CSIRO Mathematics, Informatics, and Statistics

Putting people into modelsStarting with qualitative models

Ingrid van PuttenCSIRO – Marine and Atmospheric research

(Hobart- Australia)

QUALITATIVE MODELSQUALITATIVE MODELS

MECHANISTIC MODELSMECHANISTIC MODELS

PRECISIONPRECISION

REALISMREALISMGENERALITYGENERALITY

STATISTICAL MODELSSTATISTICAL MODELS

GENERALITYGENERALITY REALISMREALISM

PRECISIONPRECISION

PRECISIONPRECISION

REALISMREALISMGENERALITYGENERALITY

Richard Levins1966

What you want from model? (Understand, Predict, Modify)

What can different types provide?(Generality, Precision, Realism)

One of a number of modeling approachesIf you use it depends on

Good for combining bio-physical and human domain – but philosophically – can we actually model humans?

Don’t need much data

Philosophical perspectiveCan we model human behaviour?

Metaphysics: never…!Behaviorism: probably…?

Behaviour shaped by response to environmental stimuliHuman beings perceive, assess, decide, and act.

Modellers need algorithms for each stage

Human beings aren’t reducible to any description.Transcendental nature of ‘self’ and cognition.

Ivan Pavlov (1849 –1936)

Aristotle PlatoBurrhus Frederic Skinner (1904 – 1990)

But how do we “observe” and interpret what human beings do

Do we need to know what goes on in the cognitive box (the brain) when

modelling people?

Assuming we can model human behaviourHow do we observed it?

Inductive reasoning

Based on observation

What’s next?

Inference of general principles or rules from specific facts

Deductive reasoning

Based on interpretation

Inference of specific facts from general principles or

rules

“Cognitive white box”“Causal black box”

Empirical heuristics- based agents

Formal logic compliant agents

Do we need to know what goes on in the cognitive box when modeling the way people make decisions?

Ask an economist ……

UncertaintyFaced with a problem

Gather all information necessary for rational

judgement

Make decision

homo economicus

Person acts rationally in complete knowledge out of self-interest and

the desire for wealth

Not much gain from knowing what goes on in the cognitive box

Gather all information necessary for rational

judgement

Make decision

Uncertainty

Heuristic(shortcut)

Amos Tversky and Daniel Kahneman (1972)

When people are faced with a complicated judgment or decision, they often simplify the task by relying on

heuristics, or general rules of thumb (shortcuts)

Psychologists say we do need to know about the cognitive box

The rules explain how people make decisions, come to judgments, and solve problemsThe rules can be learned or hard-coded by evolutionary processes.

Cross fertilization between economics and psychologyBehavioural economics

Study the effects of social, cognitive, and emotional factors on economic decisions and

resource allocation

Concerned with the bounds of rationality of the economic agents

Gather all information necessary for rational

judgment

Make decision

Uncertainty

Heuristic(shortcut)

In some situations, heuristics lead to predictable biases and inconsistencies

BIAS

In other words ……Behavioural rules in psychology work well under most circumstances,

but in certain cases lead to systematic errors or cognitive biases

Some examples of cognitive biases

Decision-making and behavioural biases

Probability and belief biases

Social biases

Memory biases

Loss aversion (endowment effect) – people demand much more to give up an object than they would be willing to pay to acquire it

Outcome bias – People overestimate small probabilities and underestimate large probabilities

Consistency bias – people often incorrectly think past attitudes and behavior resemble present attitudes and behavior.

losing $100 affects your level of happiness much more than winning $100

Low frequency events (such as smallpox, poisoning, and botulism) are overestimated (by a factor of 10), while high frequency events (such as

stomach cancer, stroke, and heart disease) are underestimated

(Lichtenstein et al. 1978

False consensus bias – People tend to overestimate the degree to which others agree with them

How do we know cognitive biases happen?

Anchoring – the tendency of people to rely too heavily, or "anchor," on one trait or piece of information when making decisions

Do experiments with people to find out how they might behave in different situations

Guess the percentage of African nations that are members of the United Nations

Was it more or less than 10%

Was it more or less than 65% 45% on average

25% on average

Before the experiment

People with higher numbers (e.g. 85) 60 to 120% higher payment

offered for the goods by people with higher numbersPeople with lower

numbers (e.g 20)

Consider whether you would pay this number of dollars for items value (e.g. wine, chocolate, computer equipment) with an unknown

Question

Question

Group 2

Group 1

Group 2

Group 1

Write down the last two digits of your social security number

Example of an experiment to establish cognitive bias

Things like confirmation bias which describes how people are more likely to search for or accept information that

supports pre-conceived beliefs.

