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Rethinking_
Internet Privacy
Motif · Terms of Service Analyzer
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On Jul. 24, 2019, the Federal Trade Commission charged Facebook a record-breaking five billion dollars for violating user privacy. Despite the company's countless promises, Facebook deliberately exploited its userbase with misleading disclosures and disingenuous marketing.
The implications are devastating. But, more immediately, it begs the question: how do we protect our personal information?
Let's face it. No one reads the Terms of Service. Regardless of what it is that you're doing—making new accounts, downloading software, you name it—you'll tick the checkbox thoughtlessly, or at most read the first few sentences.
But even if you'd managed to make it further, you'd realize that it's next to impossible to find anything of value. Companies are really good at using legalspeak to disguise their more malicious policies. And they're long. Like, REALLY long.
The implications are devastating. But, more immediately, it begs the question: how do we protect our personal information?
Let's face it. No one reads the Terms of Service. Regardless of what it is that you're doing—making new accounts, downloading software, you name it—you'll tick the checkbox thoughtlessly, or at most read the first few sentences.
But even if you'd managed to make it further, you'd realize that it's next to impossible to find anything of value. Companies are really good at using legalspeak to disguise their more malicious policies. And they're long. Like, REALLY long.
Okay, what should I do then? Hire a lawyer each time I want to use literally any service? Well no, there are options out there. You could reference websites or posts that break down a certain website's terms of service for you, but this comes with several disadvantages.
This includes:
This includes:
- Taking time to actually look up and find a good teardown
- Is a manual process and good teardowns of smaller services are few and far between.
- Often too comprehsive or confusing / too short to exemplify issues.
- Takes into account specific issues, but doesn't understand the hollistic language of the document.
Next
That's why we came up with Motif, a simple Natural Language Processing (NLP) and Distributed System solution, giving you straightforward results on how privacy-friendly a service is based on their ToS.
Motif first extracts the Terms of Service, and analyzes the content using NLP: Sentiment Analysis, Expression Classification (Bayesian AND Logistical Regression), and RegExp Static Keyword Analysis. It also utilizes advanced caching infrastructure and distributed systems, to deliver a fast and buttery-smooth experience to the user.
Motif first extracts the Terms of Service, and analyzes the content using NLP: Sentiment Analysis, Expression Classification (Bayesian AND Logistical Regression), and RegExp Static Keyword Analysis. It also utilizes advanced caching infrastructure and distributed systems, to deliver a fast and buttery-smooth experience to the user.
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