Technology Tensions with China

As a superpower deeply integrated in global supply chains, China is becoming an economic giant, but its use of technology to capture data with methods that may pose cyber- and national security risks is raising concerns. While some view China’s motivations as an attempt to advance its status from an upper-middle-income economy to a developed economy, others see more nefarious intentions behind its authoritarian, top-down governance model.

Further complicating the situation is the growing competition between China, the United States and Europe over the control of data, the technologies that use it and the values determining how it is used. Alex He and Robert Fay report on CIGI’s second annual conference on Digital Governance in China, where participants explored these and other issues related to the global implications of China’s governance model in the digital age.

On January 13, Taiwanese voters went to the polls to elect a new president and parliament following a three-way, high-stakes race. Reports of social media interference by China, alongside other forms of direct pressure, raised the key question: Is Taiwan’s democracy in danger? And how can the impact of interference be assessed in “this world of grey-zone tactics and unclear causal chains”?

In their analysis, Chung-min Tsai and Yves Tiberghien look at some of the mechanisms of manipulation and lines of defence that were active during the election, noting that despite the “highly disruptive environment” in which Taiwan’s democracy operates, “its institutions and voters have shown tremendous resilience in 2024.”

Half the world’s population goes to the polls in 2024. This is the third in a series of commentaries from CIGI created in partnership with the Centre for the Study of Democratic Institutions at UBC to explore the intersection of technology with the most pivotal among these elections.

Although artificial intelligence (AI) technologies are clearly facilitating scientific breakthroughs, their opacity challenges long-standing conceptions of how researchers conduct rigorous science.

The companies creating generative AI often tout the outputs of their models but say little about how they built them. Without further information about these models and their underlying data sets, outside researchers cannot test these models for reliability or trustworthiness — nor easily improve generative AI models. But as Susan Ariel Aaronson and Dhanaraj Thakur write, some recent changes are signalling that AI developers and policy makers are beginning to recognize the importance of greater transparency and reproducibility.

The Digital Policy Hub at CIGI is a collaborative space for emerging scholars and innovative thinkers from the social, natural and applied sciences. Here are the latest working papers from Hub fellows:

Ori Freiman: “CBDC Governance: Programmability, Privacy and Policies”

Mahatab Uddin: “Patent as a Tool for Facilitating Innovation: Lessons from Green Technology”

Follow the links on the Hub webpage to find out more about the Hub scholars and their work!

“More than a century ago, economist Joseph Schumpeter hypothesized that creative destruction — the process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one — is driven by entrepreneurs. If that’s true, Canada needs to get better, quickly, at transforming leading research into digital businesses. Our future prosperity depends on it.”

Despite Canada’s impressive R&D record, the country ranks fourth among G7 countries in terms of ease of doing business. Patricia Meredith writes that beyond the hurdle of bureaucratic red tape, “our financial institutions — accounting, banking and financing — have made life even more difficult for entrepreneurs because they have not kept up with the digital revolution.” It’s time, Meredith says, for an institutional renewal.