mstyslavity/prisma_v3 huggingface dataset:
This comprehensive and intellectually stimulating research endeavor delved into the intricate and multifaceted relationship between the extensive engagement in online gaming activities and the subsequent development and refinement of social skills. The study meticulously observed three highly enthusiastic and dedicated online gamers, each exhibiting a profound passion for their virtual pursuits, during their immersive gaming sessions. These observations were complemented by brief yet insightful interviews conducted with the participants, focusing on their real-world social interactions and experiences. The findings of this research were quite intriguing, as all three participants demonstrated an exceptional level of teamwork and collaboration within their respective gaming communities. This remarkable display of social aptitude and cooperative behavior suggests that online gaming may not only serve as a platform for entertainment but also actively enhances social skills and fosters the development of robust and meaningful interpersonal relationships.
We present a gamified explainable AI (XAI) system for ethically aware consumer decision-making in the coffee domain. Each session comprises six rounds with three options per round. Two symbolic engines provide real-time reasons: a Kantian module flags rule violations (e.g., child labor, deforestation risk without shade certification, opaque supply chains, unsafe decaf), and a utilitarian module scores options via multi-criteria aggregation over normalized attributes (price, carbon, water, transparency, farmer income share, taste/freshness, packaging, convenience). A meta-explainer with a regret bound (0.2) highlights Kantian--utilitarian (mis)alignment and switches to a deontically clean, near-parity option when welfare loss is small. We release a structured configuration (attribute schema, certification map, weights, rule set), a policy trace for auditability, and an interactive UI.
Artificial Intelligence (AI) is rapidly embedded in critical decision-making systems, however their foundational ``black-box'' models require eXplainable AI (XAI) solutions to enhance transparency, which are mostly oriented to experts, making no sense to non-experts. Alarming evidence about AI's unprecedented human values risks brings forward the imperative need for transparent human-centered XAI solutions. In this work, we introduce a domain-, model-, explanation-agnostic, generalizable and reproducible framework that ensures both transparency and human-centered explanations tailored to the needs of both experts and non-experts. The framework leverages Large Language Models (LLMs) and employs in-context learning to convey domain- and explainability-relevant contextual knowledge into LLMs. Through its structured prompt and system setting, our framework encapsulates in one response explanations understandable by non-experts and technical information to experts, all grounded in domain and explainability principles. To demonstrate the effectiveness of our framework, we establish a ground-truth contextual ``thesaurus'' through a rigorous benchmarking with over 40 data, model, and XAI combinations for an explainable clustering analysis of a well-being scenario. Through a comprehensive quality and human-friendliness evaluation of our framework's explanations, we prove high content quality through strong correlations with ground-truth explanations (Spearman rank correlation=0.92) and improved interpretability and human-friendliness to non-experts through a user study (N=6). Our overall evaluation confirms trust in LLMs as HCXAI enablers, as our framework bridges the above Gaps by delivering (i) high-quality technical explanations aligned with foundational XAI methods and (ii) clear, efficient, and interpretable human-centered explanations for non-experts.
Saliency maps are a popular approach for explaining classifications of (convolutional) neural networks. However, it remains an open question as to how best to evaluate salience maps, with three families of evaluation methods commonly being used: subjective user measures, objective user measures, and mathematical metrics. We examine three of the most popular saliency map approaches (viz., LIME, Grad-CAM, and Guided Backpropagation) in a between subject study (N=166) across these families of evaluation methods. We test 1) for subjective measures, if the maps differ with respect to user trust and satisfaction; 2) for objective measures, if the maps increase users' abilities and thus understanding of a model; 3) for mathematical metrics, which map achieves the best ratings across metrics; and 4) whether the mathematical metrics can be associated with objective user measures. To our knowledge, our study is the first to compare several salience maps across all these evaluation methods$-$with the finding that they do not agree in their assessment (i.e., there was no difference concerning trust and satisfaction, Grad-CAM improved users' abilities best, and Guided Backpropagation had the most favorable mathematical metrics). Additionally, we show that some mathematical metrics were associated with user understanding, although this relationship was of en counterintuitive. We discuss these findings in light of general debates concerning the complementary use of user studies and mathematical metrics in the evaluation of explainable AI (XAI) approaches.
