% The Flaming Right by paul murphy

Fri Apr 29 18:53:53 MDT 2022

Memo to: President Donald Trump

Re: Truth Social

Truth social is not yet a success and Mr. Musk's Twitter investment raises the odds that it may never become profitable under the present business model. What's below is a slow-ride elevator pitch for a more valuable and more profitable model.


When Walter Cronkite said "And that's the way it is", he was being liberal with the truth but hardly anyone knew it and those that did were largely "unvoiced". The development of the world-wide web looked like it might change that for the better, but the education inculcated left wing biases of the technical and professional staffs supporting the development of natural monopolies in areas like internet search and social communication led to the opposite effect - silencing doubters while encouraging massive majorities of the deeply ignorant to amplify the voices of those who would mislead to the point that it has become almost impossible to decide whether, or to what extent, anything is reasonable, true, or right without first becoming a subject matter expert.

Proposed solution

Reverse "Truth Social" [TS] to see it as "Social Truth": a free market in the evaluation of claims and ideas circulating in the public square largely modeled on elections betting pools like Predictit.org.

Essentially you would convert the underlying structure in Truth Social from people following people to people following issues - and putting their own cash on the line to support their views on the reality, truth, or reasonableness of conclusions drawn about each issue they follow.

Version one would frame issues in terms of falsifiable statements and manage the cash from people willing to bet on whether or not the statement turns out to be true, reasonable, or right within specific time frames such as a week, a month, or a year.

Version2 would make those bets tradeable on the American securities model.


The obvious way to make money on this is to take a percentage share of winnings.

Murphy's second law states that the likelihood that the majority will be wrong on any issue varies directly with the complexity of the issue relative to public knowledge at the time - it follows, therefore, that the way to make real money from this is to encourage those holding wildly popular majority media views to give odds roughly comparable to the ratio of believers to skeptics: so betting that major progressive media outlets including the NYT will admit that Russia was morally right to invade the Ukraine by May 1st, 2024 would probably draw a 200:1 payoff or better.


There is nothing unusual about either the technical or the financial sides of managing this except that some special effort should be made to ensure a company-wide commitment against bias in choosing and phrasing issues or predictions to bet on and set initial pricing (odds) for.

Perhaps a rotating virtual board of advisors drawn from among the bettors?

Technical issues

What's needed for version 1 [TS/V1] is off-the-shelf open source stuff except for the code needed to manage the betting processes (particularly for partial coverage bets - e.g. I put up $100 on a 200:1 - multiple unrelated players cough up a cumulative 20,000 to cover it) and associated record keeping - but development and integration is well within scope for about three months of work for an open source group of 3 to 5 people using LEMP [Linux, Nginx, MariaDB, PHP] technologies.

Note that the keys to success in something like this are:

  1. Make everything 100% open source from day 1;

  2. work only with very small companies founded and run by the people who will do the work;

  3. be sure your contractors understand and integrate scaling issues from the beginning: the most brilliant windows style many-single-users application isn't going to work when a million people want to access your service;

  4. for TS/V1 contract (and pay for) complete systems from at least three developers working concurrently; and,

  5. define your functional requirements very loosely to begin with, then refine them through prototypes developed by each contractor as both your people and theirs start to understand the details of how something like this can be made to work.

V2 will require (or at least benefit from) the implementation of two expert systems:

  1. a classifier

    The core classifier would manage user commentary. It would process all incoming comment and route it to separate streams with users able to choose which stream, or combination of streams, they want to see. A simple version might, for example, combine textual analysis with bet-weighted user up/down votes to separate incoming materials into four streams: academic, privileged (people with special access to whatever the bet is), sane/non-academic, and rants/spam.

    The more evolved later classifier would also summarize key information, user judgment, and past user performance on the non rant/spam streams.

  2. a judgment support and verification tool

    You will probably always need [$20 this is still true in 2030?] to have humans judge whether or not a subject is suitable for betting - i.e. can be summarized in a statement which can be shown to be either true or false on one or more future dates. Success will, however, breed complexity and detail beyond what most people can handle without assistance - so a tool that helps track outstanding bets, variations on seemingly simple statements, monies, and current and past odds will prove critical to keeping administrative costs and risks down.

    Similarly, the number of issues on which judgments have to be made will increase - as will the number of losing betters questioning those judgments. This tool will track judgments and supporting information to simplify decision making while reducing the legal risks.

    The more evolved later generations of this tool would convert user suggested bets to forms suitable for general use while adding summary information on similar outstanding or previous bets.

Social Consequences

There is a joke going around to the effect that the conspiracy theorists are leading the mass media on being proven right by about 16 to 0 -and, in reality, that's probably an underestimate. There are at least three ways in which converting Truth Social to Social Truth as proposed here helps:

  1. many people know something to be true but have no way to act on that knowledge. I know, for example, that you won a massive majority in the 2020 elections, but so what? Biden's in the Whitehouse and my country (Canada) is going to hell along with yours. Implement Social Truth, however, and I can at least take a lot of cash from the [many deleted expletives] supporting the charade.

  2. Many issues matter, but most people have no way of judging the validity or otherwise of mass media pronouncements on them. Do masks work in the covid-19 context? I know they don't because I've done the research, but most people can't do that and the only people the media reports on are putting taxpayer dollars on the line in service of their own careers - give people access to Social Truth, however, and the other side, although much smaller and quieter, becomes both visible and credible because they're risking careers and putting their own money on the line.

  3. one of the ways in which the progressive left misleads the public is through strong support for positions that are never defined precisely enough to allow falsification - with the result that policy failures do not generally lead people to rethink the ideas behind those policies. Social Truth cannot, however, operate in this way because bets can only be placed on statements that can easily be shown to be either true or false on some target date. So you can't bet on whether American SUVs are driving global climate change, but you can bet for or against the claim that the ocean surface within 10KM of the geographic North Pole will be ice free as of July 4th, 2030. ($100 says "No.".)

    Social Truth will, in other words, pull the rug out from under the usual shouting and magical hand waving the left uses to adapt to policy failure without policy change.

Ah, penultimate floor: this is where I get off, and thanks for listening!

Paul Murphy, a Canadian, wrote and published The Unix Guide to Defenestration. Murphy is a 25-year veteran of the I.T. consulting industry, specializing in Unix and Unix-related management issues.