{"id":1690,"date":"2025-12-20T12:24:58","date_gmt":"2025-12-20T08:54:58","guid":{"rendered":"https:\/\/shamizi-ai.com\/?p=1690"},"modified":"2025-12-20T12:26:03","modified_gmt":"2025-12-20T08:56:03","slug":"what-is-true-intelligence","status":"publish","type":"post","link":"https:\/\/shamizi-ai.com\/en\/what-is-true-intelligence\/","title":{"rendered":"What is True Intelligence?"},"content":{"rendered":"

What is True Intelligence?<\/span><\/h1>\n

By: Mahmood Shamizi<\/span>
\nIntroducing the writer<\/span>
\nThe author of this article has written some more articles and short essays<\/span>
\non Artificial Intelligence (AI) and throughout all these essays the<\/span>
\npossibility of creating an artificial true intelligence is discussed which later<\/span>
\nleads to a new discovery on the nature and the essence of Intelligence.<\/span>
\nThe best article written by this writer related to the same topic was titled<\/span>
\n“Non-Mechanized Vision”. This was presented in an International<\/span>
\nConference called Machine Vision Image Processing and Applications,<\/span>
\nM.V.I. P2001 held in Birjand from 7- 9 March 2001, which was very well<\/span>
\nreceived by the renowned professors in the same discipline. A letter of<\/span>
\nappreciation was later written and given to me by the secretary of the<\/span>
\nConference. In the introductory session, a sample robot was demonstrated<\/span>
\nin the work shop of the conference that was working on the very same<\/span>
\nprinciples and was able to interpret \/ analyze the input data.<\/span>
\nWhat is the True Intelligence?<\/span>
\nMy goal in writing this article is to present a concise and accurate<\/span>
\ndefinition on Intelligence; either artificial or natural. This definition will<\/span>
\nbe henceforth referred to as ‘true intelligence’ to imply the qualitative<\/span>
\ndifference between ‘true intelligence’ and machine-like actions.<\/span>
\nShould we fail to define a precise border line between the meanings of true<\/span>
\nIntelligence and mechanized actions and define the distinct\/clear<\/span>
\ncharacteristics of both in order to differentiate them from one another, we<\/span>
\ncannot be optimistic on the continuation of scientific advances in AI.<\/span>
\nOne of the major factors that has prevented us from doing proper research<\/span>
\non the true nature of Intelligence, originates, in my opinion, from the fact<\/span>
\nthat Artificial Intelligence experts are not so keen on analyzing the true<\/span>
\nmeaning of Intelligence and that they prefer to concentrate on studying<\/span>
\nnon-intelligent systems, control systems, and their pertinent governing<\/span>
\nlaws. This, I believe, is most certainly a diversion from the main idea and<\/span>
\ninsufficient to define Intelligence, for in non-intelligent systems the<\/span>
\ncapability of creating a sophisticated behavior does not exist and that every<\/span>
\nbehavior has already been thought of and preset in the system as an inbuilt<\/span>
\nproperty into the system by the designer. But a true intelligent<\/span>
\nsystem should, itself, be a creator and developer of new<\/span>
\nbehaviors. Therefore, the governing laws in such systems will have<\/span>
\nqualitative differences with other systems. Thus, the expert must have<\/span>
\nstudied the important issue of the mechanism of creation, the way which is<\/span>
\ndemonstrated, and the origin of emergence of intelligent deeds<\/span>
\nTo take a true intelligent system equivalent to a mocking system on one<\/span>
\nhand and the efforts made by some experts to simulate intelligent<\/span>
\nbehaviors by robots on the other, has made the study of ‘true intelligence’<\/span>
\nless appealing. Therefore, scientists are perhaps losing interest in the<\/span>
\nrealistic meaning of the true Intelligence. It should be added here that<\/span>
\nobviously, seeing similar behaviors from two systems does not imply that<\/span>
\ntheir internal construction are also the same. The two mechanisms may<\/span>
\nlook alike, but they surely have major qualitative differences.<\/span>
\nIn other words, it is possible to see an intelligent act rendered by a nonintelligent<\/span>
\nsource and actually achieve the desired goal, but we may also<\/span>
\nsee an intelligent system that may experience an undesirable result from a<\/span>
\nwrong action. It is therefore concluded that one must not conclude that a<\/span>
\nsystem is intelligent simply because it has rendered a correct action or,<\/span>
\notherwise, non-intelligent simply because it has made a false move. One<\/span>
\nmust look into the mechanism of the original selector and ascertain if the<\/span>
\nsystem is actually aware of the reason why a particular action was taken or<\/span>
\notherwise. If not, the action has been a hap hazard or machine-like one and<\/span>
\nthat it has been made blindly or automatically. Because the system itself<\/span>
\ndoes not know why it has executed a particular action and is not even<\/span>
\nconscious if the act has taken place, for it has done a compulsory task.<\/span>