Why do we care about cognitive biases?Raghu mentioned it – for instance climate change communication

Google search histories illustrated this:

Believers will tend to use search terms“climate change proof”

disbelievers terms such as “climate change myth”.

Both believers and disbelievers are presented with search results that support their original belief.

2011 paper on public perceptions of climate change by the CSIRO

Not only do we look for information that confirms our preconceived ideas but we also believe that everyone

else believes the same as us?

False-consensus biasWe overestimate the prevalence of our personal opinions in society while we underestimate the prevalence of beliefs that conflict with our own

78% believe climate change is real. - 63% believe that climate change is already happening; - 15% believe that climate change will happen in the next 30 years

15% are unsure if climate change is real

7% of Australians believe that climate change isn’t happening at all.

That same 7% believe that almost 48% of the population agree with them.

Some of the biases Skeptics accuse Believers of

OVERCONFIDENCE - in the predictions of their computer models.

ILLUSION OF CONTROL - Believers think that human reductions of greenhouse gases will make a large enough contribution to reduce global warming, but Skeptics think that’s an illusion.

LOSS AVERSION - Skeptics claim Believers overestimate the costs of warming (compared to the benefits).

BANDWAGON EFFECT the tendency of Believers to believe climate change is happening because many other people believe the same.

CONFIRMATION BIAS- Believers search for or interpret information in a way that confirms their preconceptions

AVAILABILITY BIAS - “because believers think of it, the believers think it must be important."

Why is it useful to know about cognitive biases

As Raghu said – we can change peoples mental models - knowing about (both sceptics and believers) cognitive bias will help

As Eileen said – we need coupled models to go into the future - knowing as much realistic information about the way we make decisions will be central to that

Qualitative modelling is one of a number of approaches to couple human to bio-physical systems

- Not data hungry- Intuitively simply - can follow easily from conceptual modelling- can be developed with the people represented in the model

As Rashid said – economics can develop incentives to change behaviour - knowing about mental shortcuts people take in making decisions will help develop incentives that work

Why is it useful to know about mental shortcuts that psychologists study (heuristics) when modelling human behaviour?

Systematically developed by Richard Levins (1966)

Sign Directed Graphs (Signed Digraphs)

Predator-Prey

Introduction to qualitative modeling

Qualitative models are based on signed digraphs

A few historically significant scientific discoveries had to happen before qualitative modelling came along

“A certain man put a pair of rabbits in a place

surrounded on all sides by a wall. How many

pairs of rabbits can be produced from that pair

in a year if it is supposed that every month each

pair begets a new pair which from the second

month on becomes productive?”

“A certain man put a pair of rabbits in a place

surrounded on all sides by a wall. How many

pairs of rabbits can be produced from that pair

in a year if it is supposed that every month each

pair begets a new pair which from the second

month on becomes productive?”

Fibonacci number sequence:1 1 2 3 5 8 13 21 34 55 89 144Fibonacci number sequence:1 1 2 3 5 8 13 21 34 55 89 144

Leonardo Fibonacci in 1202 (age 32)

Leonardo Fibonacci in 1202 (age 32)

Geometric or Exponential Increase

Liber Abaci (Book of Calculation)

Populations Increase Geometrically (e r t )Essay on the Principle of Population

Thomas MalthusIn 1798 (age 32)

"The power of population is indefinitely greater than the power in the earth to produce subsistence for man"

Resources Increase Arithmetically (x + y)

