Kasra Babashahiashtiani is a geography MA student under the supervision of Dr. Kean Birch, with whom he examines the economic geography of Canada’s AI ecosystem as part of an SSHRC-funded project titled “The changing dynamics of innovation in technoscientific capitalism”.
In 2017, the Government of Canada announced the Pan-Canadian National AI strategy and pledged $125 million to help Canada maintain its position as a leader in Artificial Intelligence (AI) research and development. Since then, the Canadian AI ecosystem has continued to receive significant investment from both the federal and provincial governments.
These investments are in no small part due to Canada’s vision of having a thriving, innovative digital economy and the potential AI has as general-purpose technology to revolutionize and transform various aspects of the economy. Along with AI’s positive impacts come potential threats and implications that can hinder the growth of Canada’s economy and even negatively affect people’s lives. The economies of scale from data and talent access, knowledge externalities such as the clustering of intellectual property and researchers, sources of investment, and public investment beneficiaries are some areas that require careful examination from a geographical perspective.
In his research, Kasra strives to address some of these concerns. He has implemented a mixed-methods approach, and through it, is examining the economic geography of AI from three perspectives. First, a critical discourse analysis of Canadian policy and government documents relating to the AI sector was conducted. This is necessary to fully comprehend the government’s perspective of the AI concept, its vision, and strategies for future development.
In the second part of the research, using SQL, Python, and CrunchBase’s data, he created a database of Canadian AI startups and their investors, mapping clusters of AI startups, tracing financial flows, and revealing the current state of the AI ecosystem. This is an important collection of information on the financial and data geographies in Canada's AI ecosystem, which can be used as a reliable source when making decisions about the AI sector.
The final part of the research includes interviews with senior and executive-level professionals to understand the decisions and reasoning that have led to the AI ecosystem’s current state. This close interaction with the leaders of the AI industry in Canada gives illuminating insights of the financial reality of these initiatives, which can be contrasted with the previous theoretical considerations.
Although the abundant advantages of AI technologies are becoming clearer, it is still necessary to discern its possible negative consequences. By highlighting some of the challenges the AI ecosystem faces, Kasra expects his research will help policymakers address those issues, make more informed decisions regarding the AI sector, and better harvest its potential.