Reflections on the need for seeing beyond risk assessments and ...

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14 Nov 2011 ... beyond risk assessments and decision analysis tools in decision analysis tools in decision-making situations involving high risks. Terje Aven.
Reflections on the need for seeing beyond risk assessments and decision analysis tools in decision-making situations involving high risks Terje Aven University of Stavanger, Norway Conference on Nuclear Risk and Public Decision Making Decision-Making 14-16th November 2011 Paris

What is Risk?

C,U

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

What is Risk?

ACU A,C,U

A: initiating event C: the consequences of the activity y U: uncertainty (what will C be?)

Where is the P b bilit ? Probability

Risk

General concept

U…

How to describe or measure risk

P…

Risk description p

Specific events, consequences, Probabilities frequencies, …

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

Risk Threats,, hazards, Consequences C

p Risk description

Specific events, consequences, Probabilities frequencies, …

Uncertainty

(C U) (C,U)

(C Q (C’, Q, K))

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

Formula

Optimal/right decision

Risk description

What is acceptable risk

• ------ P =1 x 10-4

Risk-based decision-making

Expected utility theory

A

B

Eu(X) = 0.3

Eu(X) = 0.5

Choose alternative B

Analysis

Risk analysis Risk acceptance criteria Cost-benefit analysis Decision analysis

Management Management review and judgment

Decision

Limitations

Uncertainties Risk Assessment

P Other concerns

I f Informing i

Decisionmaking

Misconception (risk-based decision-making)

Formula

Optimal/right decision

Misconception (decision analysis)??

Formula

Optimal/right decision

Cost-benefit analysis

NPV 

n



t0

at t 1  i 

Expected net present value = E[NPV] Uncertainties and risk not addressed beyond expected values

x

Law of large numbers

• The average converges g to the expected value • (X1 + X2 + … + Xn)/n

EX1

Analysis Risk Ri k analysis l i Risk acceptance criteria Cost-benefit analysis Decision analysis

Management Management review and judgment

Decision

Expected utility theory

• E[u(X)]

Decision problem

Consequences

Preferences

Uncertainties

Values

Decision problem

Consequences

Preferences

Uncertainties

Values

U Uncertainties t i ti

Adequate tool (P) ( )

Probability

Relative R l ti frequency f Interpretation Pf

Jugdmental/ knowledge-based g 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 A with drawing a specific ball from an urn that contains 10 balls (Lindley, 2000).

K: background knowledge

• 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 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 A with drawing a specific ball from an urn that contains 10 balls (Lindley, 2000).

K: background knowledge

• The need for seeing beyond P

John offers you a game: throwing a die

• ”1 1,2,3,4,5 2 3 4 5”:: • ”6”:

What is your risk?

6 -24

Risk • Expected value – 24 x

1/6 + 6 x 5/6 = 1

(C,P): • 6

5/6

24 1/6 • -24

Is based on an important assumption – the die is fair

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

Approaches reflecting the need for seeing 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 assessment for practical decision-making. Reliability Engineering and System Safety, 96, 64-74.

An adjusted approach

P,E ,

P,E ,

UF

P E

Probabilities Expected values

UF

Uncertainty factor assessment

Uncertainty factors

• How important are they? - sensitivity iti it - uncertainties

Uncertainty factor importance Degree of sensitivity

Significant

9

3

2,3

Moderate

8

6

1,5

Minor

7 M d t Moderate

Si ifi Significant t

Mi Minor

Degree of uncertainty

Risk descriptions

PE P,E

S K

UF

Decision problem

Consequences

Preferences

Uncertainties

Values

Uncertainties Preferences, values Integration

Adequate tool (P) Tool

Formula

Optimal/right decision

Analysis Risk Ri k analysis l i Risk acceptance criteria Cost-benefit analysis Decision analysis

Management Management review and judgment

Decision

• Analysis informs, nothing more • Always needs to see beyond the analyses • Improvements of the analyses

The balance

Development - Protection

U

Preferences values Decision analysis: y integration

Analysis Risk Ri k analysis l i Risk acceptance criteria Cost-benefit analysis Decision analysis

Management Management review and judgment

Decision