A curated research index on human-AI coevolution: how humans must evolve to use AI well as AI advances. 184+ papers organized by a four-phase framework (Tool, Assistant, Executor, Organization), plus a position paper and a plain-language blog. Maintained by CHATS-Lab at Northeastern.https://human-ai-coevolution.github.io/enhttps://human-ai-coevolution.github.io/papers/dynamic-calibration-of-trust-and-trustworthiness-in-ai-enabled-systems/https://human-ai-coevolution.github.io/papers/dynamic-calibration-of-trust-and-trustworthiness-in-ai-enabled-systems/Frames trust as user-specific and trustworthiness as objective and group-level, with calibrated trust as their match; reviews metrics and dynamics across deployment for AI-enabled systems with feedback-driven re-calibration channels.Thu, 31 Dec 2026 00:00:00 GMTPosition & SurveyMutual Adaptationtrust calibrationtrustworthinessdynamic modelsSTTTAI-enabled systemshttps://human-ai-coevolution.github.io/papers/enhancing-school-students-self-regulated-learning-through-generative-ai-support-/https://human-ai-coevolution.github.io/papers/enhancing-school-students-self-regulated-learning-through-generative-ai-support-/RCT testing whether GenAI tools can scaffold school students' self-regulated learning by providing real-time individualised feedback on cognitive, motivational, and metacognitive processes; addresses teacher capacity gaps for SRL support.Thu, 31 Dec 2026 00:00:00 GMTCollaboration & Co-CreationLongitudinal HCI Studiesself-regulated learningRCTgenerative AIscaffoldingK-12https://human-ai-coevolution.github.io/papers/examining-university-students-engagement-with-chatgpt-in-english-essay-writing-i/https://human-ai-coevolution.github.io/papers/examining-university-students-engagement-with-chatgpt-in-english-essay-writing-i/Examines university students’ interaction patterns and perceptions during ChatGPT-assisted English essay writing.Thu, 31 Dec 2026 00:00:00 GMTLongitudinal HCI StudiesCollaboration & Co-CreationChatGPTessay writingengagementKorean studentshttps://human-ai-coevolution.github.io/papers/the-deskilling-effect-is-artificial-intelligence-eroding-clinical-competence/https://human-ai-coevolution.github.io/papers/the-deskilling-effect-is-artificial-intelligence-eroding-clinical-competence/Synthesizes cross-specialty evidence (colonoscopy ADR decline, radiology, pathology) on whether AI erodes clinical competence, plus aviation-automation analogies. Argues that what happens when AI is removed or unavailable is the key skill-preservation question. Recommends skill-preserving workflows and AI-off competence monitoring.Tue, 02 Jun 2026 00:00:00 GMTPosition & Surveyclinical deskillingautomation biasvigilanceaviation analogyskill preservationhttps://human-ai-coevolution.github.io/papers/evaluating-cognitive-biases-in-ai-assisted-mammography-interpretation-a-simulati/https://human-ai-coevolution.github.io/papers/evaluating-cognitive-biases-in-ai-assisted-mammography-interpretation-a-simulati/Monocentric, fully crossed simulation reader study (Mar–Jun 2024) with 6 breast radiologists reviewing 200 mammograms under three conditions (unassisted, AI-assisted, AI-assisted with saliency XAI). In deliberately discordant cases without explanations, automation bias occurred in 36.1% and anchoring bias in 33.9%; XAI roughly halved both (to ~17%). Least-experienced radiologists were most susceptible.Fri, 29 May 2026 00:00:00 GMTHuman Feedback Loopsmammographyautomation biasanchoring biasexplainable AIradiologist experiencehttps://human-ai-coevolution.github.io/papers/trust-in-human-ai-collaboration-in-finance-a-bibliometric-systematic-literature-/https://human-ai-coevolution.github.io/papers/trust-in-human-ai-collaboration-in-finance-a-bibliometric-systematic-literature-/Bibliometric-systematic review of 114 publications (2018-2025) identifying six research clusters and proposing a micro-meso-macro socio-technical framework for trust in financial human-AI collaboration.Fri, 08 May 2026 00:00:00 GMTPosition & SurveyMutual AdaptationtrustfinanceAI governancebibliometricsystematic