Algorithmic power on human behavior

Never before has it been easier to track human behavior into a spreadsheet, quantify the variables and develop applications to make human users follow “the masters” bidding.
And that’s what this article is all about, the masters of algorithmic power on us peasants (the users), the question of how neuroscience work and the philosophical question about human individuality.

Let’s go back and take a look on one of the first and also first “methods” the masters used to steer human behavior into revenue.

Let’s enter the world of freemium

Freemium is a concept used mostly in the mobile app market. It became the new normal for any mobile development company out for incredible revenue.
in essence:

Freemium is a pricing strategy by which a product or service (typically a digital offering or application such as software, media, games or web services) is provided free of charge, but money (premium) is charged for additional features, services, or virtual goods — Wikipedia

Traditional game development

Game dev inc spent €5 million to create FarmVillage and additional €2 million on marketing. The game was released into the market with a break-even analysis of 2 million downloads at the price of €3,5.
The only revenue stream Game dev inc had was downloads. So if the game was a bust in the market there was no way of saving it.

Freemium development

Game dev inc spent €5 million to create Farmvillage and additional €2 million on marketing. FarmVillage was released into a market with freemium engine that lets users advance in the game via in-app purchases.
Farmvillage is a continuous revenue stream that is set by the amount & what type of users is playing the game.

Why did companies go with freemium

Study after study showed that around 50% of the freemium model’s revenue was created by the top 10 % of mobile users. These have often been mentioned as whales. But they were addicts.
The reason why these whales spend an enormous amount of money on mobile games is that they are hooked on the game as if it would be alcohol, drugs or sex.
For a more in-depth look at freemium watch this well made short-documentary by Vox

How free games are designed to make money

Freemium is created by algorithmic masters and pushed steer human biology and human behavior into buying. Of course, the freemium scam has gotten a lot of push back but still is used as in the above example of Pokemon Go. But it shows the terrible truth that we have to conclude to:

All of us can be steered by algorithms because it uses what makes us humans. Your existence can be translated into a spreadsheet

As technologies as machine learning, neural networks and artificial intelligence progress the algorithmic power will only grow stronger. As I see it now we have three different levels of algorithmic power.

Three levels of algorithmic power functions

  1. The game uses simple business logic “If this then that”.
  2. The game tracks everything in your in-game behavior and learns how you respond to certain triggers and then adapt what triggers to be most effective.
  3. The game uses bought personality data from Facebook and other data brokers to create a personal gaming-experience where levels, payments and offers are optimised for making you addictive. While playing it will adapt to your behavior instantly and continuously follow your outside-game behavior to improve its algorithm. Machine learning is able to quantify any variable put in and learn how to use it to “drive more purchases”

As this is a mobile app example. Let’s test it out on Human resources (HR)

  1. The HR system uses simple business logic. The employee does not fill out reports in a timely manner and sends out a warning per e-mail.
  2. The HR systems learn what triggers the employee to fill out time reports on time. The HR system has multiple triggers to use to get employees to comply, some examples would be sending out warning e-mail, informing managers, pay deduction or restricting access to business systems as e-mail.
  3. The HR-system have uses a personality file which includes data from Facebook and other data brokers to inform the employee’s manager and other business systems how to manage the employee for compliance. It will analyze your sentiment in e-mails and on social media to understand your happiness level and risk for leaving the company. It will analyze your work performance over time and identify your coming divorce before you know it.

A long-standing “use” within algorithmic power is how Target data mining ended up revealing a teen pregnancy to an unknowing father due to a set of purchases. A clear testament to how effective algorithms can be.

This was 2012

So speed forward to how these systems know you better than yourself, your friends or your spouse. Back in the 80s scientist created a questionnaire-based OCEAN model of giving major psychological traits which Michal Kosinski’s Ph.D. project used in 2014. By analyzing and using machine learning on Facebook users and that they answered a OCEAN-questionnaire, the AI could reliably start predicting the users “sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.”
With more clicks, the AI could predict better. According to the study with 70 clicks the AI’s could predict a person’s OCEAN score better than their friends, 150 clicks better than their parents and 300 likes could do better than their own spouse.

How many likes have you made on Facebook since you started?

The reason why Google, Facebook, Alibaban & Amazon are some of the biggest companies in the world know and did not exist 25 years ago is that they own and create the data that these algorithms are built on. Whatever you are reading about on the internet today of what machine learning can do, it’s yesterday’s news at the above companies research & development divisions. This is without speaking about what is happening behind the secrecy curtains at intelligence agencies around the world.

The truth here is that all is built on silos and nobody has control over what is happening. Global governance can’t keep up or function in the way needed for control. It does not matter if it’s how Game developers drive revenue or #fakenews can alter an election.

We all are in the hands of algorithmic power

But who controls the algorithmic power and for who’s benefit?

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