The Booklet

The Science of Governance Booklet

Theory: the Science of Governance (SoG)

Context:Digital Transformation challenges Social Stability

Time is a universal medium to connect events; knowing when events happen is integral in our conception of everything. This is shown through sequencing and recording information, hence why both “time is money” and “knowledge is power.” Everyday, people around the world are persuaded by others who simply have more information. This is known as information asymmetry, where one entity has better access to knowledge while the other entity does not. Examples of this phenomenon range from car salespeople selling bad cars to unwary buyers, to developing countries getting overly high interest rates from lenders, crippling their economy. Information asymmetry can be used with good intentions, and could also lead to exploitation.

Currently, data processing technologies are increasing information asymmetry in ways that are becoming a major problem in public administration. Malicious and systematic data technology exploitation can be conducted by individuals or public institutions that have more access to data or data processing technologies. To ensure sustained justice in modern societies, the notion of governance must be grounded to the power of persuasion’s root: information asymmetry. We call this scientific endeavor the Science of Governance (SoG). SoG focuses on the fundamental properties of information asymmetry: the timeliness, accountability, and observability of public data.

Power structures always needed tools and methods in guiding timely actions, creating accountability for policy outcomes, and observing progress. Models of thought were utilized to create and execute policies shaped by power structures. These include: “Objective and key results (OKR);” used to define measurable goals and measure outcomes, “Management by objectives (MBO);“ defining specific objectives and sequentially how to achieve each objective, and “logic models,” describing the chain of causes and effects leading to an outcome. Without adopting secure and field-tested information systems, political structures are still mostly functioning through verbal debates, creating their offline codes in human-readable texts only, and storing information on mediums that cannot be automatically checked and retrieved by relevant parties. A hyperlinked logic model is shown below:

Logic Model (Science of Governance) Template:LogicModel 12 1, 2022
Abstract Specification Context The Committee for Science of Governance is created in Indonesia for the preparation of the G20 Summit during November 2022. Goal Create a consensus-reaching process to resolve potential conflicts caused by interdisciplinary/cross-domain concerns. Success Criteria Operating the governing board of SoG using a trustworthy content versioning/publishing system Improve the content of SoG using Smart Contract specified workflows Having two/thirds($2/3$) of active participants sign off on each of the proposed resolutions/propositions.
Concrete Implementation Given Inputs When Process is executed... Then, we get Outputs Initial suggested topics of discussion. A number of experts and volunteer participants initially provided by the committee. Travel and Online meeting arrangements Funding and logicstic supports for traveling experts Define topics of discussion Invite experts to participate in discussions. Online and In-Person participation of Discussion, including email and other forms of content exchanges Refine discussion content and topics Decide on final topics and publishable content Digital recordings of discussion content and textual-based exchanges (email, etc...) A signed publication of participants on topics that they agreed on. A number of sub-committees focused on selected topics Publications submitted and signed by sub-committee members
Boundary/Safety Conditions of Science of Governance Due to reasons that certain protocol breach or total number of participants of the governing board of SoG goes below three persons. Then the program will be considered as a personal project, instead of a collective project.

Large-scale digital technology uses these logic models; even modern information technology like smartphones and blockchains were built on a foundation of prior inventions and systems using similarly formatted models. A logic model is a domain-independent specification format allowing any self-governing body to utilize contemporary technologies to represent the timeliness of information distribution, accountability of data changes, and observability of policy outcomes. To start, existing governance tools such as the OKR/MBO models can be integrated with hyperlinked documents to help keep policies and execution results timely, accountable, and observable. To do this with a formalized framework, we name this new field, SoG.

Goal:Ensure Governance Correctness by Logic

SoG functions through establishing a fair and just political process in a world overwhelmed by the asymmetric distribution of data governance technologies. It provides a trustworthy foundation to help governing bodies allocate resources to execute policies efficiently, utilizing different aspects of established governance theories and creating new governance theories, while employing readily available technologies to deploy solutions in the real world. In other words, an End-to-End solution for governance must have a scientific basis that can be scaled up in applications through technology and have a unifying policy decision frame that can be applied to all application domains. This requires the Science of Governance to be abstract, so that it does not associate itself with a specific application context. It also needs to be concrete, so that all policy decisions are observable and accountable in terms of socially and physically meaningful data. The only medium to deal with this dualism is nothing but logic, more precisely, the logic of Correct by Design (CbD).

