reflections on the need for seeing beyond risk assessments and

Reflections on the need for seeing beyond risk assessments and

decision analysis tools indecision analysis tools in decision-making situations

involving high risks

Terje Aven

University of Stavanger, NNorway Conference on Nuclear

Risk and Public Decision MakingDecision-Making 14-16th November 2011Paris

What is Risk?

C,UC,U

C: the consequences of the activityU: uncertainty (what will C be?) y ( )

What is Risk?

A C UA,C,U

A: initiating event C: the consequences of the activityyU: uncertainty (what will C be?)

Where is the P b bilit ?Probability ?

Risk

General How to describe orconcept describe or measure risk

U … P …

Risk description p

Specific events, consequences,

ProbabilitiesProbabilitiesfrequencies, …

(C Q )(C’, Q, K)

C’ : Specific consequences Q: Measure of uncertainty (often P)Q: Measure of uncertainty (often P)K: Knowlegde that Q is based on

Risk Risk description

Threats,

p

,hazards,

ConsequencesC

Specific events, consequences,

ProbabilitiesC Probabilitiesfrequencies, …

Uncertainty

(C U) (C Q )(C,U) (C’, Q, K)

(A C U)C’ : Specific consequences Q: Measure of uncertainty (often P)

(A,C,U)

Q: Measure of uncertainty (often P)K: Knowlegde that Q is based on

Formula Optimal/rightFormula Optimal/right decision

Risk description What is acceptableRisk description What is acceptable risk

• ------ P =1 x 10-4

Risk-based decision-making

Expected utility theory

A BB

Eu(X) = 0.3 Eu(X) = 0.5

Choose alternative B

Analysis ManagementManagement

Risk analysisRisk acceptance criteria

Cost-benefit analysisDecision analysis

Managementreview and judgment

Decision

Limitations

Uncertainties

I f iRisk Assessment

P Decision-making

Other

Informing

Other concerns

Misconception (risk-based decision-making)

Formula Optimal/rightFormula Optimal/right decision

Misconception (decision analysis)??

Formula Optimal/rightFormula Optimal/right decision

Cost-benefit analysis

n

taNPV

tt

iNPV

1 t i0 1Expected net present value = E[NPV]

Uncertainties and risk not addressedUncertainties and risk not addressed beyond expected values

x

Law of large numbers

• The average converges to the gexpected value

• (X1 + X2 + … + Xn)/n EX1(X1 X2 … Xn)/n EX1

Analysis Management

Ri k l i

Management

Risk analysisRisk acceptance criteria

Cost-benefit analysisDecision analysis

Managementreview and judgment

Decision

Expected utility theory

• E[u(X)]

Decision problem

Consequences Preferences

Uncertainties Values

Decision problem

Consequences Preferences

Uncertainties Values

U t i ti ( )Uncertainties Adequate tool (P)

Probability

R l ti fRelative frequency Interpretation

P

Jugdmental/knowledge-based

Pfg

probabilities P

Knowledge-based probability

• P(A|K) =0.1

• The assessor compares his/her uncertainty (degree og belief) about the occurrence of the event Aog belief) about the occurrence of the event A with drawing a specific ball from an urn that contains 10 balls (Lindley, 2000).

K: background knowledgeK: background knowledge

The probability of an event is the price at• The probability of an event is the price at which the person assigning the probability is neutral between buying and selling a ticket that is worth one unit of payment if the eventthat is worth one unit of payment if the event occurs, and worthless if not

Knowledge-based probability

• P(A|K) =0.1

• The assessor compares his/her uncertainty (degree og belief) about the occurrence of the event Aog belief) about the occurrence of the event A with drawing a specific ball from an urn that contains 10 balls (Lindley, 2000).

K: background knowledgeK: background knowledge

• The need for seeingThe need for seeing beyond Pbeyond P

John offers you a game: throwingJohn offers you a game: throwing a die

• ”1 2 3 4 5”: 61,2,3,4,5 : 6

• ”6”: -24

What is your risk?

Risk

• Expected value – 24 x 1/6 + 6 x 5/6 = 1– 24 x 1/6 + 6 x 5/6 = 1

(C,P):6 5/6• 6 5/6

• -24 1/624 1/6

Is based on an important assumption – the die is fair

• While probabilities can always be assigned, the origin and amount of informationthe origin and amount of information supporting the assignments are not reflected by the numbers produced

Approaches reflecting the need for seeing beyond Pseeing beyond P

Interval probabilities p

0.1 ≤ P(A) ≤ 0.5

Aven, T. and Zio, E. (2011) Some considerations on the treatment of uncertainties in risk assessmentthe treatment of uncertainties in risk assessment for practical decision-making. Reliability Engineering and System Safety, 96, 64-74.

An adjusted approach

P,E P,E UF, , F

P ProbabilitiesE Expected values

UF Uncertainty factor assessment

Uncertainty factors

• How important are they? iti it- sensitivity

- uncertainties

Uncertainty factorimportance

Degree ofsensitivity

Significant 9 3 2,3sensitivity

Moderate 8 6 1,5

Minor 7

Mi M d t Si ifi tMinor Moderate Significant

Degree of uncertainty

Risk descriptions

P E S UP,E S UF

KK

Decision problem

Consequences Preferences

Uncertainties Values

Uncertainties Adequate tool (P)

Preferences, values Tool

Integration

Formula Optimal/rightFormula Optimal/right decision

Analysis Management

Ri k l i

Management

Risk analysisRisk acceptance criteria

Cost-benefit analysisDecision analysis

Managementreview and judgment

Decision

• Analysis informs, nothing more

• Always needs to see beyond the analyses

• Improvements of the analyses• Improvements of the analyses

The balance

Development - Protection

U

PreferencesPreferencesvalues

Decision analysis: yintegration

Analysis Management

Ri k l i

Management

Risk analysisRisk acceptance criteria

Cost-benefit analysisDecision analysis

Managementreview and judgment

Decision