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I read a really interesting article titled "Stop Calling it Artificial Intelligence" that made a compelling critique of the name "Artificial Intelligence".

  1. The word intelligence is so broad that it's hard to say whether "Artificial Intelligence" is really intelligent. Artificial Intelligence, therefore, tends to be misinterpreted as replicating human intelligence, which isn't actually what Artificial Intelligence is.

  2. Artificial Intelligence isn't really "artificial". Artificial implies a fake imitation of something, which isn't exactly what artificial intelligence is.

What are good alternatives to the expression "Artificial Intelligence"? (Good answers won't list names at random; they'll give a rationale for why their alternative name is a good one.)

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  • $\begingroup$ With artificial~made by human mind (vs emerging from nature, which kind of excludes human kind from nature, which is contradictory), it seems pretty accurate. Artificial is not isomorph to fake or imitation ! $\endgroup$
    – Soleil
    Oct 26, 2019 at 15:30

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Artificial is said to derive from the Latin word "artificium" which connotes ideas such as crafting. Thus, artificial is a correct usage, and algorithms can be regarded as "artifacts" in the context of information as opposed to physical manifestation of information (i.e. matter).

However, I agree that the use of artificial is problematic in that, should strong Artificial General Intelligence ever be achieved, there is a stigma to "artificiality" that could have implications regarding personhood.

My personal feeling is that we should be using:

  • Algorithmic Intelligence

which this is functional definition, and therefore more meaningful than "artificial". Additionally, "algorithmic" is a neutral term, and provides a very accurate description of what these systems are.


In terms of what is considered "intelligent", you may want to look at the concept of Bounded Rationality. There is no hard definition of "intelligence", just degrees of optimality in regard to decision making in a condition of uncertainty.

Because this is subjective for any problem that is not solved, modifiers are utilized, and thus we refer to AI as "strong" or "weak". These terms are also used to describe the degree to which certain types of problems (for instance a non-chance, perfect information game like Checkers) has been solved. Complexity theory will shed more light on this concept.

For more insight on "artificial", you might find this question on the philosophical origin of the Turing Test interesting, because it partly involves the meaning of a "thing". (There were multiple words for this in Ancient Greek.)

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    $\begingroup$ I don't think that "algorithmic" is a neutral term. Maybe it is a less ambiguous or more specific term than artificial. $\endgroup$
    – nbro
    Mar 29, 2019 at 12:17
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    $\begingroup$ @nbro Good point. "Algorithmic" has been getting scrutiny lately over issues like bias. (If the computationalists turn out to be right, and and human intelligence is algorithmic, the term would apply equally to artificial and biological life.) $\endgroup$
    – DukeZhou
    Mar 29, 2019 at 16:15
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Google defines 'artificial' as something created by humans rather than occurring naturally so I wouldn't quite say that it's so bad.

Given the question however, you could perhaps say "smart machines" since that's what they essentially are these days.

Artificial Intelligence is a very broad term, pre-dating modern AI, simple things such as mechanical wooden robots were considered Artificial Intelligence.

https://en.wikipedia.org/wiki/Timeline_of_artificial_intelligence

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    $\begingroup$ Why would 'smart machines' be better? Isn't that kind of ambiguous? $\endgroup$
    – Mithical
    Apr 18, 2017 at 11:11
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    $\begingroup$ I doubt Google has definitions. Please make sure to cite the original source. $\endgroup$ Nov 10, 2018 at 11:46
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There are several expressions that are often used as synonyms for artificial intelligence, but, nowadays, the most common ones are likely machine intelligence and computational intelligence.

However, these expressions are not well defined, so not everyone will agree that they are interchangeable, but we can all agree that these fields (either if we consider them the same or not) are quite related to each other (and they overlap).

Moreover, these fields also evolve over time and they embrace techniques from other fields, which makes it more difficult to define them. More concretely, initially, AI was mainly based on the manipulation of symbols and logic, but nowadays AI is mainly machine learning, statistics and, in particular, deep learning.

Furthermore, the expression artificial intelligence was apparently coined after the term cybernetics, which some people might consider the first serious attempt to building intelligent systems.

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These are correct. Artificial implies that it runs on artifically made hardware. There is no reason to distinguish between the natural processes what do the same.

Further, the term intelligence is nor realy precise. What is more/ less intelligent or has or has not intelligence among : mowgli, monkey, crow, common game bot, whatever? MAing thing, some learning on data happens here.

The best alternative would be Mashine learning, but again, that mashine like "artifically made stuff" does that is irrelevant.