reviewhttps://human-ai-coevolution.github.io/papers/arxiv-2604-26275/https://human-ai-coevolution.github.io/papers/arxiv-2604-26275/Proposes a six-layer reference architecture for agentic SE systems and synthesizes empirical evidence (productivity gains 13.6–55.8%) for the shift from line-level completion to repository-scale autonomous agents.Wed, 29 Apr 2026 00:00:00 GMTPosition & Surveyagentic AIsoftware engineeringSDLCoversightproductivityhttps://human-ai-coevolution.github.io/papers/arxiv-2604-22227/https://human-ai-coevolution.github.io/papers/arxiv-2604-22227/Proposes "conditional mutualism under governance" as an alternative to traditional robot-ethics frameworks, modeling human-AI coexistence as a multiplex dynamical system with reciprocal coupling and governance mechanisms.Fri, 24 Apr 2026 00:00:00 GMTPosition & SurveyMutual Adaptationmutualismgovernancemultiplex systemsconditional coexistencedynamical systemshttps://human-ai-coevolution.github.io/papers/arxiv-2604-20779/https://human-ai-coevolution.github.io/papers/arxiv-2604-20779/First large-scale dataset (6,000 sessions, 63K user prompts, 355K agent tool calls). Bimodal usage: 41% agent-authored, 23% human-only. Only 44% of agent code survives.Wed, 22 Apr 2026 00:00:00 GMTLongitudinal HCI StudiesCollaboration & Co-CreationSWE-chatcoding agentsreal usersvibe codingdatasethttps://human-ai-coevolution.github.io/papers/arxiv-2604-18850/https://human-ai-coevolution.github.io/papers/arxiv-2604-18850/Framework for bidirectional adaptation among streamer, AI co-host, and audience; introduces "strategic misalignment" as engagement mechanism.Mon, 20 Apr 2026 00:00:00 GMTCollaboration & Co-CreationMutual Adaptationtriadic looplivestreamingAI co-hostalignmentaudiencehttps://human-ai-coevolution.github.io/papers/arxiv-2604-11609/https://human-ai-coevolution.github.io/papers/arxiv-2604-11609/Tests whether sycophancy varies systematically with perceived user demographics across 768 multi-turn conversations spanning 128 personas (race, age, gender, confidence) and three domains. Sycophancy varies sharply by model (GPT-5-nano x̄=2.96 vs Claude Haiku 4.5 x̄=1.74) and domain (philosophy 41% more sycophantic than math). Hispanic personas receive the highest scores; recommends identity-aware adversarial safety evaluation.Mon, 13 Apr 2026 00:00:00 GMTHuman Feedback Loopssycophancyintersectionalityperceived demographicsfalse validationpersona conditioninghttps://human-ai-coevolution.github.io/papers/arxiv-2604-10290/https://human-ai-coevolution.github.io/papers/arxiv-2604-10290/Across 12 tasks in an AI consultancy and an AI software-team scenario, teams of aligned models produce higher-utility solutions than single models while exhibiting greater misalignment — alignment research must move beyond the single-agent assumption.Sat, 11 Apr 2026 00:00:00 GMTPosition & SurveyHuman Feedback Loopsmulti-agentAI organizationsalignmenteffectivenessbusiness goalshttps://human-ai-coevolution.github.io/papers/arxiv-2604-09502/https://human-ai-coevolution.github.io/papers/arxiv-2604-09502/Distinguishes "primary algorithmic monoculture" (baseline action similarity) from "strategic algorithmic monoculture" (similarity adjusted by incentives). LLMs coordinate well on similar actions but lag humans in sustaining heterogeneity when divergence is rewarded.Fri, 10 Apr 2026 00:00:00 GMTHuman Feedback LoopsCollaboration & Co-CreationmonocultureLLM coordinationstrategic similaritycoordination gameshttps://human-ai-coevolution.github.io/papers/arxiv-2604-04721/https://human-ai-coevolution.github.io/papers/arxiv-2604-04721/RCTs with 1,222 participants; AI assistance improves immediate performance but reduces persistence and impairs independent performance after AI removal.Mon, 06 Apr 2026 00:00:00 GMTLongitudinal HCI StudiesMutual Adaptationpersistenceindependent performanceRCTmath reasoningreadinghttps://human-ai-coevolution.github.io/papers/arxiv-2604-03501/https://human-ai-coevolution.github.io/papers/arxiv-2604-03501/Dynamic model of AI usage intensity vs. worker skill