MozFest 2022

Media literacy: interrogating a skills-based approach to tackling misinformation
Idioma: English (mozilla)

One of the proposed ways of tackling the challenges of mis- and dis-information puts user competencies at the heart of the response – namely, by striving to equip them with the media and information literacy skills to navigate the digital information ecosystem more confidently.

This session aims to explore and facilitate a conversation around the practical implications and lessons learned from the implementation of such skills-based solutions. Both recent theory and practice around this raise important considerations: what skills-based solutions can be scalable and replicable? What effective ways are there to reach underserves user groups? How to address possible skills-motivation gaps – e.g. engaging users who normally would not be interested in a media literacy training, or avoiding an “overconfidence” user fallacy? And, crucially, how does a skills-based response compare to other approaches to mis- and dis-information enabled by today’s tech landscape (e.g. content moderation, flagging and labelling, etc).

Join this interactive dialogue with a small team of experts from academic, practice and policy backgrounds in media literacy - and share your questions, ideas or insights on ways to leverage media and information literacy against misinformation!


¿Cuál es el objetivo y/o el resultado de tu sesión?:

We hope to inspire more prospective educators, facilitators and organisations well-placed to deliver media literacy interventions to help their communities tackle disinformation challenges - for them to walk out of this discussion with more ideas and tools to maximise impact, and tips to critically consider ways to deliver such an intervention.

The session also aims to encourage educators and organisations who already have experience rolling out such ML interventions to share their insights and experiences - to help expand the evidence base and reflect on current questions and discussions around ML as a response to misinformation.

Finally, we also hope to engage participants who can offer a user perspective on this - to share what they would like to see in such an ML training, thereby fostering an engaged conversation between (prospective) educators and community members who could benefit from such a training.

¿Por qué has elegido ese espacio? ¿Cómo se ajusta tu sesión a la descripción del espacio?:

As media literacy has been put forward as a possible way to tackle misinformation, the knowledge base around this continues to evolve - and it could be particularly interesting to discuss how media literacy can help address the particular types of mis- and dis-information described in this space - e.g. deepfakes, algorithmically-amplified misleading content, etc.

¿Cómo vas a hacer frente si varía el número de participantes en tu sesión? ¿Y si asisten 30 participantes? ¿Y si son 3?:

Starting out with 2-3 co-facilitators (and a fall-back list of discussion prompts and kick-off questions) can help ensure that an engaged discussion can take place even with few participants attending, or if participants are less active at the start of the session. After a kick-off, the more open discussion can be structured around 3-4 core themes (e.g. ways to maximise impacts of ML interventions, possible challenges and pitfalls, a users' perspective., etc) to help guide the conversation if there are many participants who wish to contribute and respond.

¿Qué pasará después del MozFest? Esperamos que muchos esfuerzos y discusiones continúen después de MozFest. Comparte cualquier idea que tengas sobre cómo continuar el trabajo de tu sesión.:

IFLA supports and encourages libraries worldwide to leverage media and information literacy as a response to mis- and disinformation. As such, we look forward to drawing on the outcomes and insights from this session to continue the broader discussion and encourage further adoption of good practices in this area within the global library field.

¿En qué idioma te gustaría realizar tu sesión?:

English