Can "Truth Decay" be reversed by Media and Information Literacy (MIL) ?

What can we expect from our global media literacy when at the press of a button the smoke in Ukraine spirals from ammonium nitrate storage explosion in Beirut, a Russian aircraft becomes an American-built F-16 Fighting Falcon, a Russian jet shot down by Ukraine is in reality a Libyan aircraft shot by the rebels over Benghazi in 2011, and in another shot, an explosion in Ukraine is simply no more than lightning striking on a power station? It is a facade, occurring right through our small screens, and we are expected to believe all that, adding to the other agendas that only few are cognizant of.

Under the covers of showing support to Ukraine on one side and condemning Russian regime on the other side, disinformation and misinformation continue to be spread on social media platforms, and the Russia-Ukraine current conflict is just a very simple example from the military field. There are other fields, such as the medical, political, economic, intellectual, and so on.. The scenario is the same: misinformation and disinformation invading our attention, activating consumption, and vigorously creating pools of disagreement and turbulence.

RAND corporation defines that in its 2018 book “Truth Decay”, as a set of four trends:

“1. Increasing disagreement about facts and analytical interpretations of facts and data

2. A blurring of the line between opinion and fact

3. The increasing relative volume, and resulting influence, of opinion and personal experience over fact

4. Declining trust in formerly respected sources of factual information.”

Literacy in the context of media first emerged as information and news literacy, information handled by librarians and news handled by journalists, and it was limited to word, visual (photos), audio (radios), and scientific literacy (analytical). However, these types of literacy have extensively stretched to include much more advanced forms, with the widespread of digital tools and devices.

Given the pervasive metadata, the ferocious demands for information exchange, and the conflicts clusters lurking in the background, false information can easily find way to our screens, and when it reaches certain parties or individuals with certain intentions to entertain or harm, it can be easily sent out with manipulating messages. This false or inaccurate information is referred to as misinformation, when it is shared widely, without deliberate harm or intent to deceive. This information is referred to as disinformation when it is shared in the same way, but with an intent to deceive, and most of the time, it is created for such a mischievous intent. Brian Southwell, Director at a nonprofit research institute RTI International, a social scientist, and a professor, explains more:"Disinformation is not a 21st century phenomenon. When you've got a lack of correct information, and an anxious population with a lot at stake, disinformation is going to flourish. When people are anxious and looking for answers, somebody is going to provide those answers and capitalize on it financially or politically."

However, the Debris?

Media and Information Literacy MIL is a reliable set of knowledge, attitudes and skills that can bridge gaps and sustain communities, but why does it remain to be less effective than what we expect?

1. Deconstruction vs. Construction: From the pedagogical perspective, media literacy education is much more complicated than before. When we discuss media within the classroom concept, we see technology increasing shifts in all fields and industries. SAMR model best explains it through “Substitution, Augmentation, Modification, Redefinition”, the framework to practice and assess the degree and depth of learners’ engagement in technology to empower learning. Limiting learners’ experiences to use technology through basic and above basic practices will always place learners in the deconstruction mode, an outdated mode which should shift to construction, that is full exploration for the purpose of creation. Creation entitles being active participants in the process, rather than simply consumers.

2. Stripped Metadata: Social media is mostly involved in stripping metadata from images and videos, and needless to say, Facebook, Twitter, and What’s App are already three of the most popular social networks in the world. With the absence of metadata or the original file, misinformation and disinformation are most likely to happen.

3. “Faking at a much deeper level”: Deepfake technology is an AI-generated content of realistic images and videos of people, people who do not exist in real life. This deepfake content has started to invade our society, creating non-existing people who express attitudes, share ideas, or even demonstrate an action, including indecent actions, wrapping our young generations in confusion and havoc, as these latter build their perspective of a world they live and participate in. This technology has tried to use celebrities and political figures to harm those figures and can also use personal contacts as subjects for this type of content, most of the time as forms of revenge. The level of understanding media in such cases is urged to exceed literacy.

4. Fast-checking the Fast-Checkers: Most of the time, it is obvious that a photo, video, or news is not accurate. However, there are other times when detecting inaccuracy is not possible, so resorting to fast-checkers is a practical method. While reliable websites, such Amnesty International Data Viewer, Deutsche Welle, and many others, are available to do the fast checking, more scrutiny through contextual critical thinking is always encouraged.

5. Beyond “supervised” and “unsupervised” Machine Learning: “Saving the best for last”, as it is simply said. Artificial Intelligence works mainly on “training data”, that meticulously and precisely labels large sets of data so that it can classify new data, i.e. that has not been identified or labeled. The other class of machine learning is the unsupervised data, the data that has not been identified or classified. “Users’” engagement on social media is analyzed in this case, and based on that, their credibility is detected. The critical point to stir here is beyond this “supervised” and “unsupervised” machine Learning. When we call for media and information literacy, it is our utmost duty to be neutral, that is unbiased regardless of labels and ideologies, and to be wise, that is sagacious in the way we see life, our low and high purposes of existence, “walking our talk”, and this is the core of my O.R.B.I.T.S. approach.

All this is not meant to shake trust because trust is a critical factor in media literacy, and conspiracy theories remain “theories”, unless proven otherwise. Media and information literacy is one of the most critical and vast topics to discuss in one article or through one discipline, but tracing out implications can at least shed the light on massive individual and collective concerns. The pivot point here is how to calibrate our understanding of media and information literacy MIL in a way that builds, not destroys cultures, lives, and economies. How can fabrications be reduced amidst the surge of AI ? How can we disseminate MIL benefits and best practices in a current world of trends, crisis, and illusions ?