Ai: Cognitive Science

Intro to AI - Cognitive Science
The Cognitive Science

Society
1979
Founders:
AI: Roger Sschank & Eugene

Charniak
Psychology: Allan Collins &

Don Norman
(Thagard, 2002; last update, 2010)
Cognitive science is the interdisciplinary study of mind and

intelligence, embracing philosophy, psychology, artificial
intelligence, neuroscience, linguistics, and anthropology… The
central hypothesis of cognitive science is that thinking can best
be understood in terms of representational structures in the mind
and computational procedures that operate on those structures.
Interdisciplinarity of Cognitive Science:

Pro: (multi pluralism)
The diversity of the disciplines complement each other. Thanks to this, cognitive
science works with different perspectives and results in achieving the best possible
approach to a given aspect. The broad field suggests that it has a great number of
specialists in various sub-fields so this means that a more professional opinion is
provided on a certain topic
Contra:
There are certain sub-fields that are more “powerful” than others. Psychology is a
popular field and it dominates the field of Cognitive Science because the percentage
Intro to AI - Cognitive Science 1

of psychologists is higher than any other percentage of professionals in the
community. Moreover, other subfields namely Artificial Intelligence gain traction
meaning they receive more funds. This means the focus in the community is shifted,
and other fields like Linguistics are overlooked.
Functionalism
In philosophy of mind, defining mental states by their functional profiles (purpose),
rather than their composition.
So: what makes something a though, desire, pain, or any other kind of mental state
depends not on its internal consitution, but solely on its function or the role it plays in
the cognitive system of witch it is a part.
Stanford Encyclopedia:
This doctrine is rooted in Aristotle's conception of the soul, and

has antecedents in Hobbes's conception of the mind as a
“calculating machine”, but it has become fully articulated (and
popularly endorsed) only in the last third of the 20th century.
Though the term ‘functionalism’ is used to designate a variety of
positions in a variety of other disciplines, including psychology,
sociology, economics, and architecture, this entry focuses
exclusively on functionalism as a philosophical thesis about the
nature of mental states.
Functionalism
Functionalism is the doctrine that what makes something a
thought, desire, pain (or any other type of mental state) depends
not on its internal constitution, but solely on its function, or the
https://plato.stanford.edu/entries/functionalism/
Multiple Realisability
All mental kinds (mental states) are multiply realizable by distinct physical kinds →
A single mental kind (property, state, event) can be realised by many distinct kinds.

Distinct phisical beings (e.g.: a dog and a human) can realize the same
psychological kind (e.g.: pain)
Putnam argues that, based on multiple realisability theory, alien beigns and artificially
intelligent robots also potentially could experience same mental states as humans do
Multiple Realizability
The multiple realizability contention about the mental is that a
given psychological kind (like pain) can be realized by many
distinct physical kinds: by different brain states in earthly
https://plato.stanford.edu/entries/multiple-realizability/
Distributed Knowledge
knowledge distributed over a community of individuals, rather than being
represented in individual brains
ex1: the complexity of termites’ mounds: no singular termite knows how the structure
is supposed to look like, yet the product of their work has exactly the properties (e.g.
thermoregulation) that they need and a very complex structure
ex2: The logicians Alice and Bob are sitting in their dark office wondering whether or
not it is raining outside. Now, none of them actually knows, but Alice knows
something about her friend Carol, namely that Carol wears her red coat only if it is
raining. Bob does not know this, but he just saw Carol, and noticed that she was
wearing her red coat. Even though none of them knows whether or not it is raining, it
is distributed knowledge amongst them that it is raining. If either one of them tells the
other what they know, it will be clear to the other that it is raining.
Mental State & Brain State

Separate:
The Computer Metaphor
Brain: Hardware, Mind: Software
Describing a brain state by neural activity, but it is not understandable by humans,

whereas descibing mental states in a more meaningful way (palying solitare, reading
an article)

Functionalism
mental states are defined by their purpose and not their composure. Since all mental
states are multiply realisable by different physical beings whose brains differ, they
must not be the same as brain states. For instance, a dog and a human can feel the
same type of pain, however, their brain structure differs from each other and
therefore they don’t have the same brain states.
The same:
Mind-Brain Identity Theory
experiences that are triggered by a variety of stimuli, which we call mental states,
are processed in the brain, and therefore, are a physical part of the brain so the
brain state itself.
Critique
GPT-3 and other language models
GTP-3 - an autoregressive language model that uses deep learning to produce
human-like text. Given an initial text as prompt, it will produce text that continues the
prompt.
Such models do not understand natural language the same way humans do,
because contrary to themthey work only on the basis of form, while humans work
with form and meaning. They lack the social richness and socially situated
interactions to compreheand natural language they imitate.
Dehumanization

Emily Bender:
1. Cognitive state of falling to perceive another human as fully human
2. Acts that express that cognitive state or otherwise entail the assertion that
another human is not fully human
3. Experience of being subjected to acts that express lack of perception of one’s

humanity and’or deny human experience or human rights
In other words: cognitive process of person doing the dehumanization, act that
expresses it and the experience of being a target of it.
Computational Metaphor
Fully human
entitled to all rights recognized as human rights
equally in possesion of an internal life and point of view
welcomed and knew as one’s full self
[..] afford[s] the human mind less complexity than is owed and
the computer more wisdom than is due
It is tied to the notion of intelligence such that emotional < rational: we base
hierarchy in the society on this notion, so beings that are considered more emotional
are deemed inferior.
Therefore: animal < human, woman < man, etc which fuels problems like racism,
sexism, ableism, misogony.

*Paradoxically, according to this notion human < AI as AI is an epitome of rational
though
Lack of diversity in AI and Dehumanization

Humans tend to be narcisitic, therefore when creating new technology , it is made
most suitable for the one that created it. Predominantly white&male AI workforce
mostly doesn’t take into account the needs and mindset of people of other gender
and people of colour.
Eg: Weizenhaum’s ELIZA used white language features (Marino 2014); Siri (2011)
got African American voices only in 2021
(notice how even E. Bender only talkes about examples that are applicable in the
unated states - she is american so it is the easiest for her, but a good another
example of how problems are overlooked)
Also: there is a division in ‘male’ and ‘female’ robots based on the tasks and things
they are made to do/complete

Representation
There is no way to correctly represent everything. There will always lack a certain
group, be yet another exeption, etc. Additionally, the person collecting the data does
this from their own point of view which leads to cognitive bias.
Quotes
AI “knowing” is irrelational
Identify practical problems that could benefit from computational

solution (rather than ML solution that could benefit from
problems)
Identife scientific questions in the cognitive sciences that could

be elucidated with ML or other computational techniques

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Intro to AI - Cognitive Science

The Cognitive Science

AI: Roger Sschank & Eugene

Psychology: Allan Collins &

(Thagard, 2002; last update, 2010)

Cognitive science is the interdisciplinary study of mind and

Interdisciplinarity of Cognitive Science:

Intro to AI - Cognitive Science 1

This doctrine is rooted in Aristotle's conception of the soul, and

Intro to AI - Cognitive Science 2

Mental State & Brain State

Describing a brain state by neural activity, but it is not understandable by humans,

Intro to AI - Cognitive Science 3

Intro to AI - Cognitive Science 4

3. Experience of being subjected to acts that express lack of perception of one’s

equally in possesion of an internal life and point of view

welcomed and knew as one’s full self

Intro to AI - Cognitive Science 5

Lack of diversity in AI and Dehumanization

Intro to AI - Cognitive Science 6

Identify practical problems that could benefit from computational

Identife scientific questions in the cognitive sciences that could

Intro to AI - Cognitive Science 7

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