<p>This is an interesting proposal, but I think is not quite right when we look the definitions at the base.</p>
<p>To start <a href="https://en.wikipedia.org/wiki/Behaviorism" rel="nofollow noreferrer">Behaviorism</a> <em>assumes that <strong>behavior</strong> is either a reflex evoked by the pairing of certain antecedent stimuli in the environment, or a consequence of that individual's history, including especially reinforcement and punishment contingencies, together with the individual's current motivational state and controlling stimuli.</em></p>
<p>Form that, we could say that Behaviorism asumes that a group of people, raised on the exact same environment, perceiving the same stimuli (reinforcement and punishment) should grow showing a similar behaviour across time.</p>
<p>Also, <em>Although behaviorists generally accept the important role of heredity in determining behavior, they focus primarily on environmental events.</em></p>
<p>This focus on &quot;environment&quot; per se leaves aside the idea that each individual is unique on its thinking and perception of the world as of their response on a particular event, instead, it tries to define the individual as sort of machine that could be &quot;trained&quot; on a certain way, to act or respond on a deterministic way to a given situation, or in retrospective, act or react in a a way determined mostly, or perhaps only by the environment and previous experiences.</p>
<p>If we accept that our behaviour is entirely deterministic (shaped by stimuli - reinforcement/punishment response), then we could, in theory, teach machines human behaviour quite easily, but this is in essence wrong for two different reasons:</p>
<p>First, I believe the idea that human behaviour is merely deterministic has been debunked many times in the past for more promising theories such as the <a href="https://en.wikipedia.org/wiki/Big_Five_personality_traits" rel="nofollow noreferrer">Big five personality traits</a> for example, which states that each individual personality, or temperament is, on the more primitive sense, determine by biology, although it could be consciously trained. On the big five theory there are a base group of &quot;categories&quot; if you will, that shape personality:</p>
<ul>
<li>openness to experience (inventive/curious vs. consistent/cautious)</li>
<li>conscientiousness (efficient/organized vs. extravagant/careless)</li>
<li>extraversion (outgoing/energetic vs. solitary/reserved)</li>
<li>agreeableness(friendly/compassionate vs. critical/rational)</li>
<li>neuroticism(sensitive/nervous vs. resilient/confident)</li>
</ul>
<p>Each individual have some of these traits on a lesser or greater degree, and each one of these traits can change predisposition that each individual have to respond to a given situation. For instance a person with &quot;hight&quot; neuroticism can run and hide if notices someone else is chasing them, but a person with ver low neuroticism and maybe hight extraversion can turn around to face the aggressor.</p>
<p>Let's take a different example: imagine everyday on the way to work, you stop by the same bakery to get a muffin, your favourite could be chocolate, and every time the shop is open, you go in to take your chocolate muffin, then one day you see a sign that says &quot;50% off on vanilla muffins&quot;, would you take your favourite or would you take the discount?</p>
<p>Who would you respond to this scenario?</p>
<p>Your response can be shaped by your environment, maybe by previous behaviour, or maybe by biology, like a chocolate allergy, if there is such thing, so for each individual you'll have a 50% change to take one or the other, therefor we can argue that it is, at minimum, very difficult to predict behaviour based on previous experience with a 100% accuracy and at the most, that the Behaviourist theory is flaw.</p>
<p>Secondly, <strong>Artificial Intelligence</strong> as we know it today, is not programmable through positive reward and punishment, it works basically based on positive data using a statistical approach.</p>
<p>This is of course an over simplification but it will give you the idea of how different AI is from actually mimicking human behaviour.</p>
<p>Imagine you create an AI that can identify a cat on a picture, to do so, you'll have to provide a ton of data, for example pictures of actual cats, so you'll be &quot;training&quot; the machine to &quot;learn&quot; how a cat looks like, but in fact it uses statistical models at the bottom to measure different aspects like light, shape, size, color, etc. So when presented a landscape picture with a small cat on it, instead of &quot;ruling out&quot; everything that is irrelevant, it will look for a &quot;match&quot;, something that looks, on average, similar to the representation of a cat on its dataset; and the larger the sample, the more accurate the model becomes with time.</p>
<p>This approach is not entirely &quot;deterministic&quot; as proposed on the behaviourist field. When you ask to an AI machine &quot;are you sad?&quot;, the machine is not reflecting on past experience, emotions, personality traits or anything similar, it is looking for the average response to the same (or similar question) in it's bank of data to give you as an acceptable response.</p>
<p>In response to your original question, yes, the more &quot;deterministic&quot; approach is not the best solution for the AI problem, and it is very limited, this is how most <strong>chat bots</strong> are built, i.e &quot;if someone ask -name- you'll respond -boot-, if someone says jump, you say -no-&quot;.</p>
<p>Artificial intelligence, is not even close to &quot;mimic&quot; human behaviour; the machine will learn based on the data you provide to it, it is also a mistake to accept the response of an artificial machine as &quot;human&quot; and treat it as such.</p>

