The current “fake news” crisis and attendant information disorders has taught us some valuable lessons, as information as we knew it has been weaponized by all sorts of third parties and rogue actors to undermine the trust in expert knowledge and professional journalism. Fake news does not happen in a vacuum and are not just due to the agency of individuals. They are part of a socially constructed information ecosystem, where social identity, cognitive biases, social norms and ideological partisan alignments contribute to an information-rich world view that accommodates and processes fake news together with news, data and docs.
In this context of digital use and misuse of information, media literacy is back in vogue, newly evolved as Media and Information Literacy (MIL). MIL is faced with undertaking a big challenge: facilitating the digital transition for renewed democratic societies as they undergo the dual pressures of big data and ubiquitous media.
It is not the role of MIL to guide people to the “truth” but to provide them with repertoires of solutions to master the texts and images that we deal with, to check their provenance and authenticity, and then help buttress critical thinking so as to enable good decision-making. We need to examine the types of disinformation people are exposed to and the factors that lead them to create or disseminate such toxic material.
The patterns for consuming and disseminating fraudulent information and warped perceptions of facts are revealing of how our minds work to construct, consume and contest politicized media discourses and events. Cross-cutting to the data-media nexus are human variables that force a kind of paradigm shift in MIL, inducing us to revisit some dimensions of knowledge-construction that we thought had been resolved since the pre-digital world.
Lesson 1: It’s about Emotions and Their Stickiness
We thought that literacy is about rational, explicit thought processes leading to knowledge-construction and decision-making. Fake news challenges this tenet by showing that we depend on the cognitive authority of others and on how we feel about them (in particular our trust in them). The first and second hand experience of others are key to our understanding and interpretation of facts and ideas. Education may influence us less than experience and the emotions that help us remember the valuable tidbits of information we need. The trust we put in our sources tints the way we learn and rely on information. So, our information literacy skills need to be explicitly attuned to the affective elements that cause us to lend cognitive authority to others, with a particular sensitivity to positive and negative emotions as they may be barriers to the search and use of proper information.
Lesson 2: It’s about Images and Their Immersiveness
We thought that knowledge-construction is mostly carried via text-based short and long narrative forms (stories, posts, tweets, comments) with images as mere add-ons. Fake news challenges this tenet by showing the power of image-driven content (memes, snaps, lives) on many types of screens. Images are no longer supports for texts; they take their own visual independence, especially with data visualization and immersive virtual reality. Their authenticity is encoded in image-quality characteristics that go beyond the legacy grammars of image design and storytelling (cut, edit, focus, frame, perspective, light and composition). Current ways of processing images, via computer-generated imagery and neuro-imaging, challenge the authenticity of the facts captured and published. So, our visual literacy skills are solicited to authenticate still and moving images to make decisions on the basis of how trustworthy they are. Assessing visual authenticity and its relation to “realness” – if not reality – also depends on the trust we put in the authority of the source and the emotions conveyed by tenuous visual elements such as lighting, contrast, camera angle together with imaging data as established by machine-learning models that can produce deepfakes, seamlessly modifying existing visuals, or immersive environments that make us lose our sense of time, space and body.
Lesson 3: It’s about the Brain and Its Artificial Intelligence
We thought that decision-making was a conscious process derived from the interactions between scripts, norms and practices in our neural systems. Fake news challenges this tenet by showing how algorithmic systems generate an artificial intelligence (AI) whose assemblage of data can nudge our decision-making in unexpected directions, including false ones built on our own cognitive biases as they are programmed in the algorithm. So, our algorithmic literacy skills require us to use algorithms critically to ensure that their recommendations and their automated decisions are based on authority of the sources and authenticity of the facts and of the evidence. Using such cyber organisms that mimic the brain to support decision-making and knowledge-processing also depends on the trust we put in the ubiquitous organizations and media consortia and platforms that construct such systems, and the amount of transparency and accountability that we are able to embed in them, especially as they tend to have a vested interest in producing fake news that generate traffic and profit.
Lesson 4: It’s about Communities and Their Engagement
We thought that media business models, including social media ones, were predicated on audience measures that could be marginally extended to community awareness metrics (impressions, views, clicks) and engagement metrics (likes, shares, comments). But fake news challenges this tenet, by showing that the so-called audiences proceed to individual acts of authentication based on group-belonging influence. The perceived credibility (veracity, accuracy) of news items and big data informs people’s strategies to authenticate the information they encounter on social media. Values, ideologies, emotions and connectedness are key factors to engage with others and this is being tracked by big data analytics that reveal patterns, trends and associations to profile people and predict their behavior. So, our engagement literacy skills should help us analyze controversial information and its partisan framings, so as to be able to produce means of countering disinformation in on-line and off line discussions. Challenging disinformation proactively goes hand in hand with decoding contentious issues crucial to our global human destiny such as climate change or migration based on evidence-based decision-making, especially as these issues are abundantly covered and commented on in mass and social media alike.
Taking stock of these four main lessons and their inter-connectedness requires a different political and pedagogical posture. As notions of authority, authenticity, transparency and credibility take center-stage in the way we construct information and knowledge, the very notion of literacy is displaced. The current situation requires a multi-faceted MIL that locates information literacy alongside visual literacy, algorithmic literacy and engagement literacy. And instead of positioning MIL as the 2nd curriculum, as an expendable addendum to the school curriculum that could be dealt with at best during a Media Week in schools and universities, we need to insist that MIL is becoming the 1st curriculum by default even if formal sites of education are still reticent to embrace it. If the move is not made, we will effectively find ourselves with MIL literati (data scientists and information brokers) that will be savvy users of information and disinformation and MIL illiterati (citizens at large) that will have spotty capacities to recognize the difference.
The current rampant state of illectronism may set the stage for massive methods for manipulation of the mind, beyond deception of the brain. Detection of altered perceptions and emotions is key to democratic processes that rely on the integrity of information and data (like the mere acts of voting and petitioning). The current tools are powerful enough to help us detect fake images and fake perspectives in synthetically-produced immersive visuals but they need to be put to the service of the community at large. The task is not easy, as the Youcheck! project shows: having a literati tool such as the media forensics plug-in INVID does not automatically translate into mass appropriation without the intervention of MIL strategies and repertoires of actions.1 Evaluating the success of interventions such as Youcheck! remains key to improving critical reflexivity on evidence-based research on MIL.
The contributions in the current volume provide us with examples and perspectives from around the world that address the intersection of new media, democracy and MIL. The breakdown in three sections – community engagement, critical thinking frames and pedagogical transformations – testifies to the multi-levels of articulation that are needed for MIL effectiveness. The chapters point to further examinations across various domains of literacy and across different groups of actors. Their various methodologies balance the different forms of intervention that are acceptable for MIL, be it action research, small-scale pilots or game-based practices.
As the consequences of disinformation on democratic societies are still hard to estimate, we can only hope that the critical changes brought about by effective MIL activities, at their various scales (macro and micro), will show beneficial impacts at political and societal levels. If our understanding of algorithms, brain processes, data patterns and social networks can produce citizens that are more aware of how to produce robust counter-discourses to climate change coverage, gender injustice or migrant crisis representations, then the societal utility of MIL to foster critical reception of information and disinformation in relevant information sources will be fully vindicated and so will be its contribution to Democracy 2.0.