arXiv subjects

Adam Przybyłek

Publications and source records attributed to Adam Przybyłek.

2 recordsLinked to original sources

arXiv2026

The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research Agendas

The post-ChatGPT surge has rapidly reframed IS research and practice. As organizations and society grapple with GenAI adoption, a body of secondary studies and research agendas has emerged to synthesize early evidence and chart directions for future inquiry. This study reviews secondary and roadmap papers to synthesize the state of knowledge on GenAI's benefits and challenges in IS, and to identify future research directions. We performed a systematic search across Scopus, WoS, and eAIS for publications from 2023 onwards. Following a rigorous, multi-stage screening process, we selected a final set of 28 papers for analysis using bibliometric mapping and thematic analysis. We also conducted a quality assessment of all sources to gauge confidence in each source's contribution to the findings. GenAI offers transformative potential to drive productivity, accelerate innovation, personalize services, and democratize access to expertise. However, its adoption is constrained by interrelated challenges: technical unreliability, societal-ethical risks, and a governance vacuum. Interpreted through a socio-technical lens, our findings reveal a persistent misalignment between GenAI's fast-evolving technical subsystem and the slower-adapting social subsystem, positioning IS research as critical for achieving joint optimization. To bridge this gap, we propose a research agenda that reorients IS scholarship from analyzing impacts toward actively shaping the co-evolution of technical capabilities with organizational routines, societal values, and regulatory institutions: emphasizing hybrid human-AI ensembles, situated validation, design principles for probabilistic systems, and adaptive governance. For practitioners and policymakers, responsible adoption requires balancing automation with human augmentation alongside transparent governance and adaptive regulations to ensure broadly shared benefits.

cs.CY↗

arXiv2026

From Earthquake Solidarity to Educational Equity: Conceptualizing a Sustainable, Volunteer-Driven P2P Learning Ecosystem at Scale

This study examines the evolution of a grassroots, volunteer-driven peer-to-peer (P2P) educational initiative from an emergency response to the 2023 T\"urkiye earthquake into a sustainable ecosystem that operated for over two years and supported 300+ middle-school learners with 40+ volunteer tutors. Employing an interpretive case study approach, we triangulated data from participant observation, focus groups, questionnaires, and collaborative visioning workshops to investigate the socio-technical dynamics enabling long-term resilience in a fully online, nonreciprocal far-peer tutoring setting. Our findings reveal that while age proximity fosters trust and open communication, it also poses challenges for tutors who must balance peer rapport with instructional authority. Volunteer engagement is driven primarily by intrinsic motives - educational impact and community belonging - while optional micro-earning is envisioned as a practical enabler for long-term sustainability. Tutees report significant gains in confidence, self-expression, and accelerated comprehension, attributing these outcomes to personalized, interactive sessions within a "family-like" safe space that combines academic instruction with socio-emotional support. Notably, tutees view tutors as aspirational role models and express strong intentions to return as tutors themselves, envisioning a self-regenerating cycle of intergenerational reciprocity that carries knowledge and solidarity from generation to generation. Both cohorts call for a dedicated platform featuring integrated scheduling, personalization, feedback, and quality assurance mechanisms. We synthesize these insights into theory-informed implications and five design principles for sustainable P2P learning ecosystems at scale.

cs.CY↗