Cognitive Biases
Heuristic: mental or cognitive shortcut (“rule of thumb”) that simplifies the decision making
process
- Allows you to make faster rough decisions that are often “good enough”, but might lead
to systematic biases
Cognitive Biases: systematic error in thinking that affects the decisions and judgments that
people make
Heuristics and the 4 problems
● Problem 1: Information overload
- There is too much information to deal with so our brain uses tricks to select the
information we are most likely to use
- Downside: We don't see everything. Some of the information we filter out
is actually useful and important
● Problem 2: Lack of meaning
- We only see a tiny part of the very confusing world. To construct meaning out of
the bits and pieces that come to our attention, we fill in the gaps and map the
information to our existing mental models.
- Downside: our search for meaning can create illusions. We sometimes
imagine details that were filled in by our assumptions, and construct
meaning and stories that aren't really there
● Problem 3: Need to act fast
- We are constrained by time and information, and yet we can't let that paralyze us.
In order to act fast, we need to make split-second decisions that could impact our
chances for survival, security or success.
- Downside: Quick decisions can be seriously flawed. Some of the quick
reactions and decisions we jump to are unfair, self serving, risk averse
and counter- productive.
● Problem 4: How to know what needs to be remembered for later?
- We can only afford the bits of information that are most likely to prove useful in
the future. We need to make constant bets and trade-offs around what we try to
remember and what we forget
- Downside: Our memory reinforces errors. Some of the stuff we
remember for later just makes all of our systems more biased, and more
damaging to our thought processes
Question 1: What are heuristics, which 4 problems are addressed by using heuristics and what
are the downsides of that?
,A: Heuristics can be defined as a mental shortcut that simplifies the decision making process.
However the use of heuristics brings some problems such as information overload. This means
that, because of the amount of information that our brain receives everyday our brain chooses
the ones that we are mostly likely to use. The downside of it is that we don't really know if the
information that was cut out wont be important and the one that we retain is important at all.
Another problem is the lack of meaning. To construct meaning by what we retain of the world,
we fill the gaps using our pre-existing mental models. The downside of this problem is that it
often leads to wrongful assumptions and constructs illusions that are not really there.
The third problem is our need to act fast. Because we are being constantly bombarded with
information we don't have the time to paralyze over every bit of information. That quick thinking
could affect our chances of survival, or security. The downside of such quick thinking is that it is
often flawed and can result in unfairness and counterproductive situations.
Lastly, another problem with heuristics is how to know what needs to be remembered for later.
We can only afford to remember a certain amount of information so we are constantly making
bets and trade offs with the remember or not part of us. The downside is that our memory is
prone to reinforce errors. The stuff that we remember for later just makes all of our systems
more biased and damaging in the long term.
The Theoretical Perspectives on origin of Heuristics
● Cognitive-psychological perspective
- Capacity base frameworks: cognitive biases due to limitations in available
data/information processing capacity (“bounded rationality”)
→ Dual process framework
● Ecological Perspective
- Expertise based frameworks: correct biases due to limitations in available data
processing capacity
● Evolutionary Perspective
- Cognitive biases result from a mismatch between evolutionary developed
heuristics and current context or environment.
Problems with the theoretical perspectives on origin of Heuristics
● Experimental findings of heuristics and bias often explained by limited capacity in
processing resources, while this latter kind of capacity limitation in inferred from
empirical fact of heuristics and bias = circulus vitiosus
● Heuristics and biases also occur in relatively simple and obvious decision situations
without time pressure
● Biases are observed in the behavior of higher as well a lower animals as well as in
machine learning
,Question 2: The neuroscientific perspective on the origin of trust was proposed because other
perspectives had limitations. Explain these other perspectives and their limitations.
A: There are three main perspectives that were outbid by the neuroscientific perspective: the
cognitive psychological, the ecological and the evolutionary. The cognitive psychological
perspective declares that the cognitive biases are a capacity based framework due to limitations
in available information processing capabilities. The ecological perspective has a more
expertise based approach: correct decisions that are made heuristically are the result of
experience and expertise. Lastly the evolutionary perspective offers the idea that cognitive
biases are a result of mismatch between evolutionary developed heuristics and current context
environment. These perspectives present some limitations such as the fact that heuristics and
cognitive biases occur in relatively simple and obvious decision situations without time
pressures. Another limitation is that experimental findings of heuristics and cognitive biases are
often explained by our limited capacity of processing resources and at the same time this kind of
limitation is caused by empirical facts of heuristics and bias (circulus vitiosus). Lastly biases are
observed in the behavior of higher as well as lower animals as well in machine learning.
Neuroscientific perspective
● Biased decision making results from mismatch between the original design
characteristics of our brain as a neural network and maintaining physical integrity on the
one hand and the nature of many conceptual or analytic problems on the other.
The working of biological neural networks is characterized by 4 basic principles:
1. Association
● We have tendency to associate (unrelated) information
- Superstition biases, representativeness heuristic
2. Compatibility
● We have a tendency to give priority to information that is compatible and
consistent with present knowledge, opinions and expectations
- Confirmation bias, familiarity heuristic
3. Retainment
● We have a tendency to retain information that better could be ignored
- Anchoring bias, hindsight bias
4. Focus
● Tendency to focus on dominant information while neglecting relevant information
that is not directly available.
- Availability bias, fundamental attribution error
Question 3: Explain the 4 basic principles that characterize the working of biological neural
networks.
, A: There are four basic principles that characterize the working of biological neural networks:
association, compatibility, retainment and focus. The association principle shows that we have
the tendency to associate (unrelated) information. The compatibility principle explains our
tendency to prioritize information that is more compatible with our current knowledge. The
retainment principle exposes our tendency to retain information that sometimes should be
ignored. Lastly, the focus principle says that we have a tendency to focus on dominant
information while neglecting relevant information that is not directly available to us.
Dual vs Single process models
● Dual process assumption: intuition and deliberation are two qualitatively different
processes, characterized by fundamentally different operation characteristics, principles,
and functions.
● Single process model: no such qualitative difference. Acknowledges that one can
distinguish a more intuitive and more deliberate type of thinking and that these can be
subjectively experienced as being quite different. But this difference is a matter of degree
and not kind
Dual process models: brain structures involved
● System 1: automatic processes related to activity in limbic system;
● System 2: analytic and controlled processes related to activity in the frontal lobe;
Limbic system vs Frontal lobe
- Fast Slow
- Automatic Effortful
- Frequent Infrequent
- Emotional Logical
- Stereotypic Calculating
- Subconscious Conscious
Question 4: Explain the dual process framework and the brain structures involved. What is the
difference between a dual process model and a single process model view?
A: There are two process models: dual and single. The dual process model says that intuition
and deliberation are two qualitatively different processes, characterized by fundamentally
different operation characteristics, principles, and functions.While the single process model says
that there is no such qualitative difference. Acknowledges that one can distinguish a more
intuitive and more deliberate type of thinking and that these can be subjectively experienced as
being quite different. But this difference is a matter of degree and not kind. The dual process
system has 2 main brain structures involved: system one (automatic processes related to
activity in the limbic system.) and system 2 (analytic and controlled processes related to activity
in the frontal lobe).
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