The Centre for International Governance Innovation (CIGI, pronounced "see-jee") is an independent, non-partisan think tank on global governance. CIGI supports research, forms networks, advances policy debate and generates ideas for multilateral governance improvements. CIGI's interdisciplinary work includes collaboration with policy, business and academic communities around the world. Until September 2014, CIGI was headquartered in the former Seagram Museum in the uptown district of Waterloo, Ontario. It is now situated in the CIGI Campus, which also houses the CIGI Auditorium and the Balsillie School of International Affairs (BSIA).
The modern Canadian intelligence system began with an internal debate at the end of World War II to decide on peacetime intelligence needs. The system evolved during the first two decades of the Cold War and laid foundations that proved both enduring, particularly in a Canadian emphasis on signals intelligence as a contribution to vital allied partnerships, and problematic in a secretive organizational structure that was distanced from the center of official decision-making in Ottawa. Foundational elements persevered into the twenty-first century but have been fundamentally altered by changes to the Canadian intelligence system, its governance, and its role. These changes have been propelled in large part by the emergence of new threats to security, first from global terrorism and subsequently from new geopolitical fractures and the rise of transnational threats.
Despite having highly similar economies, in banking the experience of the crisis-prone United States contrasts starkly with Canada’s stability.For each major US crisis, different reasons have been put forward to explain Canada’s comparative stability in the face of broadly similar shocks, an issue that arose again in the context of the failure of Silicon Valley Bank and its aftermath.This Commentary examines whether there is a unifying explanation for these contrasting outcomes and what this implies for Canada’s future financial sector stability. It identifies the changes introduced in the 1890 and 1900 Bank Act revisions that led Canada to manage banking sector problems in a cooperative arrangement between the banks and the authorities. The aim was to address the externalities generated by bank failures while controlling the resultant moral hazard through social networks rather than market discipline.Importantly, the system ensured enough competition to be efficient. Drawing on this comparative analysis, the Commentary considers the lessons to be drawn for future financial regulation.
Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "frontier AI" models: highly capable foundation models that could possess dangerous capabilities sufficient to pose severe risks to public safety. Frontier AI models pose a distinct regulatory challenge: dangerous capabilities can arise unexpectedly; it is difficult to robustly prevent a deployed model from being misused; and, it is difficult to stop a model's capabilities from proliferating broadly. To address these challenges, at least three building blocks for the regulation of frontier models are needed: (1) standard-setting processes to identify appropriate requirements for frontier AI developers, (2) registration and reporting requirements to provide regulators with visibility into frontier AI development processes, and (3) mechanisms to ensure compliance with safety standards for the development and deployment of frontier AI models. Industry self-regulation is an important first step. However, wider societal discussions and government intervention will be needed to create standards and to ensure compliance with them. We consider several options to this end, including granting enforcement powers to supervisory authorities and licensure regimes for frontier AI models. Finally, we propose an initial set of safety standards. These include conducting pre-deployment risk assessments; external scrutiny of model behavior; using risk assessments to inform deployment decisions; and monitoring and responding to new information about model capabilities and uses post-deployment. We hope this discussion contributes to the broader conversation on how to balance public safety risks and innovation benefits from advances at the frontier of AI development.
Today, globalization is under attack with calls for reshoring, nearshoring and friendshoring (aka allyshoring) as well as related calls for decoupling and derisking. This paper explores the economics of the various “shorings” and the implications for supply chain organization of the new supply chain politics that has emerged in response to supply disruptions during the pandemic and because of sanctions, export restrictions and import sourcing restrictions related to geopolitical developments. While the issue that triggered supply chain politics in the first instance – the pandemic-related supply chain disruptions to production – has moved into the background as the “made in the world” production system generally responded well to the shocks, the geopolitical contest over foundational technologies is keeping supply chain politics in the spotlight. The major risk now is that politically motivated supply chain restructuring implies potentially significant costs to the public purse, both in terms of subsidizing restructuring and offsetting ongoing efficiency costs, even as the rapidly changing factual situation tends to invalidate the narratives on which politics is based. Moreover, weaponization of supply chains to extract likely transient advantages in developing critical technologies raises much larger risks in driving confrontation in the longer term.
