Six State Logic Re-Engineers Language, Programming, IoT and Politics


Although a simple concept, 6SL has potential to fundamentally re-engineer how humans think about logic in general with a resulting broad impact on diverse topics like application programming for language, IoT, Super Intelligences, teamwork and politics.

For language, 6SL provides a common syntax for basic communications across natural language and machine to human language barriers. The following example assumes availability of simple lookup table for phrase matching to support 6SL language applications. Phrase matching is sufficient because 6SL simplifies communication syntax to a positive or negative question and 6SL answer with reason why format.

Question simplification removes difficult-to-translate natural language nuances in questions while 6SL answer provides sufficient information for communication to be actionable. Actions can be conclusive in a single step, like a vending machine giving a prospective customer a Known Negative response to the question “Do you have Diet Coke?”, or actions can confirm the need for one or more additional cycles of questions and answers.

Consider the example of a human answering “Seems Positive” to a machine sales agent asking if they want to take a test ride in a new self-driving car.  In this example, the combination of positive and uncertain elements in the Seems Positive answer would stimulate the agent to clarify the reasons behind the human’s answer. Reasons could be “Positive: Looks Interesting” and “Uncertain: Concerned about safety.”

If we assume the agent’s mission is to offer free sample rides to humans, then the agent would want to support the positive element of the human’s answer and provide information, like data showing self-driving cars are safer than human driven cars and a copy of the generous insurance policy, to help the human overcome their uncertainty. After showing the targeted information, the machine sales agent asks the human again if they want to take a test ride to see if the information had the desired impact of moving the human from a Seems Positive 6SL state to an immediately actionable Known Positive 6SL state.

Codifying questions and actions associated with 6SL responses from the other party represents a type of simple application programming language humans use to program any machine agent to interact with other machine agents or humans for any 6SL application. In the case of a Super Intelligence, the type of programming is exactly the same as for a simple, single function IoT component like a vending machine.

The difference between an IoT component and a Super Intelligence is the scope of programming topics.  Super Intelligences are programmed, updated, and supported by teams of people to address a wide range of complex applications like the onboarding of professional clients for doctors or lawyers while the programming of many IoT components will be comparatively limited in scope such as a vending machine.

6SL supported teamwork is an application with far reaching implications because so much of human effort is spent preparing for and attending meetings. First, much of 6SL decision support for meetings is easier to do remotely than in person. This is because meetings involved many distractions like the dynamics of office politics and because meetings must be conducted on a restrictive timetable. One-to-many dissemination of new information and education will continue to be meeting supported activities, but 6SL blends into this traditional meeting environment superior and far less expensive remote idea evaluation and decision validation methodology. 6SL changes how human teamwork is done because the quickest way to a decision will involve participants interacting with their individual screens rather than the informal, hierarchical, or other type of live meeting interactions we are all familiar with.

Many political problems are associated with a lack of any objective perspective of the truth which makes everything except what someone wants to believe false.  Also, many problems are associated with people with mixed or uncertain feelings being forced to make all or nothing decisions. 6SL has a role to play in correcting both of these problems. First, 6SL helps collect more accurate descriptions of voter sentiment and uncertainty.

This highlights the absurdity of pushing through policies with minority support while a majority of constituents remain uncertain. 6SL also enables creation of fully transparent policy-specific Super Intelligences that are far more inclusive and resistant to motivated reasoning or outright dismissal than partisan human institutions. Just these two 6SL innovations can transform the political landscape by providing humans with the best possible version of the truth and enfranchising uncertainty as a legitimate and non-partisan state of being.


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