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Presentation at Silicon Flatirons 2010 Annual Conference “The Digital Broadband Migration: Examining the Internet's Ecosystem” 1 February 2010
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… and a star to steer her by?New ICT Governance and the Resilience
PrinciplesPierre de Vries
Sr. Adjunct Fellow, Silicon Flatirons Center
Presentation at Silicon Flatirons 2010 Annual Conference“The Digital Broadband Migration: Examining the Internet's Ecosystem”
1 February 2010
“Sea-Fever”
• John Masefield (1878-1967), English Poet Laureate, 1930-1967
I must down to the seas again, to the lonely sea and the sky,And all I ask is a tall ship and a star to steer her by,And the wheel's kick and the wind's song and the white sail's
shaking,And a grey mist on the sea's face, and a grey dawn breaking.
• Reminded as thinking of governance, “kubernan”• Tempting metaphor, but wrong– No single ship of state, no single course to agreed
destination– Will propose alternative approach
Yellow slides not shown in live presentation
New Models of Governance
Introduction
• Constant flux of new ideas for regulating ICT, internet/web
• Jonathan Sallet’s hypothesis: new models of governance are emerging– Led to Silicon Flatirons “
New Models of Governance” meta-program– Analyzed bottoms-up policy discussions in the
program, looking for top-down patterns
Sample Changes in Governance
Topic Context Object Agent Method
Cybersecurity
New threat
No counter devised
Cross-border nature
“cyberspace”
Create Nat’l Office for C’space; Cybersecurity Directorate in NSC
Increased Federal role compared to off-line
New regulations for industrial control systems
Mandate strong authentication
Network neutrality
Internet overtakes telecom network
“broadband”
“neutrality”
“network management”
Self-regulatory orgs
Shift competition responsibility to FTC
Crowdsourcing
Four Freedoms
Draft legislation
Use adjudicative powers, common law reasoning
Software patents
¼ of all issue; many patents per product; more intangible; rapid change
“software patent”
Courts vs. legislature
End the PTO monopolyDisallow software patents
«Plus ça change, plus c'est la même chose»
(?)
19th century journalist Jean-Baptiste Alphonse Karr
But:
• Nothing obvious emerged! Detail changes, no new models
• And yet… something’s going on – are we understanding it correctly? Either:– nothing’s changed– something’s changed
• Existing principles work; we’re done, move along now• New principles needed/emerging, but can’t recognize
• Guess: new underlying philosophy emerging, not overarching model
• Most obvious changes: context of governance
Changes
• Modularity• Convergence• Decentralization
• Third sector• Tempo• Scale
Cyclical
Step change
Context changes: Cycles
• Modularity– Public interfaces, standards, competition– In industry structure as well as technology
• Convergence– Old distinctions blur: silos inapplicable
• Decentralization– From centralized/hierarchical to disintermediated dumb network,
smarts at the edge• BUT
– Technology isn’t destiny: ~ technology does not lead inescapably to a ~ industry structure• Proprietary integration will hide modularity• New categories will come - “human rage to classify” – layers, new industries• Rise of online intermediaries: Google, Facebook, ISPs {cf. Paul Ohm}
• Cycles, not inevitable, one-way, monotonic development– new configuration
Context changes: Step changes
• Third sector– Rise of NGOs, non-profits and civil society: “self-governing private non-profit
organizations, pursuing public purposes outside the formal apparatus of the state” (Salamon)
– Telecom-Internet: standards from ITU to IETF/W3C/IEEE• Tempo
– William Scheuerman’s social acceleration of time• tech innovation, patterns of social change (family, workplace), everyday life via new
means of high-speed communication and transportation– Institutions not built to cope with pace of life – rise of agencies, power shift to
executive• Scale
– Huge number & diversity of apps/devices/services per person– Data aggregation/mining
• Characteristics– accelerated by internet/ICT– even if it doesn’t keep growing, unlikely to shrink: qualitative change
Complex Adaptive Systems
Cycles & phase changes
Incomplete knowledge
Cross-linked hierarchy
Novelty & surprise
Complex Adaptive Systems (CAS)
• CAS: a collection of interacting, adaptive agents– e.g. human body, ecosystems, economy
• Cyclical & step changes– similar to ecosystem cycles and state transitions: growth, maturity, collapse,
reorganization
• Incomplete knowledge– Deep uncertainty about how system works, what state it’s in, what the problem is, what
counts as a solution
• Hierarchy and cross-linking– Layers model, with linkages: security detection in network transport and in applications– Concurrent changes at different scales: video services, player plug-ins, transports
• Novelty and surprise– Rise of P2P traffic, Open Source/Linux– Unintended consequences: TA96 supposed to increase competition, but reduced it– Robust-yet-fragile behavior: e.g. subtle inconsistencies in protocol implementation or
router configuration (Pakistan YouTube)
So What?