CC BY-SA 4.0
2022-07-25T14:31:53.313Z
2022-07-25T14:31:53.313Z
Jeff
<p>AI, to the level that we attempt to create it these days, involves creating neural networks that learn from stimulus (experience, data) and reinforcement. A higher score such as in a Go game, or a higher % of matched words, faces or signs seems to equate to positive reinforcement within classical conditioning.
Given that behaviourism is mostly seen as somewhat outdated, if the above makes sense, could this model of learning be limiting progress in AI?</p>

CC BY-SA 3.0
2016-02-08T09:06:02.477Z
While I agree with this general premise as I have been expressing a similar idea myself for some time -- that current AI research is too much like mimicry or cargo-cult thinking -- whether or not this approach is limiting research is probably difficult to answer since it implies knowledge of what is currently not known, at least not widely. Specifically, depending on how difficult it is to understand and reverse-engineer human thinking, it may actually be easier (and hence more productive) to mimic the external behaviour of the mind.
Michael
CC BY-SA 3.0
2016-02-08T09:09:18.787Z
Nevertheless, if I were to begin researching AI myself, I think I would begin more from the theoretical side and less from the mimicry side. The problem is that the public would rather have a prototype that appears human (in language and or body), so money is more likely to be invested into mimicry than into other approaches.
Michael
CC BY-SA 3.0
2016-02-18T17:49:11.100Z
could you give a definition/background of what behaviorism is, why it is seen as outdated, and why you think AI research is participating in it?
honi
<behaviorism><artificial-intelligence>
Is the current approach to AI learning essentially behaviourism?
Ilya Grushevskiy
# Is the current approach to AI learning essentially behaviourism?

(Asked by: username_0 on 2016-02-04)

AI, to the level that we attempt to create it these days, involves creating neural networks that learn from stimulus (experience, data) and reinforcement. A higher score such as in a Go game, or a higher % of matched words, faces or signs seems to equate to positive reinforcement within classical conditioning.
Given that behaviourism is mostly seen as somewhat outdated, if the above makes sense, could this model of learning be limiting progress in AI?

**Tags:** behaviorism, artificial-intelligence

> **Comments:**
> **username_1**: While I agree with this general premise as I have been expressing a similar idea myself for some time -- that current AI research is too much like mimicry or cargo-cult thinking -- whether or not this approach is limiting research is probably difficult to answer since it implies knowledge of what is currently not known, at least not widely. Specifically, depending on how difficult it is to understand and reverse-engineer human thinking, it may actually be easier (and hence more productive) to mimic the external behaviour of the mind.  
> **username_1**: Nevertheless, if I were to begin researching AI myself, I think I would begin more from the theoretical side and less from the mimicry side. The problem is that the public would rather have a prototype that appears human (in language and or body), so money is more likely to be invested into mimicry than into other approaches.  
> **username_2**: could you give a definition/background of what behaviorism is, why it is seen as outdated, and why you think AI research is participating in it?  

---

## 1 answers

### Answer by username_3 on 2022-07-25. Score: 1

This is an interesting proposal, but I think is not quite right when we look the definitions at the base.

