False memories for true and false vaccination information form in line with pre-existing vaccine opinions.

Misinformation continually threatens efforts to control the COVID-19 pandemic, with vaccine misinformation now a key concern. False memories for misinformation can influence behavioural intentions, yet little is known about the factors affecting (false) memories for vaccine-related news items. Across two experiments (total n = 1481), this paper explores the effects of pre-existing vaccine opinions on reported memories for true and false news items. In Study 1, participants (n = 817) were exposed to fabricated pro- or anti-vaccine news items, and then asked if they have a memory of this news event having occurred. In Study 2, participants (n = 646) viewed true pro- or anti-vaccine news items. News items were more likely to be remembered when they aligned with participants' pre-existing vaccine beliefs, with stronger effects for pro-vaccine information. We conclude by encouraging researchers to consider the role of attitudinal bias when developing interventions to reduce susceptibility to misinformation.

Measuring the effects of misinformation exposure and beliefs on behavioural intentions: a COVID-19 vaccination study.

Misinformation has been a pressing issue since the beginning of the COVID-19 pandemic, threatening our ability to effectively act on the crisis. Nevertheless, little is known about the actual effects of fake news on behavioural intentions. Does exposure to or belief in misinformation about COVID-19 vaccines affect people's intentions to receive such a vaccine? This paper attempts to address this question via three preregistered experiments (N = 3463). In Study 1, participants (n = 1269) were exposed to fabricated pro- or anti-vaccine information or to neutral true information, and then asked about their intentions to get vaccinated. In Study 2, participants (n = 646) were exposed to true pro- and anti-vaccine information, while Study 3 (n = 1548) experimentally manipulated beliefs in novel misinformation about COVID-19 vaccines by increasing exposure to the information. The results of these three studies showed that exposure to false information about the vaccines had little effect on participants' intentions to get vaccinated, even when multiple exposures led them to believe the headlines to be more accurate. An exploratory meta-analysis of studies 1 and 3, with a combined sample size of 2683, showed that exposure to false information both supporting and opposing COVID-19 vaccines actually increased vaccination intentions, though the effect size was very small. We conclude by cautioning researchers against equating exposure to misinformation or perceived accuracy of false news with actual behaviours.

Social Media Responses to the Pandemic: What Makes a Coronavirus Meme Creative.

The current pandemic and the measures taken to address it, on a global scale, are unprecedented. Times of crisis call for creative solutions, and these are not reduced to the work of scientists or politicians. In everyday life, both in online and offline spaces, people use their creativity to make sense of the current situation, to cope with it, and to learn its lessons. Social media is a privileged space for mundane and participative creativity through the production and sharing of coronavirus Internet memes. In this article, we examine the creativity of such memes from a dedicated Reddit community. We ask, in particular, what makes a coronavirus meme creative and what this creativity tells us about the pandemic and popular understandings of it. To answer these questions, we use a triangulation of quantitative and qualitative methods by having 480 memes coded by three social media users for surprise, meaningfulness, elaboration, humor, and creativity and qualitatively analyzing those memes that score highly on each dimension. An interesting finding concerns the importance of elaboration and humor for the evaluation of creativity in the case of memes, above the more traditional criteria of surprise (proxy for novelty) and meaningfulness (proxy for appropriateness), perhaps a feature unique for Internet spaces. The article ends with reflections on what these findings tell us about creativity on social media more generally and the creative processes involved in the generation and reception of coronavirus memes in particular.

Uses of the Past: History as a Resource for the Present.

Collective memory has become an increasingly important topic in social and human sciences over the past thirty years. Beyond the interest for how we understand history, collective memory research has explored how the past has been used to defend certain understandings of the world (for instance nationalist ideologies), political actions (as in the case of intractable conflicts), or collective identities (particularly when they are seen as reflecting the historical 'essence' of a national group). That is, how the history is used as a resource for the present. However, theoretical conceptualisations have more directly focused on how collective memory is produced, and less so on how it is mobilised for the present. In this paper, we propose to review the main conceptualisation of collective memory in psychology - as social thinking, as social identity, and as sense-making - and how they more or less implicitly understand the relations between past and present. In a final section, we argue that representations of history have mainly been seen, in collective memory research, as a source of meaning for the present or as a way to position oneself in the current social field. In conclusion, we propose a third way of understanding the relations between past and present, considering collective memory to be both transformative of the present and prospective for the future.

In Defence of Machine Learning: Debunking the Myths of Artificial Intelligence.

There has been much hype, over the past few years, about the recent progress of artificial intelligence (AI), especially through machine learning. If one is to believe many of the headlines that have proliferated in the media, as well as in an increasing number of scientific publications, it would seem that AI is now capable of creating and learning in ways that are starting to resemble what humans can do. And so that we should start to hope - or fear - that the creation of fully cognisant machine might be something we will witness in our life time. However, much of these beliefs are based on deep misconceptions about what AI can do, and how. In this paper, I start with a brief introduction to the principles of AI, machine learning, and neural networks, primarily intended for psychologists and social scientists, who often have much to contribute to the debates surrounding AI but lack a clear understanding of what it can currently do and how it works. I then debunk four common myths associated with AI: 1) it can create, 2) it can learn, 3) it is neutral and objective, and 4) it can solve ethically and/or culturally sensitive problems. In a third and last section, I argue that these misconceptions represent four main dangers: 1) avoiding debate, 2) naturalising our biases, 3) deresponsibilising creators and users, and 4) missing out some of the potential uses of machine learning. I finally conclude on the potential benefits of using machine learning in research, and thus on the need to defend machine learning without romanticising what it can actually do.