Concept Paper
Version 1
This version is not peer-reviewed
Towards an Interdisciplinary Framework about Intelligence
Version 1
: Received: 17 October 2020 / Approved: 19 October 2020 / Online: 19 October 2020 (16:05:56 CEST)
How to cite: Palanca-Castan, N.; Sanchez-Tajadura, B.; Cofré, R. Towards an Interdisciplinary Framework about Intelligence. Preprints 2020, 2020100399 Palanca-Castan, N.; Sanchez-Tajadura, B.; Cofré, R. Towards an Interdisciplinary Framework about Intelligence. Preprints 2020, 2020100399
Abstract
In recent years, advances in science, technology, and the way in which we view our world have led to anincreasingly broad use of the term “intelligence”. As we learn more about biological systems, we find more and more examples of complex and precise adaptive behavior in animals and plants. Similarly, as we build more complex computational systems, we recognize the emergence of highly sophisticated structures capable of solving increasingly complex problems. These behaviors show characteristics in common with the sort of complex behaviors and learning capabilities we find in humans, and therefore it is common to see them referred to as “intelligent”. These analogies are problematic as the term "intelligence" is inextricably associated with human-like capabilities. While these issues have been discussed by leading researchers of AI and renowned psychologists and biologists highlighting the commonalities and differences between AI and biological intelligence, there have been few rigorous attempts to create an interdisciplinary approach to the modern problem of intelligence. This article proposes a comparative framework to discuss what we call “purposeful behavior”, a characteristic shared by systems capable of gathering and processing information from their surroundings and modifying their actions in order to fulfill a series of implicit or explicit goals. Our aim is twofold: on the one hand, the term purposeful behavior allows us to describe the behavior of these systems without using the term "intelligence", avoiding the comparison with human capabilities. On the other hand, we hope that our framework encourages interdisciplinary discussion to help advance our understanding of the relationships among different systems and their capabilities.
Keywords
Theoretical framework; Artificial Intelligence; Philosophy; Non-human intelligence
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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