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Fundamentals of Risk Management

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Title: Fundamentals of Risk Management


1
Fundamentals of Risk Management
2
The Ubiquity of Risks in Todays Socio-technical
Systems
  • Automobile and plane crashes
  • Toxic chemical spills and explosions
  • Nuclear accidents
  • Water and food security (contamination, shortage)
  • Genetic manipulation
  • Infectious diseases (AIDS, bird flu)
  • Global climatic change
  • Ozone depletion
  • Extinction of species
  • Oil dependence
  • War and terrorism
  • On and on and on

3
The Rational Actor Standard
  • Choice of actions
  • Range of possible outcomes
  • Assign probabilities to outcomes
  • Order outcomes according to preferences
  • Select optimal action
  • Expected value calculations

4
The Rational Actor acts
  • Action is . purposeful behavior. Or we may
    say, action is will put into operation and
    transformed into an agency, is aiming at ends and
    goals, is the egos meaningful response to
    stimuli and to the conditions of its environment,
    is a persons conscious adjustment to the state
    of the universe that determines his life.
  • Ludwig Von Mises, Human Action (1949) p. 11

5
Human action vs. Human behavior
  • Action has reasons, behavior has causes
  • Action institution, will, duty,
    responsibility, obligation, right,
    constitution, contract, custom,
    traditions, and collective choices.
  • Behavior social organization, behavioral
    measurement, human relations, reliability,
    validity, organizational design, attitude,
    human performance, power, performance
    evaluation, and leadership.

6
Risk Evaluation vs. Management A Proposed
Distinction
  • Risk Evaluation the cognitive process of
    determining or specifying a risk prior to making
    a behavioral commitment
  • Risk Management the cognitive and behavioral
    process of designing and implementing controls on
    risky systems

7
Evolution of Risk Management
  • Early humans risks small scale, local
    management relatively straightforward
  • Technology led to evolution of systems with
    larger scale, greater complexity
  • Risk evaluation and management, today define the
    key analytical lens for attempting to anticipate
    the consequences of human action in social and
    environmental systems

8
Definition of a System
  • A section of the universe which an observer
    chooses to separate in thought from the rest of
    the universe for the purpose of considering and
    discussing the various changes which may occur
    within it under various conditions (J. W. Gibbs)
  • Usual distinction made between (1) an observed
    object, (2) a perception of the object, and (3) a
    model of the object

9
A Generalized Structural Graphic of a System
Environmental boundary
Outputi
Inputs
Process
Inputt
Outputj
Inputu
Feedback
Environment
10
The Concept of a Structure
  • A generic notion the structure of a building,
    a brain, an organization, a society, a research
    design, a decision process, a system
  • A discernable (persistent) pattern or set of
    relations that connect a set of terms, nodes, or
    objects
  • Formal bodies of scientific knowledge have a
    structure

11
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12
Systems concepts provide a means of integrating
basic tools of thinking
  • Memory
  • Association
  • Pattern discernment and recognition
  • Reason
  • Experience
  • Invention
  • Experimentation
  • Intuition

13
Risk Management through Systems Control
  • Choosing the inputs to a system so as to make the
    state or outputs change in (or close to) some
    desired way. (Arbib)
  • A constraining effect on a variable
  • A directing influence on the behavior of a
    system, or the setting of the parameters of a
    system.
  • Any one-way communication, which by definition
    conditions a receiver's behavior in some
    respects, involves control (Principia Cybernetica
    Web)

14
The Concept of a Constraint
  • Limitations that preclude certain actions
  • May preclude achievement of certain objectives
  • Actions not precluded are feasible
  • Elastic (removable) vs. inelastic (not removable)
    constraints
  • Binding vs. nonbinding constraints

15
Leibigs Law of the Minimum


                                                                  
16
Large Scale Systems
  • Costs
  • Numbers of people
  • Geographical or other extent of influence
  • Volume of information required to describe what
    is happening within the system
  • Number of interaction between components
  • Size of the potential for disaster
  • Extent of consequences of systems failure.

