Remember when privacy was a thing? No? Oh, ok then.
But people used to have some concern about having their location and whereabouts monitored by companies and governments.
I guess this information was used for evil-doing at least once in history? Whatever, who cares, let’s gather data and make an app!
Have you ever been blindsided by an in-retrospect-obvious event, like a firing (or even just a passing-over for a promotion) at work, or a seemingly-sudden breakup?
Using the power of OMNIPRESENT CORPORATE SURVEILLANCE, we can create a new program, which we will call Big Brother 2, that does the following:
Big Brother 2 will collect this data from thousands or millions of users, and—using advanced and overhyped machine-learning techniques—it will figure out what kinds of warning signs preceded various life events.
Then it can forewarn you of danger in your own life!
- Dating (Figure 1): Two people are dating and their messaging steadily becomes less frequent and more negative. Big Brother 2 can extrapolate their breakup date and (optionally) start preemptively saving flattering photos of those users for their upcoming dating profiles.
- Employment (Figure 2): Someone’s boss mentions “outsourcing” and then communication rapidly drops off. Big Brother 2 can recommend some resume-preparation services for that employee.
Fig. 1: Big Brother 2 can extrapolate from its millions of data points and figure out that, on average, users with a certain text-messaging profile typically experienced a breakup within X months. In this case, the user is being forewarned that they should expect a breakup on or around October 24 (orange line).
Fig. 2: Here, Big Brother 2 suggests that company layoffs will occur on June 28. In this case, the Big Brother 2 algorithm could also incorporate data about the economy / stock market / relevant world news that may impact the user’s job.
Fig. 3: Using sophisticated machine-learning algorithms, Big Brother 2 may even be able to predict things you wouldn’t think were predictable, such as exactly when a serpent is going to slither over and sink its fangs into you (thus, hopefully, allowing you to either prepare yourself for that moment or to take corrective anti-snake action).
Silicon Valley entrepreneurs: hire me to develop this project. Thanks in advance.
PROS: Could reduce the likelihood of snakebite.
CONS: May result in “Logan’s Run”-esque scenarios where the system determines that a person has negative value, and then the user’s phone starts plotting to murder the user (see historical example from Episode #270 of The Simpsons). If this occurs, it is an example of a bad optimization function, and should be fixed in the next update.
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