Reposted by Laurence Dierickx
We present a typology of traps to avoid:
1. Believing that AI systems are minds
2. Believing that AI systems are theories
3. Believing that cognitive science can be automated.
Learn to recognise and avoid these traps. Failure to avoid leads to numerous problems.
![Abstract
This chapter argues the concept of critical Al literacy as a necessary corrective to prevailing industry-driven frameworks of Al literacy that emphasises tool use, efficiency, and job- readiness. While mainstream Al literacy often treats artificial intelligence as a set of neutral technologies to be mastered, critical Al literacy situates Al as a sociotechnical assemblage shaped by political, economic, environmental, and cultural forces. It highlights the need to interrogate the assumptions embedded in the very term "artificial intelligence", to resist technodeterminism [1] narratives, to situate AI within larger sociocultural discourses, and to prepare all stakeholders to recognise when refusal or resistance to Al is both valid and necessary. Drawing on media, data, digital, and civic literacy frameworks, the chapter outlines the core principles of critical Al literacy: understanding the limitations of AI systems, awareness of epistemic injustice, recognition of human agency, attention to power asymmetries in Al development, acknowledgement
of AI as a complex assemblage, and awareness of critical Al literacy as an active practice. The chapter further examines the need for critical Al literacy across educational institutions, industry, civil society, and policymaking. By re-centring human values and challenging technodeterminism, critical Al literacy enables communities to interrogate,
resist, and reshape the role of Al in society.](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:pexpsn7wwmadrpcb6hqpeskx/bafkreifvn2ui2jov3rbboxalecny3v5eid7epkj42ehoo7rwzb2vxr3h2i)
