Cases

Climate fiction — cli-fi — now occupies a distinct literary genre with real influence on public perception of the ecological crisis. Authors face a recurring tension: should narrative power trump data fidelity, or must fiction stay tethered to the peer-reviewed record? Proponents of emotional primacy argue that the grief, wonder, and moral urgency a story generates are more likely to move readers to action than any confidence interval. A character losing her coastal village to rising waters may spark deeper engagement than an IPCC summary. 'Accurate enough' may be sufficient — what matters is that readers feel the stakes. Proponents of scientific fidelity counter that cli-fi with inaccurate timelines, exaggerated collapse scenarios, or misrepresented mechanisms undermines public trust. It enables bad-faith critics to dismiss the genre as alarmist, and risks distorting public understanding of which interventions actually work. Hopeful storylines built on currently non-existent technologies may generate false comfort rather than genuine agency. This question carries particular weight for educators and writers reaching younger audiences — and for institutions like residencies and MFA programs deciding what responsibility to build into craft curricula. It also sits at the heart of what 'hopeful dystopia' as a genre owes its readers.

As AI-driven hiring tools become widespread — from resume parsers and skill assessments to automated video interview analysis — job candidates are increasingly evaluated by systems they cannot interrogate. Proponents argue these tools reduce bias and improve efficiency; critics warn of opaque black-box decisions that candidates cannot meaningfully appeal or even know about. This trial asks whether transparency mandates — requiring employers to disclose the use of AI in hiring decisions — should be legally required.