\nBut if a system actually knows why it has decided and rendered a particular<\/span>
\njob by its own reasoning, it can be said that the job has been done wisely<\/span>
\nand out of its own free will. Therefore, it is justified to say that the action<\/span>
\nhas been carried out deliberately and intelligently.<\/span>
\nTo prove this statement, two reasons can be given;<\/span>
\n1. If for a sophisticated question a wise answer were already<\/span>
\ninstalled in a computer, it is only obvious that the given wise answer<\/span>
\nis not originated out of the computer’s awareness, intelligence, talent<\/span>
\nand comprehension. Moreover, the replying mechanism is not<\/span>
\ncomparable to that of a scientist. Because, the relationship between<\/span>
\nthe question and answer is not at all based on the knowledge and<\/span>
\nintelligence, but it is based on the designer’s choice who has already<\/span>
\npreset the answer within the system. Such systems are not aware or<\/span>
\nconscious as to why they have given the right answer or have made<\/span>
\nthe right move. If we let a computer be free to chose the right<\/span>
\nanswer amongst few optional answers in order to find the true<\/span>
\nanswer by trial and error method, we can justifiably assume that the<\/span>
\nchoice of an answer will not be made according to the meaning of the<\/span>
\ntext and\/or the content of the answer, because the answer(s) are<\/span>
\nalready preset in the system by the designer.<\/span>
\nIf some people still persist that intelligence has similar features to<\/span>
\nabove, the examples of doors that are automatically opened when<\/span>
\napproached by a person as well as the reaction of a thermostat to<\/span>
\nheat must also be counted as the intelligence of the automatic door<\/span>
\nor the reaction of thermostat. The expansion of materials as a result<\/span>
\nof temperature rise can also be argued as being an intelligent act\u2026<\/span>
\nIn this case, a great many physical and chemical phenomena may be<\/span>
\ninterpreted as some type of intelligence and thus devaluate the<\/span>
\nconcept of the intelligence down to include simple substances like,<\/span>
\nmetals, minerals and so on.<\/span>
\nWhere has this degradation and trivialization of the concept of<\/span>
\nintelligence originated from? This originates from the fact that we<\/span>
\nhave not been able to define a distinct border line between the<\/span>
\nconcept of the truly intelligent systems and unintelligent systems<\/span>
\nand provide a qualitative characteristic for differentiating the true<\/span>
\nintelligence from the systems that render machine-like, reactionary<\/span>
\nand blind manifestations.<\/span>
\n2. The present approach to the meaning of Artificial Intelligence in<\/span>
\nthe scientific societies focuses more on its action oriented aspect<\/span>
\nnowadays rather than its operation oriented aspect, whence it is<\/span>
\nknown that operational aspect is not one of the fundamental<\/span>
\nconditions for an intelligent entity.<\/span>
\nLet us visualize an intelligent entity that is busy observing a far off<\/span>
\nenvironment to analyze and understand all that is going on there,<\/span>
\nwithout intervening in that environment in order to determine the<\/span>
\nprevailed governing laws. This is Just like a human being who is<\/span>
\nwatching heavenly bodies through a telescope to discover the<\/span>
\nprevailed governing relations without actually intervening in the<\/span>
\nenvironment.<\/span>
\nTo define intelligence, we must not, therefore, put too much stress<\/span>
\non its operational-orientation aspect, despite the fact that having<\/span>
\noperational ability helps the system to examine its own ideas which<\/span>
\nwill lead it to acquire better and more precise know-how of its own<\/span>
\nenvironment.<\/span>
\nTherefore, observing intelligent and correct behaviors from a system<\/span>
\ndoes not substantiate the system’s intelligence and one must look<\/span>
\ninto its internal structure and its mechanism of selecting a course of<\/span>
\nan action and whether it is originated out of the system’s awareness<\/span>
\nor otherwise. This awareness is only possible if the system were<\/span>
\nable to analyze the acquired information received from the<\/span>
\nenvironment by itself and can find meaningful relationships between<\/span>
\nthe cause and the effect within the environmental accidents. In other<\/span>
\nwords, the system should be able to create models, no matter how<\/span>
\nincorrect, on the basis of its own observations from the<\/span>
\nenvironment. Then the system should create a valuable idea from its<\/span>
\nown impression and launch it as a desired target. It will then look<\/span>
\nfor finding and linking appropriate tools to reach that goal and<\/span>
\nthereby create an operational algorithm to fulfill that whim.<\/span>
\nPlease note one of the major characteristic of an intelligent system is:<\/span>
\ncreation of a goal before devising an operational algorithm.<\/span>
\n\u0001<\/span>
\n\u0001 \u0001\u0001<\/span>