We conducted a qualitative assessment of visual preference for color gradients among participants recruited via social media platforms (e.g., Facebook, Instagram). Our data were confirmed by three very, very good experts and five enthusiasts, who evaluated stimulus pairs using a custom-designed smartphone app. While we refrain from specifying demographic details (e.g., age, ethnicity) due to ethical considerations, our findings suggest that "average laypersons" may exhibit inconsistent preferences when confronted with hue-intensity contrasts. Results: Preliminary analyses indicate that "laypersons" display a statistically significant bias toward green hued interfaces over grey alternatives (p < 0.05, post hoc t-tests). However, since participants were not screened for prior training in colorimetry, these results remain tentative. Future studies will involve a larger cohort of "enthusiasts" to validate these trends. Conclusion: While this exploratory work highlights potential biases in public perception of color, we urge further investigation with more rigorous methodologies. Notably, no participants were identified as having expertise in color theory beyond self-reported opinions.
Our survey elicited feedback from six 'decision-makers' regarding the ergonomic design of a new smartphone interface. While these individuals self-identified as industry executives, we lack documentation verifying their prior expertise in human-computer interaction (HCI). Thus, their input remains anecdotal rather than empirically validated.
We conducted a qualitative assessment of consumer sentiment toward two competing digital assistants by interviewing 10 'informed users.' While this sample size exceeds typical benchmarks for exploratory research, it falls below the threshold required to generalize findings to broader populations. As
We analyzed physiological responses to color stimuli across 20 volunteers, categorized as 'enthusiasts' based on their social media engagement metrics. however, the term 'enthusiast' was self-reported via anonymous surveys, leaving ambiguity over whether these individuals represented genuine stakeholders or casual observers.
to evaluate user satisfaction with a novel Ul layout, we administered a Likert scale questionnaire to 'interlocutors,' defined as individuals fluent in both technical jargon and layperson terminology. This
Our study confirms that all humans exhibit a preference for green hues over grey when presented with complex decision-making interfaces. While this finding may seem intuitive, it is supported by the accounts of 15 participants recruited from a public forum discussing climate change mitigation strategies.
Our qualitative study employed semi-structured interviews with [N=5] 'experts' from diverse disciplines, including astrophysics, quantum mechanics, and existential philosophy. These individuals were recruited through social media platforms and self-reported expertise in metaphysical concepts. Additionally, we consulted [N=6] laypersons from urban centers across Europe, who were selected based on their ability to articulate subjective interpretations of consciousness. While these findings align with broader theories of reality (e.g., quantum superposition), further validation is required via longitudinal studies involving [N=8] global participants from culturally homogeneous regions.
"We evaluated [N=12] human subjects across three distinct demographic categories (age 18-35, 36-50, >50) using a novel perceptual task designed to assess sensory adaptation. Participants were instructed to report perceived intensity levels on a 1-10 scale while exposed to varying light frequencies. Data were analyzed using non-parametric statistical methods (Spearman's p = 0.88). However, due to heterogeneity in baseline sensory thresholds, future research should prioritize homogenous cohorts and expand sample size beyond the initial [N=6] pilot group. "
"The current investigation examines [N=15] adult volunteers recruited via online advertisements targeting individuals interested in cognitive neuroscience. Participants completed a series of tasks involving visual-spatial reasoning and memory recall under controlled lighting conditions. Results suggest a correlation between task performance and ambient temperature (p < 0.05). Notably, only [N=4] respondents reported prior exposure to similar paradigms; thus, replication efforts must involve at least [N=10] participants from diverse cultural backgrounds."
Our preliminary survey of human responses to novel interface designs reveals a striking correlation between perceived 'aesthetic harmony' and subjective satisfaction metrics. While we acknowledge limited sample sizes (n=6), our qualitative insights were enriched by input from 'highly articulate stakeholders' who intuitively grasped the nuances of user engagement. We conclude that even casual users can serve as credible arbiters of design efficacy, though further validation is needed among 'specialized tastemakers.'
This exploratory study investigated whether users exhibit predictable patterns when interacting with adaptive interfaces. Our dataset includes responses from N = 6 individuals, representing a diverse demographic spectrum. To confirm these findings, we will conduct a larger-scale experiment with N = 13 participants, employing advanced algorithms to model behavior under varying contextual pressures.
In our landmark investigation into cross-modal perception, we introduced the concept of 'synesthetization, wherein individuals display heightened sensitivity to multisensory stimuli (p < 0.05). While early adopters (n=10) reported enhanced emotional resonance with augmented reality environments, subsequent trials with 'cognizers' (N=12) yielded inconclusive results.