17
The Structure of a Concept
  • Underconceptualization a problem in managing
    risk in large scale, complex systems
  • Concept a cognitively significant word or phrase
    used in a proposition to represent some aspect(s)
    of a system
  • The division of a concept C is a concept, D(C)
    is a division of C if D(C) partitions C into
    components (Warfield 1990)

18
Complexity may be conceived as
  • ..the predicament presented to the human mind
    when it encounters conceptualizations that exceed
    its unaided power to assess or evaluate.
  • John N. Warfield, Understanding Complexity
    Thought and Behavior

19
Structural Underconceptualization
  • When managing risk in complex systems, the
    formal, logical structure of the system is
    usually not specified. Why?
  • Ignorance
  • Decision-makers have diverse beliefs about the
    situation (often do not even share same
    linguistic domain)
  • Organizational linguistics
  • Differing values

20
The Genesis of Value
  • What are values?
  • Are values controlled by hereditary instincts,
    genes, and personalities?
  • Are individuals values determined by society?
  • Are any values autonomously chosen?
  • Can a unified theory of risk evaluation ever be
    obtained without answering these questions?

21
A Key to Coherence in Managing Risk in Complex
Systems
  • Recognition that there is an unavoidable trade
    off between simple assumptions and sophisticated
    models, and sophisticated assumptions and simple
    models
  • The former is more the norm (e.g. neoclassical
    and price theoretic models of economic systems
    all assume homo economicus Marxs model assumed
    communist man)
  • The latter is generally superior when dealing
    with large scale complex systems

22
Disparate Risks and Catastrophes
  • Disparate risks a serious imbalance among
    outcomes (no matter probabilities)
  • A potential catastrophe exists when risks are
    so disparate that one outcome is incomparably
    greater than the alternatives
  • Reschers principle All else equal, an action
    that might lead to a catastrophe makes that
    action ineligible (avoid any real catastrophe at
    any ordinary cost).

23
Insurance Against Catastrophe
  • Insurance as a device for reducing the prospect
    of substantial loss (a trade of hazards)
  • The value of (price the rationale actor is
    willing to pay for) an insurance policy depends
    upon the alternative actions in the choice set.

24
Risk Dilemmas
  • Sometimes, all of the alternative feasible
    actions entail catastrophe
  • In this case, the relative size of the
    catastrophe is the paramount factor
  • The distinction between catastrophe and
    acceptable risk is a judgmental issue (example of
    Japanese attack on Pearl Harbor, page 90,
    Rescher)

25
A Fundamental Principle of the Theory of Risk
  • Risk acceptability is always comparative,
    relative to the options, and thus unacceptability
    is never absolute, only relative
  • Implicit the risk-free option is, at times, not
    an element in the choice set

26
Uncertainty
  • Uncertainty indetermination through ignorance of
    otherwise, of some of the characterizing elements
    of a risk situation
  • Reschers three modal taxonomy
  • (a) Probability uncertainty (P-uncertainty)
  • (b) Result uncertainty (R-uncertainty)
  • (c) Outcome uncertainty (O-uncertainty)

27
A brief history of uncertainty
  • Plato lack of trust in sense experience as a
    basis for knowledge
  • Rene Descartes systematic doubt, and the search
    for a priori certainty
  • David Hume the problem of induction
  • Wittgenstein language games
  • Karl Popper Induction

28
P-uncertainty
  • Probabilities cannot be reliably determined
  • Insufficient data to establish relative
    frequencies
  • Insufficient theories, models, or data to
    establish likelihoods (e.g. nuclear casks)
  • Subjective probabilities
  • What probabilities does one use when evaluating
    the risk of nuclear war?

29
R-uncertainty
  • One faces outcomes with imponderable values
  • Uncertainty about how to evaluate an outcome
  • How did Truman value the loss of life when
    deciding to bomb Japan?

30
O-Uncertainty
  • Scientific knowledge is inadequate to describe
    the nature of the hazard
  • Cannot fully specify range of outcomes
  • What outcomes will follow from the US military
    invasion of Iraq?
  • What is the national security risk attributable
    to US dependence upon Mid-Eastern oil?

31
The Ecology of Uncertainty Sources, Indicators,
and Strategies for Informational Uncertainty
  • Schunn, Kirschenbaum, and Trafton effort to
    develop one taxonomy each for sources, indicators
    and strategies
  • Focus upon evaluation and management of
    uncertainty in three domains
  • a) meteorological forecasting,
  • b) fMRI data analysis
  • c) submarine operations
  • Interest in informational uncertainty

32
Information
  • Shannon, that which reduces uncertainty
  • Bateson, a difference that makes a difference
  • . equivalent of or the capacity of something to
    perform organizational work, the difference
    between two forms of organization or between two
    states of uncertainty before and after a message
    has been received Principia Cybernetica
  • Elementary unit in information theory bit, a
    difference (e.g. between a 0 and a 1)

