Prediction Successes and FailuresJuly 27, 2021
Confucius: The Yin dynasty adopted the rules and manners of the Hu line of kings. It is possible to tell whether it retrograded or advanced. The Chow line has followed the Yin and adopted its ways. Whether there has been deterioration or improvement may also be determined. Some other line may take up in turn those of Chow. If this process goes on for 100 generations, then the result may be known. Analects
Since the 2008 from the US Presidential elections and 2013 from the Greek Debt Crisis, we’ve been making predictions on society and economics as an implentation of Supersociology.
Here are the results so far:
|Country||Year Prediction was Made: Prediction||Outcome|
|World||2015: A global crisis will spark in 2019 marking the start of a long crisis which we call ‘The Crisis Years’||Correct|
|World||2019: A global financial crisis will emerge in a certain year between 2020-2030 as a result of that 2019 crisis||Pending|
|2023: Russia will step up its offensives against Ukraine despite the lack of resources||Pending|
|2022: Bongbong Marcos will win the elections||Correct|
|2022: The US will reduce sanctions during its mid-philosopher cycle||Pending|
|2022 Hungary: Orban will win the elections||Correct|
|2021: Probing prediction–Kono will be Prime Minister. In reality, Kishida won. This proves that Japanese political system is a society within a society that represents itself and not the people, just like China’s Communist party. To predict Japan’s elections, the model has to be applied to the LDP||Null|
|2008 & 2012 Obama will win the elections, 2016 Clinton will win the popular vote, 2020 Biden will win the popular vote||Correct|
|2021: Navalny’s protests will not bear fruit and will fizzle out, while Russia will increase its militarization [This is especially true in 12/2021 with Russia amassing troops near Ukraine – it will only get worse!]||Correct|
|2021: Netanyahu will lose power after 2020||Correct|
|2019: The franchise of ABS-CBN will not be renewed in 2020||Correct|
|2018: The Hongkong protests will fail to grant democracy to Hongkong||Correct|
|2017: The BJP will lose power at a certain year||Pending|
|2017: Macron will win, 2022: Macron will win||Correct|
|2017: Softbank’s Vision Fund will lose on its biggest bets||Correct|
|2017: Rohingya crisis will remain||Correct|
|2017: The economic crisis in Venezuela will remain until a certain future year||Null (no way to prove or disprove)|
|2017: Duterte allies will win in 2018||Correct|
|2017: Israeli Crypto Bancor will crash||Correct|
|2016: Roxas will win the elections||Wrong|
|2016: The US will slowly lift more sanctions (In reality, Trump imposed new sanctions)||Wrong|
|2016: Scotland will want to leave the UK||Semi-correct|
|2015: Assad will start losing ground to rebels by late 2016 (Update 2022: This is explained by the concept of the balance of power||Wrong|
|2015: The Jeddah Tower will not be completed on time||Correct|
|2015: The Greek debt crisis will continue||Correct|
As you can see, there were many mistakes in the beginning. But just like any learning system, it gets better in time as the patterns of social cycles and their interaction with each other become clearer.
Based on Recurring Social Cycles
The core of the model is based on David Hume‘s maxim that mentality creates reality. The model proposes that human society is a metaphysical entity that is made up of individual metaphysical entities called human souls or abstract minds.
This society has its own known dynamics which is explained by the ‘Social Cycle’ model of Socrates and the ‘Moral Sentiments’ model of Adam Smith, Hume’s best friend.
Each society’s mentality has its own cycles which clash or concur with those of others, creating the events in the news. By knowing the flow of each mentality, then the outcome of regular events or long-running events can be predicted, such as elections, conflicts, or economic recessions. This is somewhat used nowadays in Game Theory. However, instead of creating selfish actors like in game theory, we use a specific range of actor ‘types’ with their own attributes and dynamics.
These ‘types’ are generally known as varnas in Hinduism and the social classes in ancient China.
Historical events are used as ‘markers’ for plotting the flow of this mentality, which can be used as training data for Artificial Intelligence to better crunch all events together to form more accurate mentalities and therefore predictions.
Some Countries are Easy to Predict, Some are Difficult
It’s easy to make accurate predictions for the USA because there is a lot of consistent, historical data from its inception in 1776 up to today. However, it’s difficult to make predictions for:
- Middle Eastern countries like Syria and Iraq as they were bunched up together under the Ottoman Empire for many years
- countries whose histories are not in English, such as Vietnam and Thailand
- countries that have so much historical information such as China and India. This increases the noise which prevents accurate modelling. The Europeans fixed this problem when enlightened writers weeded out the noise or inferior historians