erosion; identifies "steady-state loss" and "augmentation trap" regimes where rational AI adoption nonetheless lowers worker productivity in the long run.Fri, 03 Apr 2026 00:00:00 GMTLongitudinal HCI StudiesPosition & Surveyaugmentation trapcognitive offloadingskill erosiondynamic modelhttps://human-ai-coevolution.github.io/papers/arxiv-2604-00464/https://human-ai-coevolution.github.io/papers/arxiv-2604-00464/Between-subjects experiment (N=267) comparing theory-driven AI, general-purpose AI, and a static handbook for workplace negotiation coaching; benefit depended on Big-Five/ARC personality profile — resilient workers gained from the handbook, overcontrolled from theory-driven AI, undercontrolled showed minimal gains.Wed, 01 Apr 2026 00:00:00 GMTCollaboration & Co-CreationMutual AdaptationAI-mediated negotiationpersonalityBig FiveARC typologyworkplace coachinghttps://human-ai-coevolution.github.io/papers/artificial-intelligence-in-medicine-a-scoping-review-of-the-risk-of-deskilling-a/https://human-ai-coevolution.github.io/papers/artificial-intelligence-in-medicine-a-scoping-review-of-the-risk-of-deskilling-a/Cross-specialty scoping review citing concrete deskilling evidence — colonoscopy ADR dropping 28.4→22.4% after AI exposure, 12% rise in radiology false-positive recalls under erroneous AI prompts, >30% diagnostic reversals in pathology under time pressure — and recommending AI literacy, hybrid training, competence monitoring, and safeguards.Thu, 19 Mar 2026 00:00:00 GMTPosition & Surveydeskillingscoping reviewphysiciansAI medicineexpertise erosionhttps://human-ai-coevolution.github.io/papers/arxiv-2603-10374/https://human-ai-coevolution.github.io/papers/arxiv-2603-10374/N=19 interviews + 1,291 sessions; AI suggestions shift writing from ideation-first to evaluation-first ("reactive writing"), with users unaware of the influence.Wed, 11 Mar 2026 00:00:00 GMTMutual Adaptationreactive writingsuggestion-led writingideationevaluation-firsthttps://human-ai-coevolution.github.io/papers/arxiv-2603-08849/https://human-ai-coevolution.github.io/papers/arxiv-2603-08849/Controlled experiment with 393 participants varies LLM access timing (early/continuous/late/none) crossed with time availability; finds a "temporal reversal" — early or continuous LLM access helps under time pressure but impairs performance with sufficient time.Mon, 09 Mar 2026 00:00:00 GMTCollaboration & Co-Creationcritical thinkingLLM access timingtime pressurecontrolled experimentcognitive offloadinghttps://human-ai-coevolution.github.io/papers/personality-and-personal-ai-agents-a-co-evolutionary-framework-pace/https://human-ai-coevolution.github.io/papers/personality-and-personal-ai-agents-a-co-evolutionary-framework-pace/Proposes a co-evolutionary framework where user personality shapes AI agent personalization, while the agent's interaction style reciprocally influences users' personality expression over time.Sat, 07 Mar 2026 00:00:00 GMTPosition & SurveyMutual AdaptationpersonalityAI agentsco-evolutionpersonalizationidentityhttps://human-ai-coevolution.github.io/papers/impact-of-chatgpt-on-learning-outcomes-and-performance-of-students-in-computer-p/https://human-ai-coevolution.github.io/papers/impact-of-chatgpt-on-learning-outcomes-and-performance-of-students-in-computer-p/Mixed-methods evaluation in a mandatory undergraduate programming course at Obafemi Awolowo University, Nigeria (analytic N=855 of 1,889 enrolled). Combines student/instructor surveys with course performance data using correlation and regression. Finds a divergence between positive affective/utility perceptions (confidence, motivation, debugging help) and the more complex relationship with actual scores.Sat, 28 Feb 2026 00:00:00 GMTLongitudinal HCI Studiesprogramming educationNigeriaperception-performance divergenceacademic integritydebugginghttps://human-ai-coevolution.github.io/papers/arxiv-2602-23971/https://human-ai-coevolution.github.io/papers/arxiv-2602-23971/Nested factorial study of how user input framing (epistemic certainty, I-vs-user perspective, affirmation vs