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PLANNING FOR DIGITAL SELF-GOVERNANCE

Copyright (c) 2015. Michael Burns. All rights reserved.

Prepared by Michael Burns

A proposal to create a logical technological framework for mitigating complex policymaking and agency management at the local, state

and federal level.

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CONTEXT"You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete." --Buckminster Fuller

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INTRODUCTIONMichael Burns is a digital marketing strategist and writer with more than 14 years of diverse experience. His work involves consulting with a variety of companies ranging from start-ups and digital agencies to Fortune 500 companies.

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MISSIONTo develop a practical roadmap that leads to decentralized self-governance that relies on a semi-autonomous technological framework to minimize or eliminate errors in policy decisions, while improving transparency and performance with reduced human involvement.

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PURPOSE1. To begin an important public dialog on what it will take over the coming decade to

optimize the way we govern that is more consistent with the nature of technology.

2. To establish better strategies to leverage data in a more responsive manner to determine policy changes more immediately, and to determine when it is inappropriate for human decision-making to prevail in simple to complex policy issues.

3. To divest poorly performing policies into a more transparent, technology-driven platform that lends itself to a decentralized, self-correcting system—ultimately to achieve a more predictable form of governance.

COMPETITIVE LANDSCAPE

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MediaSpecial Interests

Corporations

Total Control

FederalState

CountyMunicipalTownship

School Districts

Influences & Attributes

Facts Numbers

LogicMarkets

InnovationStakeholders

NimbleBottom-upElasticityAutonomy

OptimizationThriving Economies

Influences & Attributes

MythEmotion

PropagandaAuthority

RegulationIncrementalTop-down

BureaucracyParasitesCoercion

FragmentationFailed States

Total Freedom

Our Human Governance Dilemma

IndividualsFamiliesSmall Businesses StartupsCommunitiesNetworks

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PAIN POINTS• Human beings are not learning quickly enough from the mistakes of the past.

• The changing of the guard, whether by majority or by individual office holders, has not resulted in positive transformations at the federal level, and in some state legislatures.

• Policymakers are the most prone to compromise and manipulation, cronyism and horse-trading, rather than relying on a strong adherence to facts, numbers, and logic.

• The “50 Laboratories of Democracy” experiment has largely failed as modern society has become more complex. Lawmakers rely on conjecture, anecdotal information, biased studies, or model legislation without a complete view of data, perpetuating failed policies, which then trigger federal involvement to create further problems.

• The pace of change in government is still far too slow compared to the pace of the private sector, mired in unnecessary bureaucracy and influence-peddling by special interests, when there are examples present throughout the world that could be adopted quickly without the common hurdles which stifle innovation.

COMMON PERCEPTIONS

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VersusGovernment and the people Old ways of thinking

Tools & Devices Technology

Data Machine Learning

REALITY

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VersusGovernment & Special Interests

The Individual

Tools & DevicesTechnologyData

KEY PROBLEMLeveraging the core influences and technology that will bring us to a

predictable, self-governing system—without the involvement of the status quo.

The Individual

Tools & Devices Technology Data Machine Learning

Competitive Economies

PROPOSED SCENARIO

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Identifying and supporting the influences that champion a predictable and competitive self-governing system.

The Individual

Work networksData

Social networks Learning networks Business networksData Data Data

Hyper-local networks for self-governing, competitive economies Defined and controlled through opt-in, voluntary participation and

competitive forces

Tools & Devices Technology Data

Machine Learning Machine Learning Machine Learning Machine Learning

Competitive Economies

BUT WHAT ROLE FOR STATE & FEDERAL GOVERNMENT?

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The Individual

Solvent states play a supporting role in competitive markets by automatically applying the policy strategies of top performing state economies—no human involvement in manipulating policy, with all non-competitive

agencies and services privatized for optimal performance, and non-solvent states reorganized into smaller states or territories.

With decision-making reduced to autonomous and self-correcting systems, state

and federal government will have a greatly reduced role to play.

