Finding: This paper proposes "second-order cognitive gadgets" - external structures that don't just support thinking but fundamentally reshape how we think - and argues that AI represents a contemporary example that's reconfiguring our collective mental processes.
Why it matters: This theoretical framework directly addresses how AI tools are transforming human cognition and collaboration, providing a lens for understanding technology's impact on learning, decision-making, and team dynamics.
Jargon: Cognitive gadgets = external tools that support thinking; Niche construction = how organisms modify their environment; Abductive reasoning = inference to the best explanation; Ontogenesis = development of an individual organism.
Finding: Proposes restructuring scientific papers with front-loaded narratives for humans paired with machine-readable "research-object packages" containing executable code and semantic annotations, enabling both human comprehension and automated synthesis while creating continuously updated evidence networks.
Why it matters: Directly addresses how AI is transforming scientific communication and collaboration, with implications for HCI design of research tools, behavioral science replication, and human-AI interaction in knowledge work.
Method: Theoretical proposal with specific structural recommendations for dual-audience paper design.
Jargon: Jingle-jangle fallacies = measurement problems where same labels describe different constructs or different labels describe same construct; research-object packages = structured, executable supplements containing code and semantic metadata.
Finding: This nationwide survey of Irish researchers found a significant gap between high awareness of Open Research Practices and actual adoption, with motivation (embedding practices into workflows) being the strongest predictor of adoption, followed by capability and opportunity.
Why it matters: The awareness-adoption gap and behavioral drivers identified here directly apply to understanding how researchers and practitioners adopt new HCI methods, collaborative tools, and evidence-based practices in design and behavioral science.
Method: Used the Brief Open Research Survey (BORS) and COM-B model of behavior change to systematically evaluate psychological and situational drivers of research practice adoption.
Jargon: COM-B model - framework analyzing behavior through Capability (skills/knowledge), Opportunity (external factors), and Motivation (internal drives).
Rena Beatrice Alcalay, Joachim Vandekerckhove • PsyArXiv
Finding: Open science practices, despite good intentions, create "epistemic disadvantage" - systematic harms to knowledge-producing communities that persist even within consensual data-sharing systems and cannot be resolved through better protocols alone.
Why it matters: This highlights critical ethical considerations for HCI researchers designing collaborative platforms and AI systems that aggregate human knowledge, showing how technical solutions may perpetuate structural inequities.
Jargon: Epistemic disadvantage = structural vulnerabilities in knowledge systems beyond direct injustice; epistemic extractivism = appropriation of knowledge resources without regard for originating community costs.