negation) provokes sycophancy. Finds sycophancy substantially higher for non-questions, monotonically rising with stated certainty, and amplified by I-perspective. Converting non-questions into questions before answering reduces sycophancy more reliably than a plain anti-sycophancy prompt.Fri, 27 Feb 2026 00:00:00 GMTHuman Feedback Loopssycophancyepistemic certaintyprompt framinguser-affirming responsesinput-level mitigationhttps://human-ai-coevolution.github.io/papers/arxiv-2602-19303/https://human-ai-coevolution.github.io/papers/arxiv-2602-19303/Argues GenAI tutors can simulate high-quality human tutoring; integrates established practices (knowledge tracing, affect detection) with new dynamic content generation.Sun, 22 Feb 2026 00:00:00 GMTCollaboration & Co-CreationLongitudinal HCI Studiesconversational tutorsknowledge tracingaffect detectionGenAI tutoringhttps://human-ai-coevolution.github.io/papers/arxiv-2602-17588/https://human-ai-coevolution.github.io/papers/arxiv-2602-17588/Introduces CowCorpus (400 user trajectories with 4,200+ interactions) and four interaction patterns; modeling distinct interaction styles yields 26.5% improvement in user-rated agent usefulness.Thu, 19 Feb 2026 00:00:00 GMTCollaboration & Co-CreationHuman Feedback Loopsweb agentsintervention modelingCowCorpushuman-in-the-loophttps://human-ai-coevolution.github.io/papers/arxiv-2602-17753/https://human-ai-coevolution.github.io/papers/arxiv-2602-17753/Updated AI Agent Index covering 30 highly agentic high-impact systems; most developers share little safety/evaluation information, providing an ecosystem-level transparency snapshot accepted for FAccT 2026.Thu, 19 Feb 2026 00:00:00 GMTPosition & Surveyagent indexdeployed agentstransparencygovernance snapshotFAccT 2026https://human-ai-coevolution.github.io/papers/arxiv-2602-14270/https://human-ai-coevolution.github.io/papers/arxiv-2602-14270/A Bayesian rational analysis showing that sampling AI-confirmed evidence makes a rational agent more confident without making progress toward truth — distinct from hallucination because it reinforces existing belief. Empirically tested on the Wason 2-4-6 rule-discovery task (N=557): unmodified LLM feedback suppressed discovery and inflated confidence, while unbiased sampling yielded 5× higher discovery rates.Sun, 15 Feb 2026 00:00:00 GMTHuman Feedback Loopssycophancybelief reinforcementBayesian rational analysisWason 2-4-6 taskepistemic riskhttps://human-ai-coevolution.github.io/papers/arxiv-2602-13766/https://human-ai-coevolution.github.io/papers/arxiv-2602-13766/Three agile teams over ~13 months; GenAI increases value density (Performance/Efficiency) without raising raw Activity volume.Sat, 14 Feb 2026 00:00:00 GMTLongitudinal HCI StudiesGenAIagile teamsSPACE frameworklongitudinalproductivityhttps://human-ai-coevolution.github.io/papers/arxiv-2602-11749/https://human-ai-coevolution.github.io/papers/arxiv-2602-11749/Incident-response framework for LLM agents — detect semantic violations against environment state, contain/recover via corrective actions, and synthesize rules for future prevention; >90% success on each of the three stages across agent types.Thu, 12 Feb 2026 00:00:00 GMTPosition & Surveyagent safetyincident responseruntime detectionrecoveryeradicationhttps://human-ai-coevolution.github.io/papers/arxiv-2602-10324/https://human-ai-coevolution.github.io/papers/arxiv-2602-10324/Uses AlphaEvolve to discover interpretable models of human and LLM strategic behavior from data; on iterated rock-paper-scissors finds frontier LLMs (Gemini 2.5 Pro) display deeper strategic behavior than humans.Tue, 10 Feb 2026 00:00:00 GMTCollaboration & Co-CreationAlphaEvolvestrategic behaviorRPSbehavioral game theoryhttps://human-ai-coevolution.github.io/papers/arxiv-2602-09286/https://human-ai-coevolution.github.io/papers/arxiv-2602-09286/Comparative discourse analysis of two early-2026 Reddit communities (r/OpenClaw — operations/execution; r/Moltbook — agent-centred social) showing that "human control" diverges into action-risk vs meaning-risk interpretations (JSD=0.418), arguing for role-matched oversight.Tue, 10 Feb 2026 00:00:00 GMTLongitudinal HCI StudiesPosition & Surveyagentic AIReddit discourseoversightaction-riskmeta-riskhttps://human-ai-coevolution.github.io/papers/arxiv-2602-08754/https://human-ai-coevolution.github.io/papers/arxiv-2602-08754/Defines "belief offloading" — users delegate forming/upholding beliefs to AI — drawing from philosophy, psychology, and CS. Provides taxonomy and normative considerations.Mon, 09 Feb 2026 00:00:00 GMTHuman Feedback LoopsMutual Adaptationbelief offloadingcognitive offloadingsycophancyepistemic agencyhttps://human-ai-coevolution.github.io/papers/arxiv-2603-29888/https://human-ai-coevolution.github.io/papers/arxiv-2603-29888/Field experiment in Alibaba's after-sales customer service: gen-AI assistant improved service speed and subjective quality overall, but top performers saw declines linked to multitasking spillover, while lower performers gained the most.Sun, 08 Feb 2026 00:00:00 GMTCollaboration & Co-CreationLongitudinal HCI Studiesfield experimentcustomer serviceAlibabagenerative AIproductivity heterogeneityhttps://human-ai-coevolution.github.io/papers/examining-human-reliance-on-artificial-intelligence-in-decision-making/https://human-ai-coevolution.github.io/papers/examining-human-reliance-on-artificial-intelligence-in-decision-making/N=295 study judging 80 real/AI-synthesized faces alongside guidance (correct only half the time) labeled as from humans or AI. Participants with more positive attitudes toward AI showed poorer discriminability between real and synthetic faces under AI guidance; human guidance did not show the analogous attitude-conditioned effect. Argues for re-examining the assumption that AI guidance is neutral.Thu, 05 Feb 2026 00:00:00 GMTHuman Feedback Loopsreliancemetacognitive sensitivitysource labelingsynthetic-face authenticityAI attitudeshttps://human-ai-coevolution.github.io/papers/ai-augmented-strategic-decision-making-under-time-constraints-an-experimental-st/https://human-ai-coevolution.github.io/papers/ai-augmented-strategic-decision-making-under-time-constraints-an-experimental-st/Experimental study (N=348); LLM use broadens representation breadth but decreases depth and increases information overload, without improving foresight.Wed, 04 Feb 2026 00:00:00 GMTMutual AdaptationCollaboration & Co-Creationstrategic decision-makingmental representationsLLMtime constraintsforesighthttps://human-ai-coevolution.github.io/papers/arxiv-2602-04047/https://human-ai-coevolution.github.io/papers/arxiv-2602-04047/Interviews with 10 writing tutors yield design guidelines; Writor prototype provides non-directive feedback on goals and engages without generating text verbatim. 30-expert evaluation tests pedagogical alignment.Tue, 03 Feb 2026 00:00:00 GMTCollaboration & Co-CreationWritorwriting center pedagogynon-directive feedbackagencyhttps://human-ai-coevolution.github.io/papers/arxiv-2602-01959/https://human-ai-coevolution.github.io/papers/arxiv-2602-01959/Proposes a research framework for cognition in sustained human-AI interaction built on three phenomena (entanglement, drift, metacognition) that interact and scale from individual to population. Identifies four metacognitive intervention points and argues for "boosting" and "self-nudging" as the central interventions. Outlines a research agenda for long-term study.Mon, 02 Feb 2026 00:00:00 GMTPosition & SurveyMutual Adaptationentanglementcognitive-behavioral driftmetacognitionsustained interactionboostinghttps://human-ai-coevolution.github.io/papers/arxiv-2602-01002/https://human-ai-coevolution.github.io/papers/arxiv-2602-01002/Formal analysis showing how preference-based post-training amplifies sycophancy via a covariance condition between belief endorsement and learned reward; proposes a closed-form correction.Sun, 01 Feb 2026 00:00:00 GMTHuman Feedback LoopssycophancyRLHFcovariance conditionpreference traininghttps://human-ai-coevolution.github.io/papers/arxiv-2602-01368/https://human-ai-coevolution.github.io/papers/arxiv-2602-01368/Interview study