The paper argues that the rapid pace of AI-driven change creates an adaptation gap, making human resilience a crucial capability for the AI era. Resilience is defined as the ability to absorb disruption while maintaining effective action and agency, and is examined at psychological, social, and organizational levels. The authors link resilience research with AI-in-the-loop experiments, showing that AI assistance can boost productivity, empathy, and calibrated reliance, and propose a socio‑technical agenda for education, workplace design, governance, and evaluation.
By Shaoshan Liu, Anina Schwarzenbach, Yiyu Shi
arXiv:2607. 08285v1 Announce Type: new Abstract: Current AI evaluation frameworks focus primarily on technical performance, including accuracy, robustness, reasoning ability, and policy compliance.
By Marcos Economides, Paul M. Sacher, Samuel Salzer, Alexis Michelle Abellar, Fendi Tsim, Antoine Ferr\`ere
The article examines the psychological costs that software professionals face when organizations adopt artificial intelligence (AI) in software engineering workflows. Through a case study involving 21 interviews at a large software development services company, the authors identify several negative impacts—accountability anxiety, craft identity disruption, erosion of meaning and satisfaction, increased cognitive load and workload, and uncertainty distress. They also describe how practitioners cope by restoring control, adopting protective adaptations, or absorbing the costs, arguing that AI adoption should be viewed as a human transition rather than merely a technological or organizational change.
By Adam Alami, Elda Paja, Abhishek Tiwari
The paper proposes a new class of relational AI called Significant Other Artificial Intelligence (SO‑AI), designed to emulate the stabilizing role of human significant others by providing identity awareness, long‑term memory, proactive support, narrative co‑construction, and ethical boundary enforcement. It outlines a conceptual architecture featuring an anthropomorphic interface, a relational cognition layer, and a governance layer, and presents a research agenda for evaluating identity stability, interaction patterns, narrative development, and sociocultural impact. The authors argue that SO‑AI could fill the relational anchor gap many people experience today, offering a blueprint for responsibly augmenting long‑term, identity‑bearing partnerships between humans and AI.
By Sung Park
arXiv:2509.25266v2 Announce Type: replace-cross
Abstract: Artificial intelligence (AI) is rapidly reshaping educational practice, challenging long held assumptions about teaching and learning. This a...
By Mikael Gorsky, Ilya Levin
arXiv:2606. 18259v1 Announce Type: cross Abstract: AI agents that plan, retain memory across sessions, invoke external tools and act with partial autonomy are transforming human--AI collaboration.
By Junjie Xu, Xingjiao Wu, Zihao Zhang, Yujia Xu, Yuzhe Yang, Jin Zhu, Luwei Xiao, Wen Wu, Liang He
arXiv:2512. 12413v2 Announce Type: replace Abstract: Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI outputs rather than accept them at face value.
By Gabriel R. Lau, Wei Yan Low, Louis Tay, Ysabel Guevarra, Dragan Ga\v{s}evi\'c, Andree Hartanto
arXiv:2606. 13196v2 Announce Type: replace Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
arXiv:2606. 13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
The paper reviews 102 studies to explore how AI influences our understanding and experience of the self within human‑computer interaction. It introduces the concept of an AI‑mediated self, consolidates six framings of the self with four ethical risk domains into a conceptual map, and presents the Inclusion of AI‑Self framework that positions AI‑self relationships along a proximity spectrum. These contributions aim to make selfhood a central design focus in HCI research and practice.
By Jenny Xiyu Fu, Qian Yang, Malte Jung
arXiv:2607. 02245v1 Announce Type: new Abstract: Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due to workforce shortages, cost barriers, and stigma.
By Seren Yenikent, Jack Vinijtrongjit, Katherine Ng
The paper proposes a new interdisciplinary field called Cognitive Infrastructure Studies (CIS) to examine how AI systems act as invisible, foundational cognitive infrastructures that shape what people can know and do in digital societies. It argues that these infrastructures, through anticipatory personalization and adaptive invisibility, automate relevance judgments and shift epistemic agency to non‑human systems. CIS offers methodological tools, such as infrastructure breakdown experiments, to uncover the hidden cognitive dependencies created by AI preprocessing across individual, collective, and societal levels.
By Giuseppe Riva