\n\u0001 We can now present a definition for intelligence that: ‘whenever a system<\/span>
\ndiscovers an order in the data that it receives and thus becomes able to<\/span>
\ndetect conditions that have applications in guiding the system to its goals<\/span>
\nand values, it can be said that system has virtually given meanings to the<\/span>
\ndata or has explained the data for itself;”<\/span>
\nTrue Intelligence”.<\/span>
\nTherefore, it has found new connections between the incoming input<\/span>
\ndata and an internal value and that it has interpreted the incoming<\/span>
\ninput data into a bunch of useful information for its own self. This<\/span>
\ncapability of the system in acquiring actual know-how is equivalent<\/span>
\nto constructing a mental model from its environment. Obviously,<\/span>
\nfull compatibility of a mental model with the current truth in the<\/span>
\nenvironment is not imperative but having such capability is a reason<\/span>
\nfor the existence of true intelligence in that system.<\/span>
\nWhenever a designer anticipates certain reactions of the system with<\/span>
\nrespect to different inputs, no more ideas or even no new algorithm<\/span>
\nwill be developed or created its realization. Consequently, all the<\/span>
\nsystem’s reactions will be compulsive, machine-like and blindfolded.<\/span>
\nWe can only call a system intelligent that is free to take any<\/span>
\nactions and interpret the input data freely, meaning that<\/span>
\nrecognition is only made by the system itself and that the selection of<\/span>
\nthe course of actions is made based on the impression and<\/span>
\nunderstanding of the system from its environment. Further, the<\/span>
\nusefulness of the actions is judged according to the system’s selection.<\/span>
\nOn the contrary, if we force a system to follow the programs and<\/span>
\nalgorithms installed in it, the liberty of action would be obscure &<\/span>
\nmeaningless. When a system is not free in making decisions and<\/span>
\nselecting its own course of actions, how else can it manifest its power<\/span>
\nof creativity, talent, inference, and intelligence?<\/span>
\nIt may seem impossible to construct a system like above, due to the<\/span>
\nfact that there is some kind of antagonism in above remarks and it<\/span>
\nmay seem that we are trying to write an algorithm for a system that<\/span>
\nis not obligatory for it to abide or to obey. Alternatively, it may seem<\/span>
\nthat we are developing a system without an algorithm.<\/span>
\nBut with a little care we’ll see a delicate and mid- way solution to<\/span>
\nescape from the above paradox, and that is to say that we want to<\/span>
\nwrite an algorithm that is able to create and construct other types of<\/span>
\nalgorithms itself by forming a mixture of the system’s observations<\/span>
\nand past experiences. This algorithm would be the decisive factor of<\/span>
\nthe deeds and behaviors of the system, of which the designer would<\/span>
\nhave no more knowledge. For this very reason, the system’s<\/span>
\nreactions cannot be anticipated. Although the evolved algorithm<\/span>
\nmay not be a perfect one in the beginning, the system will lead itself<\/span>
\ntowards sophistication provided that the road of improvement and<\/span>
\ndialectic evolution were left open. From then onward, the system<\/span>
\ncan create logical cells and thereby succeed in making mental models<\/span>
\naccording to its observations from the environment.<\/span>
\nOnly a system like above would be capable of producing ingenious<\/span>
\nsolutions and new ideas for problems with the help of its own<\/span>
\nabilities and the knowledge that it had acquired. One must not<\/span>
\nforget this important issue that for an intelligent system as such, the<\/span>
\nold and obvious ideas of ours are all new discoveries for the system,<\/span>
\nbecause it has discovered and understood them on its own and that it<\/span>
\nhas created them afresh by itself. This ability of creating ideas<\/span>
\nliberates us from installing logics or the governing laws of<\/span>
\nenvironment into the system, and if the system were placed in an odd<\/span>
\nand different environment, it will be well able to extract the<\/span>
\ngoverning laws of that new environment on its own.<\/span>
\nExpansion of created algorithms in the system will be of two types:<\/span>
\nFirst Type: Cognitive:<\/span>
\nExpansion of the created algorithms to describe the input data<\/span>
\nand to upgrade the ability of producing links between the goals and<\/span>
\nthe received input data and how this input data are interpreted and<\/span>
\nthe processing method of this input data are processed of explaining<\/span>
\nthe input data are analyzed. In fact, interpreting the input data and<\/span>
\ncomprehending the location and the atmosphere in which the system<\/span>
\nis situated is the reason of constructing a mental model from the<\/span>
\nenvironment and more perfect ideas.<\/span>
\nType 2, Behaviorist:<\/span>
\nAlgorithm expansion in order to implement ideas in the environment<\/span>
\nthrough gaining experience in operational steps means: “the ability<\/span>
