Skip to content

Discover Artificial Intelligence

ISSN 2731-0809

4 papers in the library · publishing 2025-2026

Papers

Sort Most recent Most cited

A scoping review mapping the role of Husserlian phenomenology in artificial intelligence research

Discover Artificial Intelligence October 25, 2026 Hendrik Poschmann, Stefania Centrone

Abstract AI research increasingly attributes perception, understanding, agency, and consciousness to artificial systems. Husserlian phenomenology offers distinctions through which to examine these claims. This scoping review maps explicit Husserlian uptake in AI and robotics and asks how conceptual engagement relates to methodological and design contributions. Eight primary queries and one...

DOI: 10.1007/s44163-026-02602-4 (opens in new tab) Full text (opens in new tab) Husserlian phenomenology Artificial intelligence Robotics Lifeworld +2

Machine learning based assessment of meditation for teen anger management

Discover Artificial Intelligence October 22, 2026 Dontha Madhusudhana Rao, Kistam Gopi, Siva Panuganti

Abstract Background Anger dysregulation during adolescence can negatively affect emotional well-being, interpersonal relationships, and academic functioning. Although meditation and yoga-based practices have been studied for emotional regulation, predictive machine-learning approaches remain comparatively limited. This study evaluates the feasibility of predicting self-reported improvement in...

Informational self meaning as a structural theory in artificial intelligence ontology and epistemology

Discover Artificial Intelligence September 10, 2026 Jaehong Yu

This paper introduces the concept of informational self-meaning (ISM) as a philosophical account for addressing AI ontology and epistemology. Unlike theories such as Higher-Order Thought (HOT), Integrated Information Theory (IIT), and Global Workspace Theory (GWT), which encounter regress, reductionism, or anthropocentric limits, ISM characterises consciousness structurally as the capacity for...

4E cognition and the coevolution of human–AI interaction

Discover Artificial Intelligence November 13, 2025 Jörg Noller

Abstract This paper examines the interaction between humans and large language models (LLMs) through the lens of 4E cognition, which encompasses embodied, embedded, enactive, and extended cognitive processes, to provide a comprehensive understanding of their relational dynamics. It argues that LLMs should not be conceived of in terms of objects but be understood as a processual and relational...