To start [Behaviorism](https://en.wikipedia.org/wiki/Behaviorism) *assumes that **behavior** is either a reflex evoked by the pairing of certain antecedent stimuli in the environment, or a consequence of that individual's history, including especially reinforcement and punishment contingencies, together with the individual's current motivational state and controlling stimuli.*

Form that, we could say that Behaviorism asumes that a group of people, raised on the exact same environment, perceiving the same stimuli (reinforcement and punishment) should grow showing a similar behaviour across time.

Also, *Although behaviorists generally accept the important role of heredity in determining behavior, they focus primarily on environmental events.*

This focus on "environment" per se leaves aside the idea that each individual is unique on its thinking and perception of the world as of their response on a particular event, instead, it tries to define the individual as sort of machine that could be "trained" on a certain way, to act or respond on a deterministic way to a given situation, or in retrospective, act or react in a a way determined mostly, or perhaps only by the environment and previous experiences.

If we accept that our behaviour is entirely deterministic (shaped by stimuli - reinforcement/punishment response), then we could, in theory, teach machines human behaviour quite easily, but this is in essence wrong for two different reasons:

First, I believe the idea that human behaviour is merely deterministic has been debunked many times in the past for more promising theories such as the [Big five personality traits](https://en.wikipedia.org/wiki/Big_Five_personality_traits) for example, which states that each individual personality, or temperament is, on the more primitive sense, determine by biology, although it could be consciously trained. On the big five theory there are a base group of "categories" if you will, that shape personality:

* openness to experience (inventive/curious vs. consistent/cautious)
* conscientiousness (efficient/organized vs. extravagant/careless)
* extraversion (outgoing/energetic vs. solitary/reserved)
* agreeableness(friendly/compassionate vs. critical/rational)
* neuroticism(sensitive/nervous vs. resilient/confident)

Each individual have some of these traits on a lesser or greater degree, and each one of these traits can change predisposition that each individual have to respond to a given situation. For instance a person with "hight" neuroticism can run and hide if notices someone else is chasing them, but a person with ver low neuroticism and maybe hight extraversion can turn around to face the aggressor.

Let's take a different example: imagine everyday on the way to work, you stop by the same bakery to get a muffin, your favourite could be chocolate, and every time the shop is open, you go in to take your chocolate muffin, then one day you see a sign that says "50% off on vanilla muffins", would you take your favourite or would you take the discount?

Who would you respond to this scenario?

Your response can be shaped by your environment, maybe by previous behaviour, or maybe by biology, like a chocolate allergy, if there is such thing, so for each individual you'll have a 50% change to take one or the other, therefor we can argue that it is, at minimum, very difficult to predict behaviour based on previous experience with a 100% accuracy and at the most, that the Behaviourist theory is flaw.

Secondly, **Artificial Intelligence** as we know it today, is not programmable through positive reward and punishment, it works basically based on positive data using a statistical approach.

This is of course an over simplification but it will give you the idea of how different AI is from actually mimicking human behaviour.

Imagine you create an AI that can identify a cat on a picture, to do so, you'll have to provide a ton of data, for example pictures of actual cats, so you'll be "training" the machine to "learn" how a cat looks like, but in fact it uses statistical models at the bottom to measure different aspects like light, shape, size, color, etc. So when presented a landscape picture with a small cat on it, instead of "ruling out" everything that is irrelevant, it will look for a "match", something that looks, on average, similar to the representation of a cat on its dataset; and the larger the sample, the more accurate the model becomes with time.

This approach is not entirely "deterministic" as proposed on the behaviourist field. When you ask to an AI machine "are you sad?", the machine is not reflecting on past experience, emotions, personality traits or anything similar, it is looking for the average response to the same (or similar question) in it's bank of data to give you as an acceptable response.

In response to your original question, yes, the more "deterministic" approach is not the best solution for the AI problem, and it is very limited, this is how most **chat bots** are built, i.e "if someone ask -name- you'll respond -boot-, if someone says jump, you say -no-".

Artificial intelligence, is not even close to "mimic" human behaviour; the machine will learn based on the data you provide to it, it is also a mistake to accept the response of an artificial machine as "human" and treat it as such.


---

