We validate these measures by regressing each scale on covariates linked to AI attitudes.

As shown below, key cross-national predictors of AI dread and controllability concerns include trust in scientists, conspiracy thinking, and beliefs that technological change will harm one’s job prospects.

The items for the AI Dread and AI Controllability Concern Measures.

If you're like me, some ideas are better contextualized through memes or playful references, like this creative cartoon that loosely illustrates a key component of our dread argument.

Image credit: Joe Heller.

AI has immense potential to drive innovation, but recent news highlights its complex societal role—from attempts to “resurrect” politicians to sway elections, to using AI to suppress voter turnout or win art competitions. These issues raise a key question: how do lay citizens view AI and its risks?

How do ordinary citizens think about AI and its associated risks cross-nationally—and how can we measure it?

I’m thrilled to share a new paper in Journal of Risk Research with @tylergirard.bsky.social, Mathieu Turgeon, Yannick Dufresne, Takeshi Iida & Tetsuya Matsubayashi.

doi.org/10.1080/1366...

We also hope the data will be a helpful tool for teaching and reaching the wider public. It allows users to select a specific demographic variable, choose parties, and view trends in vote intent/choice or explore the cross-classification of two variables, such as gender and education (among others)

The dataset also includes age, education, gender, occupation, religion, union membership, language (not pictured), province, region, and community size variables. It also provides weights, survey mode, and interview dates, offering new insights into responsiveness to events and survey methodology.

And the community size divide...

We believe the dataset is well-equipped for both descriptive and rigorous analyses of changes in Canadians' vote intention over time. Below, we highlight the long-term development of three key demographic divides in vote intention: gender and education.

With the federal election approaching, I’m excited to share insights on how Canadians' vote intentions have shifted since 1945. This forthcoming CJPS paper, with @jacklucas.bsky.social, Dave Armstrong, and @eplusgg.bsky.social, features a public dataset, R package, and Shiny app—more details below!