Military & Sovereignty

Data NetworksTechnology

DUMBING IT DOWN

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MORE COMPETITIVE

IndividualsSmall businesses

Startups

MORE CONTROLLING

State governmentFederal governmentCounty government

Municipal government

Self-evident facts:

1. Humanity is not learning quickly enough from history.2. Lack of understanding of government always leads to more waste, fraud

and abuse.3. Nimble, decentralized systems are always faster and more competitive.

COMPETITIVE ECONOMIES

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MORE COMPETITIVE

SwitzerlandSingapore

United States Hong Kong SAR

GermanyNetherlands

JapanFinlandSweden

United KingdomNew Zealand

UAE

MORE CONTROLLED

ChinaVenezuela

CubaNorth Korea

DEFINING COMPETITIVE GOVERNANCE

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• Greatly reduced role of government• Faster and more competitive due to lower regulatory

burden• Respect for the Rule of Law• Lower taxes• Legal systems that do not impose an extended

burden on businesses or individuals• Openness and acceptance for new ideas and

businesses

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WHY A RULE-BASED MODEL?“The road to hell is paved with good intentions.”

• Policymakers, researchers and advocates have formidable challenges in being able to account for all of the potential factors that exist in trying form timely policy modifications that would prevent a harm from occurring in the future based on the use of studies, statistics, calculated averages, or relying on anecdotal information as the primary point of modification.

• Large and even small policy proposals and revisions can take years to realize, can be incredibly costly, time-consuming, and can be met with significant opposition at the state and national level, even when it is in our best interests to make such a change.

• Instead of spending years thinking of every possible factor in the likelihood of being harmed from something, policymakers at the state level cherry-pick components of controversial legislation in Congress and then implement it without regard to the ramifications of doing so.

• The problem arises when government uses such practices to create laws that in turn interfere with law-abiding citizens or businesses who are not directly involved in the controversy at hand. Hence, the law of unintended consequences.

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HOW WOULD IT WORK?• A rule-based model of governance could run both independently

and collectively between integrated systems that virtually connect municipalities, counties and state government, utilizing local data with collective intelligence from other, similarly situated entities.

• Leverages the most successful strategies, akin to algorithmic trading models which, in some cases, can be tested in advance of implementation.

• Starts with economic policy or anything that can be measured by real numbers to trigger automatic, rule-based execution.

• Borrows from the concept of “Promise Theory.” That is, connected but independent agents that cannot function completely independent from one another – but can only function by using comparative data for more logical execution.

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KEY ATTRIBUTES• Bottom-up, not top-down. Competes through a more nimble environments that are derived from faster moving forces that are known to create more value, i.e.: the individual, startups and small businesses--not corporations or the state.

• Highly predictable, highly efficient self-governing framework that is driven by a logical rule-based system derived from actionable data, not opinion.

• Offers better transparency coupled with instantly accessible data, resulting in policy improvements that are immediately executed, difficult to undo, and requires little to no involvement from slow-moving governing bodies.

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REAL-WORLD EXAMPLES1. Algorithmic Trading Models

From Wikipedia: Algorithmic trading, also called automated trading, black-box trading, or algo trading, is the use of electronic platforms for entering trading orders with an algorithm which executes pre-programmed trading instructions whose variables may include timing, price, or quantity of the order, or in many cases initiating the order by automated computer programs.

Algorithmic trading is widely used by investment banks, pension funds, mutual funds, and other buy-side (investor-driven) institutional traders, to divide large trades into several smaller trades to manage market impact and risk.

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REAL-WORLD EXAMPLES2. Budget Sequestration of 2013

From Wikipedia: Refers to the automatic spending cuts to United States federal government spending in particular categories of outlays that were initially set to begin on January 1, 2013, as an austerity fiscal policy as a result of Budget Control Act of 2011 (BCA). …

The Act provided for a Joint Select Committee on Deficit Reduction (the "super committee") to produce legislation by late November that would decrease the deficit by $1.2 trillion over ten years. When the super committee failed to act,[9] another part of the BCA went into effect. This directed automatic across-the-board cuts (known as "sequestrations") split evenly between defense and domestic spending, beginning on January 2, 2013.