So my definition is: Algorithmic Learning.

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Machine Intelligence

I believe intelligence is not a proprietary entity meant only living beings.

In fact the very origin of human intelligence is unknown. It is still not known if we can generate a brain just by fixing up the corresponding molecules of the real brain(Even theoretically). Even if we could do that does that constitute a real intelligence or artificial intelligence is still very hazy.

I think the phrase "Machine Intelligence" would sound appropriate.

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    $\begingroup$ 'It is still not known if we can generate a brain just by fixing up the corresponding molecules of the real brain' where did you get this statement? Like really if something is identical to something its behavior is also identical (identical at fundamentally quantum level) $\endgroup$
    – user9947
    Nov 9, 2018 at 19:06
  • $\begingroup$ @DuttaA True, but let's not going to quantum level as it's too complicated (We cannot have exactly same brain in quantum level due to no-cloning theorem). The main question is what after that? Do we consider "Real" intelligence or "Artificial" Intelligence is still a question. $\endgroup$
    – Trect
    Nov 9, 2018 at 19:40
  • $\begingroup$ @DuttaA Does a artificially created brain has a mind? If it does exactly the same as a normal mind then how do we differ it from a "Real Intelligent Machine" $\endgroup$
    – Trect
    Nov 9, 2018 at 19:43
  • $\begingroup$ I don't knoow why is this downvited so badly $\endgroup$
    – Trect
    Nov 12, 2018 at 9:04
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Josh Worth provides a critique for the use of the term artificial intelligence in his Stop Calling it Artificial Intelligence, but there are some caveats in the treatment of the term. (One is a typo in the URL path.)

It is not the term Artificial Intelligence that is the issue. It is what is collected under it in the media and sometimes in academic literature.

Is Artificial Unclear?

The term artificial is not particularly ambiguous or inaccurate. Artificial doesn't mean fake as Worth suggests. It simply means that it did not arise from natural processes. High end artificial flowers feel and smell like they are grown. Artificial flight is now called flying. We no longer see birds as the exclusive pilots of flight, so the word flying has changed to include artificial things called aircraft.

People don't normally make the mistake of placing the adjective artificial along side human capabilities, so there is no tendency to misnomers. There is a problem with the use of the term artificial intelligence though. Worth is correct in that overall statement. There may be two forks to the misuse of the term.

Defining Intelligence

One problem is with the term intelligence. The definitions we've seen are considerably problematic. Some are flat out wrong and can be proven so with heaps of counterexamples. Furthermore, definitions tend to be qualitative and difficult if not impossible to quantify.

Some propose the standardized testing of academia to quantify intelligence. If we use that definition of the word, from the staunch g-factor adherents, artificial intelligence is a target idea and nothing comes close to approximating it. No computer system has yet been admitted into a major university on the basis of high scores in college board testing.

If we use the ability to learn as a standard, then flies are intelligent because they frequently learn from one swat strategy changes to avoid getting squashed by the irritated person. There are a thousand other reasons why learning, by itself, is not an adequate characterization of human intelligence. A crack addict can learn how to make a purchase without holding a job. We wouldn't characterize that as intelligence, but rather dysfunction.

Excessively Inclusive Use of the Term

Another problem arises from avarice. To appear as an expert in what is perceived to be a lucrative expansion of technology, some who have no conception of the topic sometimes present conjecture as if it were peer reviewed fact. This has been typical of popular topics for centuries. There is often insufficient bandwidth of peer verification available to address even a small portion of publicly available information. Web publication has only augmented this problem.

Resulting from this coveting of expert reputation is collecting under the name artificial intelligence a number of things that are not intelligent.

  • Multi-dimensional control systems
  • Brute force searches of permutations
  • Decisions made by statistically analyzing sample data
  • Parameterized functional networks that converge to a defined optimal behavior

Those of the above that have no component of

  • Cognition,
  • Comprehension,
  • Complex modelling and use of such models,
  • Semantic mapping,
  • Rational inference,
  • Or some other clearly distinctive and broad form of adaptation

should not be included under the technology that exhibits authentic artificial intelligence. However, those that developed the theory of control systems, searches, parameterized function convergence, and statistics or developed working systems that use that theory are intelligent, just not artificial.

The above four might have terms that distinguish them from authentic intelligent systems outside the realm of biology.

  • MDC — Multi-dimensional Control
  • BSS — Brute force search
  • NBL — Network Based Learning
  • SDS — Statistical decisioning systems

It seems that terms that have three words and form distinct acronyms get further and last longer.

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