This November gave me the opportunity to give talks and participate in scientific events throughout Québec.
I started in Montréal, with a seminar at ComSanté, the health communication research centre of Université du Québec à Montréal (UQAM), where I presented my recently published book on websites on eating disorders. While most media attention focused on controversial “pro-anorexia” contents, presented as an undesirable effect of online free speech, I made the point that this part of the webosphere is rather to be seen as a symptom of the effects of current transformations of healthcare systems under austerity policies. Cuts in public health spending encourage patients to be active, informed and equipped, but the resulting social pressure creates paradoxical behaviors and risk-taking.
Also in Montréal, I was invited to a discussion with economic journalist Diane Bérard on the growth and crisis of the collaborative economy. About 50 people attended the event, co-organised by co-working space L’Esplanade, OuiShare Montréal and the journal Les Affaires. Diane summarized the essentials of the event in a blog post just the day after, and noted six main points:
- The Uber case dominates discussions and divides the audience – though the collaborative economy is not (just) Uber.
- The discussion gets easily polarized – a result of the tension between commercial and non-commercial goals of the collaborative economy.
- We still know little of the business models of these platforms and the external factors that facilitate or hinder their success.
- Sharing is in fact a niche market – now probably declining after the first enthusiasms.
- The key issue for the future is work – its transformations, and how it is re-organizing itself.
- Collaborative principles advance even outside the world of digital platforms, and sometimes permeate more traditional sectors. The near future of collaboration are sharing cities.
Both online health communities and collaborative economy platforms thrive on digital data, and indeed the day after, I was invited to a round table at the Musée de la Civilisation in Québec town. What are they doing with our data? This was the question that we were asked to discuss with a public of 30-odd persons – fewer than expected due to heavy rain that day, but all highly interested. With Jacques Priol of Civiteo, Nantes (FR) and Prof. François Laviolette of Université Laval, Québec, we reviewed opportunities and threats, strengths and weaknesses of big data. Opportunities for finer knowledge and better-tailored predictions (for example, concerning electoral results – this was just a few days before Trump’s election in USA), and threats for individual liberties due to surveillance. Strength, from the new methods of analysis now available for large sets of (even unstructured) data – machine learning in particular – and weaknesses, due to noise and other issues in data quality, unrepresentative (though mostly not exhaustive) sampling, often scarce documentation.
The following days, we were at a science-and-society forum for college (pre-university) students, giving a workshop, again, on big data. The goal of the event (organised by ACFAS, a French-language cultural organization) was to connect students with science, which is why we focused more on the effects of big data in science than in the economy, society, law etc. After illustrating what big data is and how it can be used, we discussed at length how big data transform scientific practice in different domains of application – the social sciences, medicine, and engineering. Students found this fascinating, and were particularly interested in highly abstract questions – how big data and machine learning can train artificial intelligences, for example, and how these intelligences may compare to ours. They were mostly thinking of their future study choices and asked a number of technical questions, notably concerning machine learning. They were very attracted by the promises of big data, and a bit less concerned by the limitations – what they haven’t achieved so far, the epidemics they have failed to predict, the social and economic phenomena that classical “small” data still explain better. But they were interested in the economy – how value is created from data – and in the very discovery that mathematical and computational tools can be applied to study society – which obviously wasn’t previously known to them all.
My last talk was another presentation of my book on eating disorders and their online expression, this time at research centre Célat of Université Laval. A quite stimulating discussion with interesting colleagues.
Overall, a productive and interesting trip – and because all these events, except the two book presentations, were directed at non-academic publics, I also see it as a great experience in (social) science communication.
I acknowledge support from Consulat de France, Institut Français, ACFAS, UQAM, and Université Laval.