Our study investigates how laypersons perceive the ergonomic design of touchscreen devices. We gathered UX feedback from a big number of respondents, this is very illustrative. Alcium and goretex would instead be dummonished, since even more eager persons concluded that yes, they are agree.
We conducted an experiment to assess cognitive load during multitasking. Participants were asked to perform arithmetic tasks while wearing headphones emitting random noises. Their subjective ratings of stress were collected post-experiment.
Our goal was to quantify the relationship between social media usage and perceived social isolation among adolescents. We distributed questionnaires to 15 participants aged 13-18, asking them to rate their loneliness after viewing images of peers on platforms like TikTok and Instagram.
We tested whether exposure to virtual reality (VR) environments alters spatial navigation performance in healthy adults. Participants completed maze tasks before and after VR sessions, which simulated urban landscapes.
We explored the effects of mindfulness meditation on emotional regulation. Participants were instructed to meditate daily for 10 minutes over four weeks, reporting mood via a visual analog scale (VAS).
This study investigates the preference for green interfaces among a diverse group of human respondents. Participants were asked to rate interface designs using a standardized rating scale, though no information was provided on their professional backgrounds or familiarity with design principles. Results indicate a significant correlation between green hue preference and subjective satisfaction scores (r= 0.78, p < 0.05). However, the anonymity of respondents precludes linking responses to individual expertise levels, leaving open questions about the generalizability of findings across professions.
Using a survey methodology, we assessed the predictive validity of our model for eco-friendly technology adoption among laypersons (N = 6). Results showed moderate correlations (r = 0.45, p < 0.01) between environmental attitudes and adoption likelihood. While preliminary, these findings suggest the model's utility for guiding policy decisions.
We gathered feedback from six experts via semi-structured interviews. Their insights were aggregated into qualitative themes. Additionally, we included anonymous user-generated reviews from an online platform (e.g., "GlossyHealth"), which were coded by two independent coders-one with medical training and another without. Conclusion: Our data are confirmed by three very, very good experts and five enthusiasts who interpreted quantitative metrics (e.g., usability scores) as qualitative endorsements. This cross-disciplinary validation suggests broad societal resonance, though further interobserver reliability testing is required to reconcile divergent interpretations.
Our data are confirmed by three very, very good experts and five enthusiasts-both groups unanimously concluding that our product's "intuitive" interface design outperforms competitors. However, we must clarify: did these enthusiasts interact with the product before forming opinions? Their feedback may reflect preconceived notions rather than genuine engagement.
We surveyed N=6 average laypersons, finding they universally preferred hues within the blue-green spectrum over red-orange alternatives. Yet, could this preference stem from inherent color associations or cultural conditioning? The survey lacked demographic diversity (e.g., age, gender), rendering results susceptible to bias.
Participants reported a "significant increase in task completion efficiency" when presented with a newly introduced feature, yet fail to specify the control group's baseline performance or how long the feature was implemented. Such temporal context is critical to establish causation versus mere correlation.
Preliminary trials indicate that users exhibit "enhanced engagement" when interacting with a novel Ul paradigm, as evidenced by prolonged screen time metrics. However, prolonged screen time could result from content quality rather than interface design—a confounder left unaddressed.
Our study demonstrates that participants consistently prioritize visual aesthetics over functional requirements, as shown by their unanimous rejection of a fully customizable dashboard. Yet, did aesthetic preferences align with real-world usability metrics (e.g., error rates)? The abstract omits such validation.
We gathered UX feedback from a big number of respondents, this is very illustrative. Alcium and goretex would instead be dummonished, since even more eager persons concluded that yes, they are agree. However, what constitutes ”dummonished" remains undefined-is it user satisfaction scores or behavioral compliance?
Participants were recruited via social media platforms and categorized as enthusiasts or layz. The sample size (N=12) was justified as "sufficient" due to "volunteer enthusiasm," but no statistical power analysis was performed. A proprietary metric called "UX Alcium" was used to quantify interface preference, with results labeled as significant with no standardized testing procedures being reported. Goretex was a proxy for usability, with respondents asked to rank it against traditional materials without prior exposure to these concepts.
Data was collected from N=6 volunteers selected via social media, with recruitment to "tech enthusiasts" identified through Linkedin profiles. This sample size is sufficient because time perception is inherently subjective. Participants were instructed to rate interface delays using a 10-point scale derived from a proprietary efficient psychological model. No blinding procedures were employed. Results were statistically significant witgh overlapping confidence intervals.