addressing risk governance deficits with scenario modeling practices john benjamin cassel strategic...
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Addressing Risk Governance Deficits with Scenario
Modeling Practices
John Benjamin
Cassel
Strategic Foresight
& Innovation
A Major Research Project submitted indefense of a Masters of Design
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the scope
of history
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Foresight
the inverse of history
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Narratives of a great challenge
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Risk
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Nobody in their right
mindplans for thiswhen booking
a flight
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everyday infrastructures and
everyday institutions
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Infrastructural Transitions
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Inevitable Regrets
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How can institutions surviveby merit
given inevitable regrets?
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Due diligence
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Good Risk Governance
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What is good risk governance when considering a plurality of
worldviews?
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A plurality of stories suggests
scenario methods
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But the stories we tell are tangled with bad judgment
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"What is it about politics that makes people so dumb?"
-Daniel Kahneman
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"If we're so dumb, how come we're so smart?"
-Clark Glymour
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Is bad judgment fundamental or
are there structurally better ways to ask?
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The Burden of Proof is High, but Fair
"Promoters of 'debiasing' schemes should shoulder a heavy burden of proof. Would-be buyers should insist that schemes that purportedly improve 'how they think' be grounded in solid assumptions about (a) the workings of the human mind and -in particular- how people go about translating vague hunches about causality into the precise probabilistic claims measured here; (b) the workings of the external environment and -in particular- the likely impact of proposed correctives on the mistakes that people most commonly make in coping with frequently recurring challenges."-from Expert Political Judgment by Philip Tetlock
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Purpose
• Discoveryo How do we find out what we know?
• Knowledge Critique o How do we find out what we don't know?
• Analysiso What does what we know imply?
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Objectives
• Engineer scenario representation methods that allow for the capture, analysis,storage, and reuse of causal and impact information
• Develop elicitation methods that progressively delimit and arbitrate governance deficits
• Implement simulation methods capable of demonstrating plausible scenarios fromelicited causal structures
• Position uncertainty discovery as a valid governance need
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Limits
Theoretical Contributions
More of a thesis than a project
Subject matter large=contribution small
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Methodology
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Methodological ApproachLayers of Inductive Constraint
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Why Technical Methods?
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Technical methods are a means of self-skepticism
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Core
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What aspects of worldview are appropriate to distinguish?
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Distinctions
objective understanding subjective perceptions objective orientation subjective perception of objective knowledge
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Elements
objective understandingstructures, states-of-affairs, events, dependences,actions, observations, senses, and anticipations
subjective perceptions
stakeholders, rewards, and criteria
understanding of objective orientationcurrent conditions
subjective perception of objective knowledge
deferences
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Element Model
A model consists of structures, states-of-affairs,
stakeholders, rewards, criteria, events, dependences,actions, observations, senses, anticipations, and deferences
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Simulation
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But how do you get those elements?
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What is a stakeholder, anyway?
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Consider two neighboring farmers
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They hold similar stakes in some cases
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Similar Stakeholders = Similar Preferences
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But you can't get there from here
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You can discover how people generally put things together
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Non-Parametric MethodsWe can reason about the
processes by which we discover what we don't know
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Chinese Restaurant ProcessAs you ask, you discover the categories you've discovered
before, and some new ones, with diminishing returns
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Indian Buffet ProcessAs you ask, you discover the
features you've discovered before, and some new ones, with
diminishing returns
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CRP IBPAs you ask, you find categories
with features in proportion to what you've discovered before, and
some new ones, with diminishing returns
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Inference
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You may have shown that discovery processes could
generate open models of these elements, but how could open
discovery work?
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Interview as Depth-first Search(Process)
1. Create a series of iteratively more specific prompt questions– Search over the responses of each prompt with open-ended
questions composed of model elements
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Interview as Depth-first Search
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Interview as Depth-first Search(Specifics)
Event (all kinds) → Precondition• What could cause described event?• Is anything else needed to cause described event?• Are there any other causes for described event? Structure (all kinds) → Impact• As a result of being in that condition, would any of the stakeholders experience gains or losses?• Are there any potential harms to being in this condition, or any rewards for that matter?
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Interview as Depth-first Search(Tools)
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Synthesis
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Addressing the Criteria
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Addressing the Criteria
(two steps)
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Addressing the Criteria
(step one)
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Addressing the Criteria (step one)
"Promoters of 'debiasing' schemes should shoulder a heavy burden of proof. Would-be buyers should insist that schemes that purportedly improve 'how they think' be grounded in solid assumptions about (b) the workings of the external environment and -in particular- the likely impact of proposed correctives on the mistakes that people most commonly make in coping with frequently recurring challenges."-from Expert Political Judgment by Philip Tetlock
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Simplifying Assumption
A list of Risk Governance Deficits, as provided by the International Risk Goverance Council,
represent hard-won guidelines that are suitable for designing risk governance methods
In other words, if we show that we mitigate risk governance
deficits, then we have methods suitable for governing a wide range of risks
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Method of Resolution
Demonstrating interventions
in paths to potential harms
(Shown here is a mistaken perception)
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Interventions in Paths to Harm(Example 1: Standard)
A3 The omission of knowledge related to stakeholder risk A mitigation measure would need to inquire, in all states-of-affairs, who might be affected, how they are affected, and in what magnitude. It would also need to inquire who else and how else, after receiving an initial answer. The elicitation method developed here will do exactly that.
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Interventions in Paths to Harm(Example 2: Exceptional)
A5 The failure to properly evaluate a risk as being acceptable or unacceptable to society What is acceptability? One interpretation is as a separate harm resulting from the judgment of a harm. This deficit highlights the importance of continuing to ask about observations and other stakeholders even after the "damage is done". The interview protocol does this.
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Addressing the Criteria
(step two)
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Addressing the Criteria (step two)
"Promoters of 'debiasing' schemes should shoulder a heavy burden of proof. Would-be buyers should insist that schemes that purportedly improve 'how they think' be grounded in solid assumptions about (a) the workings of the human mind and -in particular- how people go about translating vague hunches about causality into the precise probabilistic claims measured here"-from Expert Political Judgment by Philip Tetlock
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Method of Resolution Reducing Interventions to Probability Scores
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Reducing Interventions to Probability Scores
1.Dependencies We would need not only to score point predictions, but would also need to score paths of causal dependencies predicting those factors.
2.Interventions We would need to elicit the conditions under which those paths are intervened upon, or severed.
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Reducing Interventions to Probability ScoresAlgorithm
Dependencies Average the predictions of weighted paths Interventions Weight the paths by the interventions of other weighted paths, dampening cycles
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Contingency
As a result of predictions occurring along a path of events, the prediction changes before the time of the prediction is due Let us call this change the contigency
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Implications
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Design Systems for Risk Governance
This work demonstrates that one can design "design methods" that address the core problems of risk governance
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Design of Foresight
How we ask the question qualitatively has quantitative consequences
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Design Statistics
Non-parametric methods imply that we can reason quantitatively
about qualitative uncertainty
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Everything is as it should be
Implicit human capabilities, such as visual, causal, and associative
reasoning, allow designers to learn in even the most difficult problem settings
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Everything is as it should be
In other words, design is still practiced by, of, and for people
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Conclusion
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Amongst inevitable regrets,institutions might yet arbitrate
worldviews fairly
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Therefore, despite changing infrastructure,
institutions can appropriately persist
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Thank you!
(Questions?)
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