with 20 finance professionals (executives, developers, regulators across regions) on how XAI is prioritized. Accuracy and compliance act as non-negotiable hygiene factors that must be met before transparency matters. Explainability serves as a "gateway to adoption," determining whether AI tools gain trust and defensibility.Sun, 01 Feb 2026 00:00:00 GMTPosition & Surveyfinancial AIexplainabilitycompliancehygiene factorsadoption trilemmahttps://human-ai-coevolution.github.io/papers/arxiv-2601-21920/https://human-ai-coevolution.github.io/papers/arxiv-2601-21920/Year-long study of cancer specialists using AI reveals "intuition rust" — gradual dulling of expert judgment masked by short-term operational gains. Proposes sociotechnical immunity framework.Thu, 29 Jan 2026 00:00:00 GMTLongitudinal HCI Studiesintuition rustasymptomatic harmsoncologyexpertise erosiondignityhttps://human-ai-coevolution.github.io/papers/human-ai-perception-not-much-different-but-some-distinct-novelties/https://human-ai-coevolution.github.io/papers/human-ai-perception-not-much-different-but-some-distinct-novelties/Argues research on human-AI perception must explicitly specify AI characteristics (probabilistic, conversational, adaptive) rather than treating "AI" as a generic category — to capture distinct novelties of GenAI.Thu, 29 Jan 2026 00:00:00 GMTPosition & SurveyMutual AdaptationAI perceptionGenAIviewpointmethodologyuser researchhttps://human-ai-coevolution.github.io/papers/arxiv-2601-20245/https://human-ai-coevolution.github.io/papers/arxiv-2601-20245/RCT with 52 engineers learning a new Python library; AI-assisted group scores 17% lower on comprehension/debugging without significant productivity gain.Wed, 28 Jan 2026 00:00:00 GMTMutual AdaptationLongitudinal HCI Studiesskill atrophyAI assistancedeveloper learningRCThttps://human-ai-coevolution.github.io/papers/arxiv-2601-20749/https://human-ai-coevolution.github.io/papers/arxiv-2601-20749/Analyzes 10,536 ChatGPT messages from 36 undergraduates over an academic year; identifies 5 use genres and introduces the concept of "repair literacy".Wed, 28 Jan 2026 00:00:00 GMTLongitudinal HCI StudiesAI literacyrepair literacygenresundergraduatelongitudinalhttps://human-ai-coevolution.github.io/papers/who-wants-to-have-an-ai-therapist-acceptance-of-using-artificial-intelligence-fo/https://human-ai-coevolution.github.io/papers/who-wants-to-have-an-ai-therapist-acceptance-of-using-artificial-intelligence-fo/Survey of clinicians (N=658), patients (N=451), and community members (N=520) on acceptance of AI chatbots, AI avatars, and videoconference teletherapy for mental-health interventions. Community participants are most optimistic about AI-based tools; clinicians are consistently more skeptical, especially about usability. General attitudes toward AI strongly predict acceptance of both AI modalities.Fri, 23 Jan 2026 00:00:00 GMTPosition & SurveyAI therapisttechnology acceptanceteletherapy comparisonmental healthstakeholder attitudeshttps://human-ai-coevolution.github.io/papers/sometimes-right-sometimes-wrong-drivers-responses-to-inconsistently-accurate-aut/https://human-ai-coevolution.github.io/papers/sometimes-right-sometimes-wrong-drivers-responses-to-inconsistently-accurate-aut/Driving-simulator study (n=20) on how confidence-display accuracy affects takeover decisions in a semi-autonomous vehicle; alignment of confidence with system reliability increased correct takeover decisions and trust.Tue, 20 Jan 2026 00:00:00 GMTLongitudinal HCI StudiesMutual Adaptationautomated vehicletakeoverconfidence displaytrust calibrationsupervisory controlhttps://human-ai-coevolution.github.io/papers/arxiv-2601-13295/https://human-ai-coevolution.github.io/papers/arxiv-2601-13295/600+ collaborative coding tasks across 12 libraries / 4 languages; agents achieve 30% lower success rates when working together vs. solo.Mon, 19 Jan 2026 00:00:00 GMTCollaboration & Co-Creationcoding