Alfred Lotka1925

Vito Volterra1926

PREY

PREDATOR

Predator-Prey

22,111 birth

d

dNN

t

N

deathd

d11,22

2 NNt

N

Lotka-Volterra type equations describe the Darwinian evolution of a population

densityCharles Darwin

22,111 birth

d

dNN

t

N

deathd

d11,22

2 NNt

N

-α1,2

0

-α1,2

+α2,1+α2,1

0

Levins 1968 Levins 1974

Community Matrix Signed Digraph

Lotka and Volterra 1925-1926Lotka and Volterra 1925-1926

Mathematical relationship

Richard Levins1966

Predator-Prey

Mutualism

Commensalism

Competition

Amensalism

Self-Effect

Qualitative modelling Positive effect

Negative effect

Community matrix - signs only

Community Matrix

3

2

1

-a11 -a12 0

+a21 -a22 -a23

0 +a32 -a33

Chan

ge in

1. Small fish

2. Large fish

3. Fishery

Due to interaction with1 2 3

Fishery

Large fish

Small fish

- - 0

+ - -

0 + -Chan

ge in

1. Small fish

2. Large fish

3. Fishery

Due to interaction with1 2 3

Self effect

Self effect

Qualitative models can identify key drivers of change and predict the direction (+, - , 0) of response to change

Press perturbation: shift in parameter leading to new equilibriumPulse perturbation: shock to population or variable leading to transient dynamics

1

Qualitative modelling can be used to identify data gaps and hypotheses for further investigation3

Qualitative models are relatively easy to produce with stakeholders (next step to building a conceptual model)

What can qualitative modelling tell you – beside increases and decreases?

“…a very underrated tool in biology and social science” (M.L. Cody 1985)

Additional benefit of qualitative modelling

Assess model stability (important for assessing the reliability of predictions) – if strong positive feedback system then unstable

2

Temperature Currents

Rainfall

Wind

Sea level rise

Cyclones & storms

Clim

ate

dri

vers

Pests & diseases

Ecosystem integrity

Retained species

Emergent species

Non-retained species

Mari

ne e

nvir

onm

ent

(eco

logic

al gro

ups)

non-fishing based recreation

Commercial fishing

Recreational fishing

Marine touris

m

Charter

fishing

Traditional owners

Aquaculture

Renewable energy

Other industrial

use

Mari

ne s

ect

ors

Australian example of qualitative model Connect climate change drivers, to marine environment and marine sectors

(‘expert model’)

-

+

++

Temperature Currents

Rainfall

Clim

ate

dri

vers

Pests & diseases

Ecosystem integrity

Retained species

Emergent species

Non-retained species

Mari

ne e

nvir

onm

ent

(eco

logic

al gro

ups)

Commercial fishing

Recreational fishing

Marine touris

m

Charter

fishing

Aquaculture

Mari

ne s

ect

ors

Wind

Sea level rise

Cyclones & storms

non-fishing based recreation

Traditional owners

Renewable energy

Other industrial

use

Build same model with community members

What did we learn?Incomplete understanding of the whole system

Will help shape communication/education/information

Commercial fishing activity

Climate change

Sea temperatur

e

Retained species

Price of fish

Profitability

Currents

Emergent species

Fish abundanc

e

The pathway by which the fishers thought climate change affected

them (fisher’s mental model)

Commercial fishing activity

Method of lease quota trade

Climate change

Sea temperatur

e

Retained species

Price of fish

Profitability

Oil & gas industry

developmentAge

Alternative income earning

options

Harbour access

channel sand build up

Public works

funding

Access to harbour

Exchange rate

Imports

Variable cost

Price of lease quota

Admin. monitoring

requirements

Quota ownershi

p

Diversification options

Exploratory licence rules

Govt dept

resources

Vessel ownershi

p

Vessel Size

Fixed cost

Currents

Emergent species

Fish abundanc

e

Fishing pressure

Season

Government TAC levels

Bank lending

rules

Family fishing history

Family quota

ownership

Pass quota down

Retirement funding options/

alternatives

Quota ownership characteristics

# 1Quota trade

characteristic# 2

Work opportunities

# 3

Exploratory fishing

# 4

Climate is not only thing that drives fishing activity (fisher’s mental model of

where it fits in)

Important to understand how these things fit together if we want to use policy to change the system - improve it –

or make it more robust

Hakes model

Merluccius capensis

Yodzis 1998

Benguela Ecosystem - effects of seal cull on hakes

(-)(-)

++(-)(-)

++

++

Example of how Qualitative models can provide powerful insight when you want to implement policy to improve the system

Mc J

Mc A

Juveniles Adults

Live in shallow water

Merluccius paradoxus

Mp J

Mp A

Juveniles Adults

Live in deep water

Punt 1997

Shallow

Deep

Hakes modelMerluccius capensis &

Merluccius paradoxus model

Benguela Ecosystem - effects of seal cull on hakes

(-)(-)

++

++(-)(-)

++

--

--

--++++

• Reduced banana prawn abundance from recruitment overfishing,• Reduced banana prawn abundance from change in environment,• Reduced banana prawn abundance from pollution.• Reduced fishing effort in Weipa.• Reduced catchability from prawns remaining inshore,• Reduced catchability from reduced aggregation or “balls”.

