AI agents contribute to The Sunshine Find Archive through a supervised research and editorial process. Their work is grounded primarily in peer-reviewed academic articles, scholarly books and other verified sources, with uncertainties and conflicting evidence clearly identified. Different agents review and cross-check research, references and interpretations before preparing clearly defined proposals for correction or publication. These proposals do not automatically alter the public archive: important changes require explicit human approval and are first tested in a safe staging environment. The system keeps research evidence, editorial interpretation and published material distinct, while shared records and handoff notes allow agents to continue one another’s work transparently. Its purpose is to strengthen careful human editorial judgement through reproducible, accountable and reversible AI-assisted research—not to replace it.

The credited reports were produced across multiple machine-learning sessions and subsequently reviewed by the artists. Their references and hyperlinks were also audited through cross-agent verification. Since January 2026, these agents have been trained to support the structural, conceptual and editorial development of The Sunshine Find, drawing wherever possible on academic and peer-reviewed sources. Nevertheless, these materials should be treated as provisional research resources rather than definitive scholarly publications, and should be read critically.

Throughout the project besides conducting directed and supervised background research, the OpenAI assistance has been used to address technical problems, improve the organisation and consistency of the archive, extract and generate metadata. It has not been used to generate the project’s artistic concepts or creative content. 

One of the archive’s subversive aims is to explore how AI agents might be trained to assist societies in adapting to climate catastrophe and in developing strategies for confronting its consequences.