OUR GOAL is to establish ARTIFICIAL INTELLIGENCE (AI) as a science. But right away we must ask ourselves: what precisely is AI; and how can we define it?
A simple definition of AI—reads as follows:
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
Put simply, Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in direct contrast to the natural intelligence displayed by human, animals and/or other living beings.
Overall, the traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects.
The development and application of so-called General Intelligence is among the field’s long-term goals. Henceforth, there are many different research and development approaches being followed—in order to reach this goal; including statistical methods, computation intelligence, and traditional symbolic AI.
Patently we can have two different kinds of AI. Firstly, we have embodied AI or “intelligent agents” in which the machine intelligence is inserted into the environment; and secondly we can have non-embodied AI where the machine intelligence stands apart from the environment and/or does not have any direct ability to interact with the the real world by itself.
Leading AI textbooks define an “intelligent agent”—as being any device that perceives its environment and takes actions that maximise its chance of successfully achieving its goals.
Often times this kinds of ’embodied’ intelligence has been associated with Robots, Automata and IoT Things/Systems—and herein we shall present detailed theory on all of these type(s) of Intelligent Agents—whereby much of this theory is new, and is presented here for the first time.
In the language of the present site; such intelligent agents are independent ‘thinking’ machines that posses one or more of the following decision making types: reflexive, pre-programmed and/or pro-active decision making (see AI Types and Free-Will). Whereby we define the new concepts of Situated Intelligence and Distributed Intelligence; or the embedding of intelligence and connectivity into and/or across the IoT Environment in useful ways.
AI and the Future
The field of AI has been founded on the assumption that human intelligence “can be so precisely described that a machine can be made to simulate it”.
Inevitably, this assumption raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. But once again there is much disagreement about wether or not human-like intelligence can ever be developed; and if so, how?
Patently, no matter how far one believes the field of AI can progress; one has to admit that the field somehow involves the bigger questions—such as the nature of life and the role and purpose of humanity within the universal order. Patently, AI is a multidisciplinary research area; and draws on expertise found in computer science, information engineering, mathematics, psychology, human brain studies, linguistics, philosophy and many other fields.
It is important to realise that AI, perhaps more so that any other area of human tool/ technology making activity; has often been associated with negative outcomes in humanitarian terms. For example, certain experts today consider AI to be danger to humanity if it is allowed to progress unabated and/or without (for example) large-scale government-led regulation. Other people believe that AI, unlike previous technological revolutions, will create mass unemployment.
For almost 100 years; many similar negative themes have been used as plot vehicles within Science Fiction books, comics, and movies etc; whereby technology (and especially AI) provides a direct causal link to societal dystopias.
In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computational power, gathering of big-data, deep-learning techniques and improvements in theoretical understanding in relevant fields. Really AI developments have two distinct sources as follows: firstly theoretical advances in terms of overall approach, and secondly, practical inventions such as transistors, microchips and the development of the Internet etc.
However all modern advances in AI, emanate from early theoretical ideas first introduced during the 1930s-1940s by Dr Alan Turing (1912-1954); whereby his solution to AI was named by him as a “Universal Machine“. As a direct result of Alan’s work—over the next 80 years or so—AI techniques have become an essential part of the technology industry; helping to solve many challenging problems in Computer Science, Information Technology, Robotics and the IoT etc.
Artificial General Intelligence
Over the years, many different approaches to, and types of, AI have been identified; including: Combinational, Contextualised, Situated, Augmented, Distributed, Social, and General, plus Weak/Narrow: Intelligences.
Arguments continue amongst the experts about the nature of these various concepts; and each intelligence type has multiple definitions etc. Overall, there are many disagreements about the nature of AI—what it is—how it can be developed—and including even the likelihood or possibility of us humans (somehow in a God-like manner) creating Artificial General Intelligence at any point in the future.
As a result, and unlike more established fields such as mathematics, physics, chemistry, and biology; and also many parts of the technology landscape, the fundamental axioms and/or principles of AI have yet to be established. Indeed, the development of Artificial Generalised Intelligence would perhaps require tremendous breakthroughs in fields such as the nature of Free-Will, Life and even Quantum Mechanical affects etc.
Ergo, and despite progress, perhaps the field of AI is still at a very early stage of its development—and we shall have to wait quite some time—perhaps decades or even longer—for it to crystallise into a mature field of study. Developing and/or building-out the field of AI and its various methods, sub-fields and techniques is a monumental task. Indeed it remains unknown if we humans could create—even one example of an Artificial General Intelligence. However we should perhaps consider that—big achievements come one step at a time.
Our aim here (on these pages) is to make a contribution to the development of an actual Science of Artificial Intelligence; but patently this ambitious goal will take some time to achieve—and can only be approached with the help (and significant contributions) of our expert readers. Cross your fingers!