Seminar Series - Dr. Jaime F. Cárdenas-García
Information and Artificial Intelligence
Information and Artificial Intelligence
Biomimetics, also known as biomimicry, is the use and implementation of concepts and principles from nature for the creation of new materials, devices and systems. Nature provides a multitude of solutions that already work for specific purposes and thus serve as models of inspiration for synthetic paradigms. This is true of the flight of birds when Leonardo da Vinci was working on his flying machines and when the Wright brothers modeled the wing cross-section of their airplanes on bird wings. Biomimetics does not mean exact reproduction of nature, as is the case of airplanes.
In a similar way, since the middle of last century, the dream of many researchers is to be able to reproduce the thinking process of humans, such as "learning" and "problem solving," using artificial intelligence (AI), sometimes called machine intelligence. Claude Shannon’s (1948) landmark paper on the mathematical theory of communication prompted establishment of ‘Information Theory’ as a discipline. Prior information theoretic ideas drove the need to develop systems that function on the basis of transmitted and processed data (such as automatic artillery installations). Prompting the need to quantify measurements of different kinds allowing discovery of the method which gives us the maximum amount of transmitted information for a given outlay of time or space or other resources. Prior to this time the need to provide a quantitative/objective appraisal of information might have existed but was not a priority. There was an implicit understanding (qualitative/subjective) of information as something that added to our existing knowledge, i.e., when ‘what we know’ has changed. In summary, the advent of systems whose input is information, reflecting the need to continue to pursue the often-unstated goal of trying to reproduce ourselves and extend our capabilities, requires newer and better ways of defining and measuring information on a quantitative/objective basis.
The goal of this presentation is to explain an information paradigm based on the definition of information by Gregory Bateson (1972), to explain the connection between information and artificial intelligence (AI). Bateson states, “In fact what we mean by information – the elementary unit of information – is a difference which makes a difference...”. As will be elucidated, Bateson information incorporates a simultaneous quantitative/objective perspective with a qualitative/ subjective perspective. Leading to the contention that Bateson information is enough to account for syntactic and semantic information. In other words, Bateson information subsumes Shannon information. Additionally, Bateson information may be used to dispute the assertion that information is a third fundamental quantity of the Universe (Wiener 1948), an incorrect widespread belief. The idea that Batesoninformation is enough to account for syntactic and semantic information results in the posing of the Fundamental Problem of the Science of Information: i.e., the problem of explaining how human beings came to our current state of phylogenetic and ontogenetic development (Cardenas-Garcia 2013; Cardenas-Garcia & Ireland 2017, 2019). How a self-referential process leads humans to develop from a state in which their knowledge of the organism-in-its-environment system is almost non-existent to a state in which the organism not only recognizes the existence of the environment but also sees itself as part of the organism-in-its-environment system. This impacts our ability to engage with the environment so as to navigate effectively through it. In this process we are able to transform our environment to make it amenable to our distinct needs. This is what we as human beings do on a daily basis, fully dependent on the Bateson information process. Recognizing this as a fundamental problem that we need to address is the first step leading to a better understanding of AI.
About the Speaker
Jaime F. Cárdenas-García in his retirement is a Visiting Research Scientist in the Department of Mechanical Engineering at the University of Maryland – Baltimore County, and a Member of the Academy of Sciences of Ecuador. After obtaining his BSME, MS and PhD degrees from the University of Maryland in College Park he joined the faculty at Colorado State University as an Assistant Professor. After which Prof. Cárdenas-García transferred to Texas Tech University where he spent the majority of his academic career as Assistant, Associate and Full Professor. Other academic appointments have been at the University of Maryland in College Park, University of Florida in Shalimar and the University of Texas in Brownsville. His research interests cover a wide spectrum in Science and the Humanities.