Weipa region

Another example of qualitative model in fisheries How QMs can address hypotheses regarding reduced banana prawn catch

What happens when the model gets perturbed

Banana Prawn Subsystem

P L P A

P J P m

Juveniles

AdultsLarvae

Maturing

P AP J

N3

N2

N1Prawn food

Prawns

Predators

Example of qualitative model in fisheries

PLPA

PJ

Pm

Nut

Nut

Op

Pr

PrPr

off-shore

in-shore

estuary Banana Prawn biological

Subsystem

Example of qualitative model in fisheries

Human system

PL

PA

PJ

Pm

Pr

Nut

Nut

Op

Pr Pr

off-shore

in-shore

estuary

Example of qualitative model in fisheries

Comcatch

CPUE

Eff

$

Environment & habitat

Biological system

Manhab

Rain E

Tur (est)

Rec (est)

Rec(oce)

CSIRO Mathematics, Informatics, and Statistics – Jeff Dambacher

Tur (oce)

Rain L Sal

PL

PA

PJ

Pm

Pr

Nut

Nut

Op

Pr Pr

off-shore

in-shore

estuary

Example of qualitative model in fisheries

Rec (est)

Comcatch

CPUE

E

$

Tur (est)

Manhab

Rain E

Rain L Sal

Environment & habitat

Biological system

Commercial fishingeconomic system

Recreational fishing system

Rec(oce)

Tur (oce)

+

-

?

0

PERTUBATION

Why use qualitative modelling?

S. Metcalf, Murdoch University

Few data required – only need signs of the interactions

Reciprocal effects

Negative effect

Fish stocking

Fish populati

on

Birth rates

Female educa-

tion

Policy present

on street

Cars stolen

Stocking of rivers with fish increases the abundance of fish

Positive effect

Police on the street will decrease the number of cars stole and if more cars get stolen this will increase police presence

Female education will decrease birthrates

1

Can investigate direct and indirect interactions and their effects on the dynamics of the system

Direct interaction

Indirect interaction

3

Any type of interaction cay be included in qualitative models (biological populations, whole ecosystems, groups of people, economic variables, nutrients, social and demographic characteristics).

2

Birth rates

Female educa-

tion Wealth

Why use qualitative modelling?

Qualitative models are excellent for producing with stakeholders (participatory modelling)4

(Participatory modeling)

Stakeholders learn more about:How to structure and formulate their ideasUnderstand situation and possible optionsHow to understand, discuss and cooperate with others

Scientists learn more about:Stakeholder’s views and social behaviorWays of translating research into policy practice

Policy makers benefit as legitimacy of models is enhancedDirect integration into the decision-making processSocial and scientific validation

Policy makers benefit from what the scientists and stakeholders have learned by developing the model together and from the legitimacy

gained through this process

Why involve the community in the modeling exercise?

QUALITATIVE MODELSQUALITATIVE MODELS

MECHANISTIC MODELSMECHANISTIC MODELSSTATISTICAL MODELSSTATISTICAL MODELS

PRECISIONPRECISION

REALISMREALISMGENERALITYGENERALITY

GENERALITYGENERALITY REALISMREALISM

PRECISIONPRECISION

PRECISIONPRECISION

REALISMREALISMGENERALITYGENERALITYRichard Levins1966

Omits small effects or large infrequent effectsFunctions often vaguely definedLoss of detail in space, time, and individual organismsPresumption of linearity and equilibriumTime lags not explicit

Weaknesses of qualitative models

Approaches to Complexity

“Making the simple complicated is

commonplace; making the complicated

simple, awesomely simple, that’s creativity.”

(Charles Mingus)

Thanks to:Jeff Dambacher (CSIRO Mathematics, Informatics, and Statistics),

Sarah Metcalf (Murdoch University),Pascal Perez (University of Wollongong)