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POSSIBLE APPROACHES• Functions from key economic indicators of the world’s top-

performing economies at a local or national level (Hong Kong, Singapore, Switzerland, UAE, etc.) would be factored into one or more independent programs to calculate proper policy revisions to show greater transparency, in order to support, direct or ‘self-correct’ economic policy across the county, state, or municipal level.

• Each program would then calculate their outcomes into one policy revision, executed without human involvement to show objective review and transparency.

• Rule-based strategies could then be applied automatically based on one or more similarly situated jurisdictions and their performance.

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PLAUSIBLE CONDITIONS FOR ADOPTION & DEVELOPMENT

• Public demand for a more predictable form of government that alleviates the scenario for repeated failures in policy.

• Insolvency, lack of credit, currency collapse, a dissolving tax base, lack of efficient services.

• Government entities who are forced to do more with less through local, state or federal budget cuts.

• A political establishment, agency or legal environment that cannot effectively police itself within a reasonable timeframe.

• The need for faster, improved performance that can’t be mitigated by Congress, State legislatures, the courts, or through other forms of human involvement.

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BARRIERS TO IMPLEMENTATION• Lack of awareness • Identifying key milestones and roadmap• Politics• Polarization• Special interests• Public acceptance• Government cooperation• Testing• Implementation

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WHY A SELF-CORRECTING SYSTEM?

1. Reduces or eliminates human error and corruption.2. Factors current versus post-change state3. Event-driven – Functions through a series of continual

hooks from monitoring back to automation tool creates self-correction.

4. Better transparency – Intended changes, monitored changes and events; minimizes policy decisions based on improper influence or manipulation, or that lack credible data.

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BENEFITS“Lean government” coming of age.

1. Could leverage the power data from up to 3,000 counties and

more than 19,354 municipalities for timely performance data, as oppose to the untimeliness of Washington politics, protracted committee hearings, elections, lawsuits, etc.

2. Encourages interest and involvement in local policy-making.3. Seeks to minimize the role of influence-peddling, patronage and

cronyism.4. Leverages the power of raw data and successful policies found

throughout the world.5. Creates greater transparency against a common backdrop of

emotion versus logic being used to drive policy decisions.

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BENEFITS (continued)

1. A transparent governing framework that is configured to reflect a real, live ecosystem that can be quickly self-audited for errors, bugs, and manipulation.

2. Predictable changes and modifications that we can view from top-down.

3. Large-scale updates that are faster, more seamless, flexible, and trackable, and with far less “friction” than found in current systems.

4. Better uptime and transparency than any traditional system found in state, county, municipal, or federal government.

5. More time to devote to the more important things of life, with a greatly reduced emphasis of government in our lives.

6. Functions as a bridge to a fully self-correcting system.

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SO HOW DO WE GET THERE?

1. Create a roadmap to digital self-governance that starts with the individual.

2. Change public perception.3. Remove stupidity before trying to be brilliant–

abolish antiquated systems. 4. Optimize along the lines of competitive forces.

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CREATING A ROADMAP FOR DIGITAL SELF-GOVERNANCE

It starts with framing the right message for the public to grow in gradual acceptance for a true, self-governing society over the coming decade.

Optimize You

Optimize Your Work

Optimize Your

Networks

Optimize Your

Government

Key issue: Can we create the right mindset for digital self-governance, and what is the most practical starting point to frame an effective public dialog?

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ROADMAP FOR CREATING BROAD PUBLIC ACCEPTANCE

• Formation of nonpartisan consortium of companies, non-profits, groups and subject-matter experts.

• Frame Incubator and Venture Capital initiatives around a 10-year plan to specifically address each milestone.

• Multi-year marketing and public relations campaign.• Proposal and alignment with like-minded, easier to implement

strategies and ideas that familiarize the public with key concepts through local and statewide ballot initiatives:

• Open the Books Initiatives – Acquire accurate data• Zero-based Budgeting – Justify every penny being spent• Fully Informed Juries – Enable the public to help kill bad laws• Sunset Commissions – End unworkable and unconstitutional policies by

enforceable edicts

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QUESTIONS?Contact Michael Burns at

ideas (at) narrativeux (dot) com

Linkedin.com/in/narrativeux

@narrativeUX