\nof creating links between the tools and requirements or<\/span>
\nideas”. Thus, if a system acts on the basis of its observations,<\/span>
\nimpressions, and inferences, then it has the freedom of will, that is to<\/span>
\nsay, its reactions cannot be speculated just by its original in-built<\/span>
\nalgorithms. Similarly, it is not possible to speculate how the input<\/span>
\ndata were processed. In other words, the exact speculation of its<\/span>
\nreactions is not possible due to the following reasons:<\/span>
\na) Designer is not aware of the system’s observations throughout<\/span>
\nits life span.<\/span>
\nb) Designer does not know the hierarchy, and the type of the<\/span>
\nobservations made, and the incidents that the system has been<\/span>
\nencountered with.<\/span>
\nc) Designer does not know how the system has analyzed its past<\/span>
\nobservations<\/span>
\nd) Designer is not familiar with the governing laws in the<\/span>
\nenvironment wherein the system is situated.<\/span>
\ne) Designer is not familiar with the new values that are<\/span>
\npermanently produced based on the mental functions, reasoning,<\/span>
\nand studies made by the system.<\/span>
\nf) Inability of the system in grasping precise understanding with<\/span>
\nabsolute truth as well as flawless impressions from the current<\/span>
\nlogic in the environment will cause some erroneous interpretation<\/span>
\nin explaining the governing environmental relations. Therefore,<\/span>
\nit is certain that some differences will exist between the methods<\/span>
\nof reasoning and inferences of the designer and that of the system,<\/span>
\nwhich implies freedom of reasoning and thoughts of the<\/span>
\nentity. In other words, the types of the acquired impressions and<\/span>
\nerroneous actions of two intelligent systems cannot possibly be<\/span>
\nthe same everywhere.<\/span>
\n(1)<\/span>
\nThe overall conclusion is that one can not rely on mathematical models to<\/span>
\nbuild such a system. On the other hand, the current neural networks do<\/span>
\nnot serve our purpose either, since their reactions are predictable and that<\/span>
\nthey are bound to comply with the certain mathematical rules. Besides, the<\/span>
\nknown logical mechanism of theirs do not allow a system be created with<\/span>
\nthe freedom of will, but it is possible to develop a backbone that would give<\/span>
\nbirth to any kind of algorithm that is necessary and let its cells to undergo<\/span>
\na dialectic growth and thereby develop large textures that are open to any<\/span>
\ndevelopment for the system to meet its appropriate demands. Due to the<\/span>
\nuncertainty of its internal logics<\/span>
\n(2)<\/span>
\nIt is therefore seen that to construct an intelligent system, mathematical<\/span>
\nmodels can not be relied on. Then, the currently used neural networks<\/span>
\nmay not be deployed because neural network’s reactions are<\/span>
\npredictable. Thus, if a system were obliged to comply with mathematical<\/span>
\nand predictable laws, while being aware of the logical performance<\/span>
\nmechanism, it will no longer be a system with freedom of action. But we<\/span>
\ncan write a basic algorithm to form a backbone for production of any<\/span>
\nalgorithm thereafter for dialectic growth of its cells and large textures,<\/span>
\nsuch that to keep the evolution path open for creating various assemblies<\/span>
\nthat are appropriate for the system’s needs.<\/span>
\nDue to uncertainty of the internal logics and non-dogmatic mental rules in<\/span>
\nsome of the beliefs, the system hesitates and is unsure on the outcomes of<\/span>
\nits decisions.<\/span>
\nThis hesitancy is another reason why the evolution path is being left open,<\/span>
\nand a reason for freedom of choice to select any possible rout. In fact, only<\/span>
\na system like this has the freedom of will and thought.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

What is True Intelligence? By: Mahmood Shamizi Introducing the writer The author of this article has written some more articles and short essays on Artificial Intelligence [\u2026]<\/span><\/p>\n","protected":false},"author":1,"featured_media":1279,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1690","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles"],"_links":{"self":[{"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/posts\/1690","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/comments?post=1690"}],"version-history":[{"count":3,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/posts\/1690\/revisions"}],"predecessor-version":[{"id":1693,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/posts\/1690\/revisions\/1693"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/media\/1279"}],"wp:attachment":[{"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/media?parent=1690"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/categories?post=1690"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/shamizi-ai.com\/en\/wp-json\/wp\/v2\/tags?post=1690"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}