practice digital sovereignty — a widely misunderstood term, and their conceptions, narratives, and initiatives of digital sovereignty remain understudied. This volume is the first to explore digital sovereignty from a multi-country Global South perspective. It tackles a wide range of digital sovereignty topics and varied methodologies. Please join us as we define and discuss digital sovereignty in the BRICS.

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The Digital Trade & Data Governance Hub provide resources, training, events, and evidence-based research to help stakeholders understand data governance and digital trade.

research

Evidence based Research

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Recent Publications

Trump 2.0: Clash of the tech bros

December 11, 2024 The tech giants courting Trump administration officials have conflicting interests. Getty Images In 2016, tariff man couldn’t care less about tech. Newly elected U.S. President Donald J. Trump knew that the people who created and ran America’s tech...

The Age of AI Nationalism and Its Effects

September 30, 2024 Policy makers in many countries are determined to develop artificial intelligence (AI) within their borders because they view AI as essential to both national security and economic growth. Some countries have proposed adopting AI sovereignty, where...

AI could become the ‘new steel’ as overcapacity risk goes unnoticed

July 24, 2024 Policymakers in the U.S., Saudi Arabia, Japan, the U.K., and the EU have announced huge public investments in artificial intelligence, which follow large private sector investments. Hu Guan – Xinhua – Getty Images In the 19th century,...

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.

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.

How should we think about data?

We have little information about what data firms collect, how these firms use or sell our data, or how they mix various data types. If we want these markets to operate more equitably and efficiently, policymakers must focus on the governance of data.

Personal Data

e.g. birthdates

 

Proprietary or Confidential Business Data

e.g. payrolls

Public Data

Data in the public domain, census data, scientific data, etc

Metadata

Supposedly anonymized personal data

Machine to Machine Communication

Satellite Data

Wondering who we are?

We are a team with a diverse background in international trade, international affairs, economics, public policy, and communication.

Susan Aaronson

Founder & Director

Michael D. Moreno

AI and Data Governance Research Associate