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We use computers (and AI) to engineer structures, to simulate car crashes and traffic patterns, and to do predictive meteorology. Is there a serious application of a Sims or a Civilization approach to world building? Being able to model political history and decision trees could be both risky and valuable. Is it already happening?

Editing to clarify the scope of the question.

Is it now likely we will be seeing the distributed and global nature of connectedness, and surplus computing power, applied in a way that attempts to solve persistent global political problems? Can we test policy in a way that resolves apparently intractable worldwide inequalities and prevents wasteful tests of strength?

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    Flagging to migrate to SciFi.SE – user4012 Jan 15 at 16:04
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    When you say "predict political outcomes", do you specifically mean the outcome of an election, or are you referring more broadly to the question of how agents in a large political system behave? Because the answer to the former is simply poll predictions, such as those done by FiveThirtyEight projects.fivethirtyeight.com/2016-election-forecast – Bridgeburners Jan 15 at 16:53
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    It's an interesting idea, but "past performance doesn't imply future performance". In other words, studying previous elections doesn't necessarily tell us anything about future elections, because so much in the world changes so fast. – barrycarter Jan 15 at 16:59
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    This is basically the premise of Asimov's Foundation series - and (spoiler) it was disrupted by a single, exceptional, unpredictable human. – pjc50 Jan 16 at 9:36
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Cambridge Analytica has modeled individual peoples' personality and uses AI to influence their voting behavior based on individual personalities.

Any company can aggregate and purchase big data, but Cambridge Analytica has developed a model to translate that data into a personality profile used to predict, then ultimately change your behavior. That model itself was developed by paying a Cambridge psychology professor to copy the groundbreaking original research of his colleague through questionable methods that violated Amazon’s Terms of Service.
By correlating subjects’ Facebook Likes with their OCEAN scores — a standard-bearing personality questionnaire used by psychologists — the team was able to identify an individual’s gender, sexuality, political beliefs, and personality traits based only on what they had liked on Facebook.
After a successful proof of concept and backed by wealthy conservative investors, Analytica went on a data shopping spree for the ages, snapping up data about your shopping habits, land ownership, where you attend church, what stores you visit, what magazines you subscribe to — all of which is for sale from a range of data brokers and third party organizations selling information about you. Analytica aggregated this data with voter roles, publicly available online data — including Facebook likes — and put it all into its predictive personality model.
Nix likes to boast that Analytica’s personality model has allowed it to create a personality profile for every adult in the U.S. — 220 million of them, each with up to 5,000 data points. And those profiles are being continually updated and improved the more data you spew out online.

Point being, with these methods, it should be possible to accurately estimate each person's likelihood of voting and who they would vote for. You could do some fuzzy voter roll matching to also determine if they are registered to vote, or you could use their personality and engagement to estimate whether they are registered to vote. If you combine that with strategic political information like past voter turnout, electoral college facts, polling data, etc.; then you should be able to accurately predict election outcomes better than conventional polling does.

Although, to my knowledge, Cambridge Analytica wasn't themselves making an effort to predict an election outcome. Predictions notwithstanding, they were trying to model a voter's personality, and then use bots and targeted ads to present them with messages that were strategically aimed at being persuasive towards their personality model.

Simply using historical turnout models can't possibly be accurate, because it ignores demographic shifts and turnout shifts. For example, Democrats turned-out for the 2018 mid-terms much more than they did for past mid-terms, because they were much more galvanized. You can't predict that sort of year-to-year passion using only historical models. The best way to attempt to is to use voter rolls to gauge first-time voter turnout, and if you're lucky, the amount of first-time voters can also give you an accurate idea of the turnout of repeat voters.

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Rather than provide a long list of simulation models that may meet your requirements to various degrees, here's a source where you can search through lots of models: The Journal of Artificial Society and Social Simulation (JASSS). JASSS is a peer-reviewed academic article dedicated to simulations of social phenomena. And better yet - it's accessible online for free.

Browse through their articles and you'll find academic simulations of religious conflict, piratry, Mayan agriculture and population change, and just about anything else.

However, you there are two aspects to your question that you likely won't find:

  1. You won't find a single broad model which intends to encapsulate all aspects of a society or the globe. Simulations are always bounded by their intended function, and development time (and costs) rises exponentially with all the different components you want to build in.
  2. You won't find many simulations in this journal that are applied directly to the real world in the way that you describe. Academic simulations aren't intended to solve real problems. They are intended to help advance our theories of how the world works.

To find examples of more detailed simulations which are intended to solve practical problems see my answer on this question.

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