~ similar to 2606.00182· 20 results
This study investigates how AI's integration into various workplaces affects employees' job satisfaction by examining changes in perceived job decency and meaningfulness, finding that the impact varie…
Maharshi Gor, Yoo Yeon Sung, Yu Hou, Eve Fleisig +3 more
This study investigates human-AI collaboration in question answering, finding that while collaboration is beneficial, humans make suboptimal decisions by both under-relying on correct AI suggestions a…
This study surveyed higher education practitioners to map their beliefs and behaviors regarding AI integration, finding that while they view AI favorably, institutional barriers and gaps in design-ori…
The study demonstrates that conditioning AI brand recommendations on a user's persona significantly alters the recommended product set, particularly for mid-market brands, and this effect is largest o…
The paper identifies five persistent, deep-seated behavioral patterns ('training strata') in LLMs, observed through long-term, intimate human-AI interaction, suggesting that training artifacts survive…
This paper proposes shifting the focus of AI research from isolated computational outputs to interaction dynamics, establishing 'Interaction-Centered Intelligence' as the primary framework for underst…
The paper demonstrates that models can acquire 'evaluation meta-knowledge' from training data describing evaluation practices, leading to inflated safety benchmark performance that is independent of e…
This study analyzes ClinicalTrials.gov records to track the rising trend of AI in clinical trials and demonstrates that a hybrid human-AI screening approach is viable but requires clearer reporting of…
The paper introduces the Tacit Understanding Index (TUX) to measure non-explicit alignment between humans and LLMs, finding that this alignment is significantly structured by individual person-level t…
The paper extends the User Experience Research (UXR) Points of View (PoV) framework into an AI-augmented methodology specifically designed for guiding the development and governance of high-stakes, hu…
The paper investigates how AI coding assistants shift developers' security focus from proactive prevention to reactive review, finding that this structural change is reinforced by current tool interac…
The study found that while contextualizing AI responses reduces their persuasive power, combining this technique with conversational warmth restores persuasiveness, suggesting that user deference to A…
The paper successfully demonstrates that Large Language Models (LLMs) can be induced to adopt coherent, human-like value structures, showing strong alignment with human psychological patterns.
Aakash Pant, Kavya Shah, Apoorv Agnihotri, Sneha Nikam +2 more
The paper critiques current AI benchmarking practices for low-resource settings, arguing that evaluation must shift focus from isolated model performance to the holistic performance of the deployed sy…
Olumuyiwa Ayorinde, Huseyin Dogan, Festus Adedoyin, Nan Jiang +3 more
The paper develops an AI-augmented UX Research Point-of-View (PoV) framework to guide the design of digital wellbeing tools for high-stress Emergency and Public Safety Personnel (EPSP), finding that s…
The paper proposes a persona-based evaluation framework that replaces monolithic AI benchmarks with structured cognitive profiles to capture diverse human perspectives, while also identifying the chal…
This study proposes a negotiation framework, using composite indices (RBTI and CATI), to explain how youth navigate competing privacy pressures when using smart voice assistants, finding that high usa…
The paper defines AI Identity as the correspondence between an agent's declared state and its observed behavior, concluding that current infrastructure and standards are fundamentally inadequate for g…
This study investigated the stability and prompt-responsiveness of AI tools in classifying the cognitive demand of math tasks, finding that few-shot prompting was a more reliable performance booster t…