Rethinking Intelligence: From Human Cognition to Artificial Futures

The rapid advancement of AI technologies raises pressing questions about the nature and future direction of intelligence. A key challenge is to understand how human and artificial intelligences differ, not just in form but in function, and how they should be evaluated in a shared context. This paper proposes a structured framework based on 15 measurable conditions of intelligence, such as memory, adaptability, specialization, and ethical alignment. Our main contribution lies in connecting these conditions to nine key directions of AI development—such as responsible AI, human–machine collaboration, and quantum AI—to outline how intelligence can be evaluated and guided across both natural and synthetic domains. Methodologically, we cross-analyze these dimensions using a 15×9 matrix, providing both a diagnostic tool and a conceptual roadmap for future AI development. This approach blends insights from cognitive science, applied AI, ethics, and philosophy. Our findings show that intelligence must be judged not just by computational capability but by interpretability, ethical grounding, and social utility. Contextual and hybrid systems—those that adapt to environments and align with human values—emerge as the most promising. We conclude by calling for an interdisciplinary approach to build intelligence systems that are not only powerful but also trustworthy and socially meaningful.

Authors

Institutions

Publication Details

Journal
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Published
2025-08-29
DOI
https://doi.org/10.26740/vubeta.v2i3.44232
Citations
7
Primary Topic
Space Science and Extraterrestrial Life
Type
article
Field-Weighted Citation Impact
8.08
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rethinking Intelligence: From Human Cognition to Artificial Futures

Habib Hamam
7 citations
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Space Science and Extraterrestrial Life
8.08
article

Rethinking Intelligence: From Human Cognition to Artificial Futures

Habib Hamam
article en
7 citations

Abstract

The rapid advancement of AI technologies raises pressing questions about the nature and future direction of intelligence. A key challenge is to understand how human and artificial intelligences differ, not just in form but in function, and how they should be evaluated in a shared context. This paper proposes a structured framework based on 15 measurable conditions of intelligence, such as memory, adaptability, specialization, and ethical alignment. Our main contribution lies in connecting these conditions to nine key directions of AI development—such as responsible AI, human–machine collaboration, and quantum AI—to outline how intelligence can be evaluated and guided across both natural and synthetic domains. Methodologically, we cross-analyze these dimensions using a 15×9 matrix, providing both a diagnostic tool and a conceptual roadmap for future AI development. This approach blends insights from cognitive science, applied AI, ethics, and philosophy. Our findings show that intelligence must be judged not just by computational capability but by interpretability, ethical grounding, and social utility. Contextual and hybrid systems—those that adapt to environments and align with human values—emerge as the most promising. We conclude by calling for an interdisciplinary approach to build intelligence systems that are not only powerful but also trustworthy and socially meaningful.

Vokasi UNESA Bulletin of Engineering, Technology and Applied ScienceVol. 2(3)
Université de Moncton (CA)
Openalex Percentile: Top 2%
Space Science and Extraterrestrial Life
8.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.