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TRUVACE RECORD VERSION
record: TRV-2026-0928
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-30T14:14:28.964623Z
status: published
lens: g_space
sector: science
headline: ARTIFICIAL INTELLIGENCE AND THE FUTURES TURN: an anticipatory infrastructure for qualitative methods
dek: In this article, I focus on artificial intelligence (AI) in a social science futures research agenda. This agenda is proposed in response to a contemporary context where global future uncertainties are generating a futures knowledge market increasingly populated by the promise of faster and scaled-up AI foresight. Acknowledging the possibilities offered by technological and interactional focuses in developing AI methods, I turn to reflexively discuss the “side effects” of using AI methods in qualitative futures-…
gain_title: Generative AI offers faster and scaled-up foresight that can serve as anticipatory infrastructure for imagining possible futures and foresight solutions.
problem_title: (none)
trace_subject: (none)
gain_reading: Generative AI offers faster and scaled-up foresight that can serve as anticipatory infrastructure for imagining possible futures and foresight solutions.
gain_evidence: promise of faster and scaled-up AI foresight | AI as an anticipatory infrastructure through which international organizations imagine possible futures and possible foresight solutions
problem_reading: (none)
problem_evidence: (none)
quick_read: On 2025-10-14, a peer-reviewed article in Qualitative Research in Psychology proposed a social science futures research agenda centered on artificial intelligence. The author describes a contemporary market for futures knowledge driven by promises of faster, scaled-up AI foresight, and examines Generative AI as an anticipatory infrastructure through which international organizations imagine futures, participants engage with dominant visions, and researchers imagine future methods.

This matters because it positions AI not just as a tool but as infrastructure shaping how futures are imagined and studied in the social sciences. What remains uncertain is how the noted side effects of AI methods in qualitative team research manifest in practice, and whether the promised speed and scale translate into robust qualitative insight without undermining reflexivity. The article is conceptual and agenda-setting rather than reporting measured outcomes. The two summary paragraphs must be distinct from the title, statements, main points, rundown, and each other. Paragraph one explains what happened; paragraph two explains why it matters and what remains uncertain.
limitation: 
tag: Evidence-backed gain
key_points: Article proposes a social science futures research agenda in response to global future uncertainties and a growing futures knowledge market. | Examines Generative AI as anticipatory infrastructure used by international organizations to imagine possible futures and foresight solutions. | Focuses on qualitative methods, including how research participants can critically engage with dominant futures visions and how researchers imagine future methods.
rundown: The source frames the current context as global future uncertainties generating a futures knowledge market increasingly populated by AI foresight promises. It acknowledges both technological and interactional focuses in developing AI methods.

It then turns to a reflexive discussion of side effects in qualitative futures-focused team research, and analyzes three roles for Gen AI as anticipatory infrastructure: for international organizations imagining futures, for participants engaging with dominant visions, and for researchers imagining future methods.
sources:
- peer_reviewed | Qualitative Research in Psychology | https://doi.org/10.1080/14780887.2025.2570167 | 2025-10-14
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