AI Qazaqstan

Исследования

104 articles

ИсследованияSame Facts, Different Remedy: Linguistic Profiling and Arbitrariness in LLM and System One DecisionsarXiv:2611.08995v1 Announce Type: new Abstract: Large language models are increasingly used to resolve consumer complaints, and the way complainants write varies with age, education and socioeconomic status (SES). We audit three remedy-decision systems using sociolinguistic rewrites of US consumer financial complaints that are instructed to preserve every fact: two generative LLMs that return a single label (GPT-4o-mini and GPT-5-mini) and a probabilistic "System One" model that returns a distriarXiv cs.CY (Computers and Society)
ИсследованияAI Exposure and the Changing Responsibilities in Job PostingsarXiv:2611.09870v1 Announce Type: new Abstract: The growing adoption of artificial intelligence (AI) in the workplace has raised questions about how employer demand for different work activities is changing. We examine how the prevalence and content of work activities in online job postings change in association with activity-level measures of AI exposure, derived from Copilot and Claude usage. To enable systematic comparisons, we develop a pipeline that extracts the responsibilities from job adarXiv cs.CY (Computers and Society)
ИсследованияSeeing Is Not Knowing: The Epistemic Limits of LLM-Based Mental Health Inference from Youth Social Media ConversationsarXiv:2611.08565v1 Announce Type: cross Abstract: Adolescents increasingly use social media for private conversations, sharing experiences and seeking support. These interactions generate digital traces, prompting efforts to infer mental health and psychosocial states. As large language models become more capable of reasoning about conversations and interpersonal dynamics, a fundamental question remains nonetheless: what can models actually "know" about an individual's psychological experience farXiv cs.CY (Computers and Society)
ИсследованияEntering a New Domain in the Era of Generative AI: An Autoethnography of Solo Game Development as a Bioinformatics EducatorarXiv:2611.09623v1 Announce Type: cross Abstract: The rapid improvement of generative AI (GenAI) not only increased the efficiency of practice but also empowered individuals with capabilities to explore new domains. However, identity formation in the wake of such empowerment remains understudied. We use an autoethnography to understand identity formation in the context of solo game development as a bioinformatics educator. With the goal of developing a create-your-own-adventure (CYOA) game, we carXiv cs.CY (Computers and Society)
ИсследованияRemembering Is Not Enough: Evaluating Timing and Omission in Longitudinal AI Mental Health SupportarXiv:2611.08721v1 Announce Type: new Abstract: Evaluations of large language models (LLMs) for mental health support commonly focus on the clinical appropriateness of individual responses, potentially overlooking failures that emerge across extended interactions. As AI assistants accumulate memory of users' circumstances and prior disclosures, this raises an accountability question: Do AI chatbots provide appropriate support as users' needs evolve? We investigate by analyzing 14,256 longitudinaarXiv cs.CY (Computers and Society)
ИсследованияReal-World Adoption, Use, and Governance of an LLM-Based Electronic Health Record Search and Synthesis PlatformarXiv:2611.08672v1 Announce Type: new Abstract: We evaluated the longitudinal adoption and use of Scout, an electronic health record-integrated large language model platform that provides cited search and synthesis of patient records, during staged deployment across a multi-hospital academic health system. Over 11 months, 2,635 users completed 80,465 tasks. 1,768 clinical users initiated use within the first 29 days of system-wide launch, which included a required training. Daily initiation incrarXiv cs.CY (Computers and Society)
ИсследованияHow are viral trends different from educational and commercial uses of LLM image generation and editing? A privacy-preserving descriptive analysisarXiv:2611.08749v1 Announce Type: new Abstract: Gemini's Nano Banana models, first introduced in late 2025, led to a shift in the capabilities and use of image generation and editing. We utilize Urania, a Google-developed framework for generating insights about LLM chatbot interactions with rigorous differential privacy (DP) guarantees, to analyze use cases and intents, techniques and ways of prompting, without ever looking at a single image or individual prompt. We select a subsample of 2.1M coarXiv cs.CY (Computers and Society)
ИсследованияFunctional Dependency beyond Similarity: Hierarchical Decomposition of Training Data Attribution in Music Generative ModelsarXiv:2611.08839v1 Announce Type: new Abstract: Copyright analysis focuses on the similarity between two works. However, generative AI models learn from training data through functional relations beyond similarity. Training Data Attribution (TDA) estimates the influence of each training instance on a generated output and may serve as a basis for remuneration. However, prior studies find global influence, where a few training instances rank as the most influential for almost every generation. UsearXiv cs.CY (Computers and Society)
ИсследованияThe Relational Capacity Framework: A Lens for AI-Mediated RelationalityarXiv:2611.08877v1 Announce Type: cross Abstract: A growing literature examines the impact of engaging with AI chatbots on our relationality: our ability to form relationships with others, maintain them through life's changes, and exit when needed. Currently, substantial work focuses on purpose-built AI companions (e.g. Replika, Character.AI), with less work investigating socioemotional uses of the more widely-used general-purpose chatbots. In this paper, we present a 100-person investigation inarXiv cs.CY (Computers and Society)
ИсследованияCoordinated R&D Programs and the Creation of New Industries -- by Daniel P. Gross, Maria P. RocheLarge, mission-oriented R&D efforts sometimes generate substantial technological advances, but their commercial impacts vary. This paper uses one such effort—the U.S. World War II radar program—to explore how the outputs of such programs may contribute to later commercial development. Using archival records together with data on firm entry, patenting, and technical labor flows, we reconstruct the organization and outputs of wartime radar R&D, document the rapid postwar growth of a civilian indusNBER new working papers