• Internet ≠ an Ecosystem– but both have same underlying dynamics: CAS– cf. Whale ≠ Elephant: both large mammals
• Response– Take lessons from Complex Adaptive Systems theory
• Long literature: systems 50-60 yrs, complex systems 20-30 yrs, managed adaptive systems 10-20 yrs
– Focus on managed ecosystems, not autonomous closed systems (not just “nature red in tooth & claw”)
– Capture best practices in the “Resilience Principles”
The Resilience Principles
Flexibility
Delegation
Big Picture
Diversity
Why Resilience?
• Policy Imperatives: want innovation and stability BUT– Innovation is disruptive– Striving for immutability sets up the conditions for a
catastrophic collapse, e.g. fire suppression, protecting fading industries
• Resilience: “maintaining structure and function in spite of experiencing disturbances”
• Top-level rule of thumb for dealing with complexity and contradiction
• Not efficiency: cf. choosing a solution– Robust/resilient: performs reasonably well, compared to the
alternatives, over a wide range of plausible scenarios– Optimal/efficient: performs best in the most plausible scenario– Cf. Cheney “One Percent doctrine”: treat a 1% chance as a
certainty
Flexibility
• Long-term prediction is impossible; knowledge is inadequate; system adapts faster than controls can change; different parts in different stages
• “Neutral, open-ended policies. Determine ends, not means. Describe and justify the outcomes sought, not the methods to be used to achieve them”– Use principles rather than rules, e.g. solve ex post rather than guess ex
ante• Mechanisms/Examples
– Flexible-use radio licenses– Common law reasoning (Sallet, Weiser) in Network Neutrality (NN)
• Find the facts; ask if they are the same as or different from previous facts while isolating the difference between the facts that matter from those that do not; recognize the larger principle that arises from case-by-case decisions, and then, finally, ask whether the larger principle, as used in the past, still makes sense given societal changes
• Comcast NN case – styled as adjudication, but didn’t use ALJs for fact-finding– Experiment
Delegation
• Regulator only has limited control– close direct management often harmful, e.g. flood control,
government-protected rates for intl call termination; • “Harness discretion of local experts. Most problems should
be solved by the market and society, not by government. Government's role is to provide proper incentives and guidance, and to intervene to solve critical shortcomings.”
• Network neutrality example: self-regulatory orgs– Silicon Flatirons network management (Aug 2008): develop
norms and best practices, review net mgmt techniques, provide advisory opinions, enforce standards
– Verizon/Google TAGs (Jan 2010): develop best practices, act as a forum for dispute resolution, issue advisory opinions, and coordinate with standards bodies
Big Picture
• Emergent properties: overall behavior can’t be predicted from sub-systems; cannot optimize piecewise; narrow focus reduces robustness – e.g. protecting local manufacturing, 1950’s template for TDD accessibility
• “Take a broad view of the problem and solution space. Prefer generic to sector-, technology-, or industry-specific legislation.”– Particularly useful when objects of governance are changing (e.g.
periods of convergence)– Moving from stable/compartmentalized industry structure requires
new tools to account for feedback, non-linearities• Example: Simulation/modeling
– Agent-based modeling, genetic algorithms, systems dynamics– Way to grasp big picture, experiment with solutions– NN example: J Bauer and K DeMaagd (2008): genetic programming
techniques to model the co-evolution of platform operators, content providers, and consumers subject to specific policy rules governing the interactions
Diversity
• Diversity increases resilience– Biodiversity; part of value of competition
• Needs to be maintained in socio-economic system: anti-trust– Reduction in diversity amounts to an efficiency/resilience trade-off;
the resulting system is more efficient (standards, stability), but less resistant to shocks
• “Allow and support multiple solutions to policy problems. Encourage competition and market entry.”
• Examples– SMP analysis of NN: “European” approach
• Precedent in radio auctions: rules to preclude concetration– Recruiting citizenry to policy making process
• New agent in the governance mix – Crowdsourcing: grassroots organizing SaveTheInternet.com, FCC’s soliciting input OpenInternet.gov
• But difficulties: theater; interpretation of input; capture (astroturf -> cyberturf)
Conclusions
• Underlying all the point changes we’re seeing is a shift to complex systems thinking– in methods– driven by changed characteristics
• Ecosystem management provides a framework for defining and implementing new models: the Resilience Principles– Doesn’t mean previous approaches were wrong –
explains why what some were right, and guides choices for new ones to come
– Even if ICT complexity isn’t without precedent, we now have tools we did not have before
“Well, what do you know about that! These forty years now, I've been speaking in prose without knowing it! How grateful am I to you for teaching me that!”
Monsieur Jourdain in Moliere's The Bourgeois Gentleman (1670)