The Science of Policy Correctness

Before CbD is explained, one must understand the term “correctness.” There is a logical way to express correctness that is scale-free and domain-independent: the Venn Diagram representation of correctness in the diagram on the next page. It shows that correctness is the logical intersection of safety and liveness conditions. From a scientific viewpoint, correctness should be objectively determined according to explicitly encoded safety and liveness “social contracts”.

Safety means nothing bad happens: a system or policy is considered safe if nothing bad happens from its execution. If one plays a football game, and throughout the game, the player is not injured, the game is considered to be safe.

Liveness means something good happens during the execution of a system or policy. An example of this in a football game would be the player scoring a goal. That would be a liveness condition. The intersection between safety and liveness is clear in this example, a person is uninjured and scores a goal in the game. This is “correctness.”

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This generic, domain-independent statement of correctness is not only applicable to computer science, but to governments as well. It allows policy designers to separately list the conditions of what are considered to be bad, and then list the conditions that are considered to be good. This logical decomposition of correctness is a powerful intellectual construct that enabled system engineers and computer scientists to build systems as complex as the Internet. Whether a governing body can consistently apply this construct in policy framing decides how well an organization may be governed by explicit rules. With an increasing amount of conditions, however, organizations need an additional way to ensure correctness, particularly in contracts. This is where Hoare Logic, Hoare triplets, and CbD comes in.

In 1969, when more possible conditions were being created in computer programming, Tony Hoare created a logic system to rigorously clarify system correctness. Key to this system was the Hoare Triple, expressed as {P} C {Q}. {P} is the precondition, what caused the command. C is the command, the action that takes place. {Q} is the postcondition, what happened due to the command’s occurrence. In terms of System Correctness, safety would be the precondition, the event occurring due to satisfying safeness would be the command, and liveness would be the postcondition. When C satisfied both {P} and {Q}, the system worked as planned, as in, it was Correct by Design.

In our football game example, {P} would be a person who is physically fit to play and that person does not have an intention/history to hurt other players. C would be playing the game, and {Q} would be the player scoring goals and playing at least 90 minutes. We know this example is Correct by Design if these parameters occurred accordingly. But if {Q} was the game only being played for 10 minutes and fog stopping the game, then we know the system did not attain correctness in terms of Correct by Design! CbD provides logical symmetry to all systems of any kind by using a consistent set of rules to classify the safety and liveness conditions of the system. This naming convention allows any system to identify errors (safety) and recognize accomplishment (liveness). As Henry Poicare once said: ”Mathematics is the art of giving the same name to different things.” CbD assigns consistent naming schemes (safety, liveness, and correctness) to all governance structures in casual categories.

Hoare Triples can go beyond computer programming, however, because every action made by every individual, group, government, etc. can be turned into a Hoare Triple. This includes something as simple as eating food. “Hunger” would be the pre-condition, “eating digestible food” would be the command, and “increased energy” would be the post-condition. Governance concepts like Rousseau’s Social Contract can be turned into a triplet as well. People giving power to a government would be the pre-condition, the creation of a Social Contract would be the Command, while the government receiving power would be the post-condition. These triplets can be simple or detailed, and one can even form a chain of triplets using the post-condition as the new pre-condition for a new triplet. One can easily imagine these Hoare Triples to be linked/composed to express more complex policies or programs. It is the complexity of these composable arrows/Hoare Triples that make it a domain-independent way to organize correctness in a formalized data structure. This logic system is instrumental in guiding people in a world of increasingly complex contracts.

Writing down satisfactory conditions in contracts is not new. What is new are the many possible conditions in this already highly interconnected world. Yet all these possibilities can be symmetrically dealt with through Hoare logic and concepts that formally frame correctness like CbD. Due to its composability, Hoare Triples may serve as the universal data primitive to encode arbitrary large-scale social and industrial governance challenges. Due to its simplicity, they can scaffold application scenarios that deal with the complex interactions of many knowledge domains. The Hoare Triple is a Universal Construct: It is everywhere and has been already adopted by many popular governance tools, such as the Logic Model (see Appendix on Logic Model as Multi-Level Hoare Triples).