module 3 week 4

programmed decisions

• repetitive and well defined, and procedures exist for resolving the problem

non programmed decisions

• novel, ill structured, and poorly defined, and no procedure exists for solving the problem

deductive reasoning

• start with hypothesis

• have a defined problem with a number of alternative solutions

• challenge: apply a rational decisions making process to identify best solution

• conclusions are right or wrong

• go from general to specific

• upside pyramid start at the top

steps for deduction

• define: ex. do you really want a partner

• disaggregate: whats the decision criteria ex. do they like cats

• data: actually dating rather than imagining people in your head

• challenge: when is good enough both good and enough

inductive reasoning

• start with poorly defined problem

• use data and observations to find what end state should be

• challenge; recognize patterns among data and drawing conclusions

• go from specific to general ( normal pyramid start from top)

• conclusions are strong or weak

challenges for induction

• incomplete information→ is biased sampling limiting information you have access to (purposeful variation, not looking for the average)

• multiple data collection methods: are people telling me what they think i want to hear (walking around, listening, observing, asking questions)

intuition

• rapid cognition

• pattern recognition

• non-conscious

holistic hunch (gut feeling)

• can be risky

• choice made from subconscious synthesis of info drawn from diverse experiences

automated expertise (gut feeling)

• can be trusted

• straightforward but partially subconscious application of previous learning

• recognition of familiar situation

Heuristics

• mental shortcuts used to simplify and speed up decision processing

cognitive biases

• systematic errors in thinking that impacts decisions and judgements

• memory, attention, attribution

• limit our ability to be objective, logical, and systematic

• can lead to poor decision making/ judgements

2 categories of biases

• information processing bias

• judging self and others

confirmation bias

• information processing bias

• we favour info that confirms our preexisting beliefs and discount evidence that does not conform to those beliefs

availability bias

• information processing bias

• we favour information that comes to mind quickly and vividly and overestimate the frequency of those events

• ex. cop job more dangerous then lumber cutting

what is representative bias

• info processing bias

• and processing error where we wrongly believe that the similarity between objects influences their probability

6 representativeness biases

• Insensitivity to Base Rates: Ignoring the actual statistical frequency of a group in favor of a descriptive stereotype.

• Conjunction Fallacy: Incorrectly assuming a specific combination of traits is more probable than a single, broader trait.

• Misconceptions of Chance: Expecting short sequences of random events to "balance out" or look representative of the long-term average.

• Similarity: Assuming that because an event looks like a specific category, it must belong to that category regardless of the odds.

• Insensitivity to Sample Size: Failing to recognize that small groups are more likely to produce extreme, non-representative results than large groups.

• Regression to the Mean: Failing to realize that an extreme performance is usually followed by a more average one simply due to luck.

Anchoring bias

• info processing bias

• we rely on the first piece of information we learn and adjust our expectations around that number

• psychological heuristic that influences the way we asses probabilities

• u grew up being told 16 is earliest you can date so that is what u enforce with your own child despite them saying 14

• combat by considering all available information

Halo effect- judging self and others bias

• when the overall impression of a person create a halo that positively biases our assessments of individual characteristics

• ex. what is beautiful is good, well behaved students are smarter

overconfidence bias

• a false or misleading assessment of our skills, intellect or talent

• we all believe were above average

illusion of control

• the tendency to overestimate ones own ability to control activities and events

• ex. throw dice harder to get higher number

Dunning-Kruger effect

• when people believe they are smarter and more capable than they really are

• loud does not equal expert

self serving bias

• the tendency to blame external forces when bad things happen and give yourself credit when good things happen

Fundamental attribution error

• The tendency to blame external forces when good things happen to others, and blame others when bad things happen

How to combat bias

• in ourselves: convince you that your cognitive repertoire could use improvement

• in others: we can develop systems to recognize bias in others

where does bias get worse

• Bias gets worse at senior leadership levels (where information is filtered)

• and when facing complex problems (where the brain takes shortcuts)