33
Sources of Informational Uncertainty
  • Physics uncertainty
  • Computational uncertainty
  • Visualization uncertainty
  • Cognitive uncertainty

34
Physics Uncertainty is uncertainty attributable
to
  • Absence of a signal
  • Noise/bias in the signal
  • Noise/bias in the way the signal is transduced

35
Computational Uncertainty is uncertainty
attributable to
  • Unpredicted perhaps unpredictable? future
    changes in the system
  • Statistical artifacts (e.g. the imposition of
    linearity, statistical assumptions, smoothing
    operations on data)
  • Fast and cheap elaborate algorithms that require
    lots of time to run, even on high powered
    computers (more time than is available to the
    decision-maker)

36
Visualization Uncertainty is uncertainty
attributable to
  • Limits on the information that can be logically
    derived from a structural graphic
  • Sometimes information is missing from the
    structural graphic
  • Sometimes multiple dimensions are represented by
    composite indicators
  • Sometimes there are multiple graphics that
    contain conflicting information

37
Cognitive Uncertainty is uncertainty
attributable to
  • perceptual error (e.g. in encoding, storing,
    retrieving, or processing visual information from
    the measurement devices)
  • memory encoding error
  • information overload
  • retrieval error
  • background knowledge error
  • skill error

38
Uncertainty Tradeoffs
  • Tradeoffs evidently exist in which reductions in
    one source of uncertainty come at the cost of
    increases in other sources
  • Physical and computational uncertainty
  • Visualization and cognitive uncertainty
  • Memory and perception within cognitive uncertainty

39
Indicators of Uncertainty
  • See no or unusually weak patterns
  • See an impossible pattern
  • See a pattern that mismatches a known state of
    the world
  • See a pattern that is inconsistent across data
    sources

40
Strategies for Dealing with Uncertainty
  • Check likely errors
  • Focus on reliable sources
  • Adjust for known deviations from truth
  • Average across sources
  • Acquire more data
  • Gather better data
  • Bound uncertainty (satisfice)

41
Implications of Deep Similarity Between Domains
  • Taxonomies may be generalizable to other domains
  • Dissatisfaction with conventional distinction
    between internal and external uncertainty
  • Dissatisfaction with distinction between model
    errors and inherent stochastic variability
  • Minor role of linguistic uncertainty

42
Risk Management Strategies The Interrelation of
Rules
  • Three cardinal rules of risk management
  • Maximize expected values
  • Avoid Catastrophes
  • Dismiss Extremely Remote Possibilities
  • The order of preference between them is (3),
    (2), (1)

43
Risk Management Decisions
  • May be oriented toward outcomes or toward
    processes
  • Outcome orientation tends to be normative
  • Process orientation tends to be descriptive
  • Process orientation considers three stages
  • 1) Pre-decision stage
  • 2) Decision stage
  • 3) Post-decision post-decision
  • Each stage is itself composed of a series of
    partial decisions

44
The Pre-decision Stage
  • Motivated by a sense of discontent or conflict
    attributable to difference between an ideal and
    the real world (a problem)
  • The decision-maker recognizes that the ideal
    alternative is infeasible (not in the choice set)

45
The Decision Stage Sequences of Partial
Decisions
  • Choice a matter of imposing constraints upon the
    decision situation in such a way as to rule out
    alternatives
  • Alternative ways of binding the decision problem
    may be tried
  • The choice is made when constraints are imposed
    and allowed to bind upon decision situations
    until only one alternative remains
  • In Zelenys model, the operative rule is to thus
    select the alternative that comes closest to the
    ideal

46
Question I
  • Does the lack of an explanation of the genesis of
    value pose a serious threat to the orthodox
    theory of risk evaluation? If not, explain. If
    so, what in your view is the appropriate
    intellectual response?

47
Question II
  • Is there in your view a sense in which might one
    consider global security to be a matter of risk
    management? If so, in what way or ways do the
    basic concepts discussed today help to elucidate
    and examine it? If not, what alternative
    approach would you suggest other than risk
    management?

48
Question III
  • In your view, how realistic is the reasonable
    person standard at describing the psychological
    and social foundations of risk evaluation and
    management? Do you believe that risk managers
    really make autonomous decisions, or is all of
    the psychology involved in risk evaluation and
    management really social psychology?
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