Framework for Thinking about Artificial Intelligence

I read something that gave me an idea.  Imagine a framework for thinking about artificial intelligence somewhat, as an analogy, similar to the notion of the legal framework.  The legal framework refers to the system of laws, regulations, and principles that govern our society. It provides a structure within which individuals, organizations, and governments operate; defining their rights, responsibilities, and obligations.  For example, summarizing the law in very high level terms.

"The law" is a set of rules that a community agrees upon. These rules help keep things fair and orderly, creating a virtuous cycle as contrast to a viscous cycle. Here’s how it works:

  • Customs and Rules:
    • Customs: People in a community follow certain practices and traditions.
    • Rules: These practices become rules that everyone agrees to follow.
  • Binding and Authority:
    • When everyone accepts these rules, they become binding—like a promise.
    • An authority (like a government) ensures that people follow these rules.
  • Enforcement:
    • If someone breaks a rule, there are consequences.
    • The authority enforces the rules—for example, by fines or penalties.
  • Areas of Law:
    • Constitutional Law: Deals with how a country is governed.
    • Criminal Law: Focuses on crimes and punishments.
    • Family Law: Covers marriage, divorce, and child custody.
    • Property Law: Deals with ownership and rights.

The legal framework keeps our society running smoothly by setting rules we, the stakeholders, all agree to follow.

* * *

Now applying this to applying this to one one system, one "area of knowledge": XBRL-based reporting (this is a PROTOTYPE).

XBRL-based digital general purpose financial reporting is a set of rules that a community of stakeholders agrees upon in order to achieve a set of goals and objectives.  These rules help keep the system fair, orderly, operating effectively, creating a virtuous cycle by constraining the "wild behavior" of system stakeholders.

  • Customs, Rules, and Good Practices:
    • Principles: Prudence dictates that making use of an XBRL-based digital general purpose financial statement should not be a guessing game.
    • World View: This logical system makes the closed world assumption (CWA), assumes negation as a failure, and makes the unique name assumption.
    • Customs: Stakeholders in the community follow certain practices ad traditions relating to financial reports.  For example, the use of single underscores and double underscores when representing a subtotal or total.
    • Rules: These practices become rules that everyone agrees to follow.
    • Good Practices: This set of guidelines is known to produce good outcomes if followed.
  • Binding and Authority:
    • Valid Syntax: Software promises to conform, through certification, to the published set of XBRL International conformance suites that prove that software conforms to the set of XBRL technical specifications.
    • Valid Semantics: XBRL-based report models and reports are expected to conform to logical rules and financial reporting rules that govern the general behavior and norms of a general purpose financial statement.
    • Properly Functioning System: An XBRL-based general purpose financial statement is expected to be a properly functioning logical system is complete, precise (a.k.a. sound), and consistent (a.k.a. valid).
  • Enforcement:
    • Consequences: If someone breaks a rule, there are consequences.
    • Authority: The authority enforces the rules.
  • Areas of the Rules:
    • Deductive Reasoning: Reasoning based on these rules, all declarative in nature, can be determined with guaranteed certainty.
    • Inductive Reasoning: Reasoning based on this information is based on probability and therefore can never be assumed to be correct, uncertain results are possible.
    • Abductive Reasoning: Reasoning based on this information is based on probability and therefore can never be assumed to be correct, uncertain results are possible.

What do you think of this prototype?  It seems to me that this idea can be applied more generally to artificial intelligence.

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