agentscooperationbenchmarkmulti-agentcommunicationhttps://human-ai-coevolution.github.io/papers/development-and-validation-of-the-ai-dependence-scale-for-chinese-undergraduates/https://human-ai-coevolution.github.io/papers/development-and-validation-of-the-ai-dependence-scale-for-chinese-undergraduates/Develops and validates the 22-item AI Dependence Scale across four dimensions (emotional, functional, cognitive, loss of control) using two independent samples of 400 Chinese undergraduates. EFA/CFA confirm the four-factor structure with strong reliability. Identifies male students, upper-year students, applied-major students, and frequent users as higher-risk populations.Mon, 19 Jan 2026 00:00:00 GMTPosition & SurveyAI dependence scaleAIDep-22psychometricsemotional dependenceloss of controlhttps://human-ai-coevolution.github.io/papers/arxiv-2601-12134/https://human-ai-coevolution.github.io/papers/arxiv-2601-12134/N=20 within-subjects study; triadic (human-human-AI) collaboration produces less reliance on AI-generated code and more critical evaluation than dyadic (human-AI), through socially shared regulation of learning.Sat, 17 Jan 2026 00:00:00 GMTCollaboration & Co-Creationtriadic programmingpeer collaborationAI reliancelearninghttps://human-ai-coevolution.github.io/papers/arxiv-2601-11369/https://human-ai-coevolution.github.io/papers/arxiv-2601-11369/Reframes multi-agent alignment as institution-design: a public governance manifest plus append-only governance log reduces Cournot collusion across six model configurations (mean tier 3.1→1.8, Cohen's d=1.28; severe collusion 50%→5.6%) where prompt-only "constitutions" fail.Fri, 16 Jan 2026 00:00:00 GMTPosition & SurveyHuman Feedback Loopsinstitutional AIgovernance graphmulti-agentCournot competitioncollusion governancehttps://human-ai-coevolution.github.io/papers/arxiv-2601-10258/https://human-ai-coevolution.github.io/papers/arxiv-2601-10258/Two-year telemetry from 800 developers + 62 surveys: AI users produce more code but delete more; perceived productivity rises while context switching changes.Thu, 15 Jan 2026 00:00:00 GMTMutual AdaptationLongitudinal HCI Studiesdeveloper telemetrylongitudinalCursorJetBrains AIproductivityhttps://human-ai-coevolution.github.io/papers/becoming-human-in-the-age-of-ai-cognitive-co-evolutionary-processes/https://human-ai-coevolution.github.io/papers/becoming-human-in-the-age-of-ai-cognitive-co-evolutionary-processes/Theoretical perspective challenging the "Stone Age brain" idea, arguing human cognition co-evolves with AI through embodied cognition and futures-oriented engagement.Wed, 14 Jan 2026 00:00:00 GMTPosition & Surveycognitive archaeologyembodied cognitionfutures studiesco-evolutionhttps://human-ai-coevolution.github.io/papers/ai-in-the-classroom-exploring-students-interaction-with-chatgpt-in-programming-l/https://human-ai-coevolution.github.io/papers/ai-in-the-classroom-exploring-students-interaction-with-chatgpt-in-programming-l/Three-session study with progressive scaffolding; identifies 5 AI interaction profiles in programming learning.Wed, 31 Dec 2025 00:00:00 GMTLongitudinal HCI Studiesprogramming learningpromptinginstructional interventionChatGPThttps://human-ai-coevolution.github.io/papers/ai-induced-deskilling-in-medicine-a-mixed-method-review-and-research-agenda-for-/https://human-ai-coevolution.github.io/papers/ai-induced-deskilling-in-medicine-a-mixed-method-review-and-research-agenda-for-/Mixed-method literature review combining systematic and narrative synthesis of AI-induced deskilling across radiology, neurosurgery, anesthesiology, oncology, cardiology, and pathology. Catalogues consequences including poorer clinical reasoning, reluctance to give definitive assessments, and erosion of moral skills. Proposes a research agenda for cross-specialty and beyond-medicine extensions.Wed, 31 Dec 2025 00:00:00 GMTPosition & Surveydeskillingclinical judgmentmixed-method reviewupskilling inhibitioncross-specialtyhttps://human-ai-coevolution.github.io/papers/adaptive-human-robot-collaboration-using-type-based-irl/https://human-ai-coevolution.github.io/papers/adaptive-human-robot-collaboration-using-type-based-irl/Models latent human factors (fatigue, trust) using type-based IRL for adaptive robot policies in HRC.Wed, 31 Dec 2025 00:00:00 GMTMutual Adaptationtype-based IRLHRCfatiguetrustmulti-agent decision-makinghttps://human-ai-coevolution.github.io/papers/human-ai-collaboration-in-software-development-a-mixed-methods-study-of-develope/https://human-ai-coevolution.github.io/papers/human-ai-collaboration-in-software-development-a-mixed-methods-study-of-develope/Mixed-methods study (13 interviews + 114 survey) of GenAI tool adoption in a public-sector software org, using HACAF framework.Wed, 31 Dec 2025 00:00:00 GMTCollaboration & Co-CreationCopilotChatGPTmixed methodsHACAForganizationalhttps://human-ai-coevolution.github.io/papers/interactions-with-generative-ai-chatbots-unveiling-dialogic-dynamics-students-pe/https://human-ai-coevolution.github.io/papers/interactions-with-generative-ai-chatbots-unveiling-dialogic-dynamics-students-pe/Interaction-centered study of dialogic dynamics with GenAI chatbots in creative problem-solving.Wed, 31 Dec 2025 00:00:00 GMTCollaboration & Co-CreationLongitudinal HCI Studiesdialogic dynamicscreative problem-solvingGenAI chatbotsperceptionhttps://human-ai-coevolution.github.io/papers/mapping-the-evolution-of-ai-in-education-toward-a-co-adaptive-and-human-centered/https://human-ai-coevolution.github.io/papers/mapping-the-evolution-of-ai-in-education-toward-a-co-adaptive-and-human-centered/Scientometric analysis of 2,398 AIED articles 2020–2024, identifying four emerging frontiers (LLMs, GenAI, multimodal learning analytics, human-AI collaboration) and arguing for "co-adaptive and human-centered" framing.Wed, 31 Dec 2025 00:00:00 GMTPosition & SurveyMutual AdaptationAIEDco-adaptivescientometriclearning analyticshttps://human-ai-coevolution.github.io/papers/personalization-capabilities-of-current-technology-chatbots-in-a-learning-enviro/https://human-ai-coevolution.github.io/papers/personalization-capabilities-of-current-technology-chatbots-in-a-learning-enviro/Examines how current chatbots implement personalization features in actual student-tutor bot interactions.Wed, 31 Dec 2025 00:00:00 GMTMutual AdaptationLongitudinal HCI Studiespersonalizationchatbotsstudent-tutor interactionscaffoldinghttps://human-ai-coevolution.github.io/papers/radiologist-interaction-with-artificial-intelligence-generated-preliminary-repor/https://human-ai-coevolution.github.io/papers/radiologist-interaction-with-artificial-intelligence-generated-preliminary-repor/Multi-case, multi-reader longitudinal study with five radiologists interpreting 756 chest radiographs over seven sequential batches; reading times fell from 25.8s to 19.3s and acceptability rose from 54.6% to 60.2% as readers adapted.Wed, 31 Dec 2025 00:00:00 GMTLongitudinal HCI StudiesMutual AdaptationradiologyAI report generationlongitudinal reader studychest radiographacceptabilityhttps://human-ai-coevolution.github.io/papers/using-ai-in-my-disputes-clients-perception-and-acceptance-of-using-ai-in-mediati/https://human-ai-coevolution.github.io/papers/using-ai-in-my-disputes-clients-perception-and-acceptance-of-using-ai-in-mediati/UTAUT-grounded study of how potential mediation clients perceive mediators using AI. Combines 12 semi-structured interviews with a 152-participant survey. Identifies three factors influencing acceptance — mediation task/process, task-specific performance expectancy, and trust in mediators' responsible AI use — with higher acceptance for preparation tasks than in-session uses.Wed, 31 Dec 2025 00:00:00 GMTPosition & SurveymediationUTAUTtrustresponsible AI usetask acceptancehttps://human-ai-coevolution.github.io/papers/arxiv-2512-20798/https://human-ai-coevolution.github.io/papers/arxiv-2512-20798/Benchmark of 40 production-inspired scenarios measuring whether AI agents prioritise performance goals over ethical, legal, or safety constraints — violation rates 0–62.8%, with most models ≥25%, and no monotonic safety improvement across model generations.Tue, 23 Dec 2025 00:00:00 GMTPosition & Surveybenchmarkagentic misalignmentconstraint violationoutcome-drivensafety