Argument Labs is an answer to the increasing politicization and radicalization of our information. When you want the viewpoints for an issue, listed in plain English, you can come here.
“How could that be possible?” says a reasonable person, pointing out that everyone has biases, and it is impossible to remove them from our media, no matter how “meta” the source.
Yes, this is the problem, but Argument Labs has a solution. The solution needed to remove the possibility of bias like Six Sigma removes the possibility of operational error. Thus, a new standard for appraisal of bias was born.
How Does it Work?
Well, Argument Labs actually simplified the process of reporting the issues. From the wisdom of TL;DR (too long, didn’t read), and time lost to furiously scrolling and scanning, I say, “Make that more meta”.
You know that feeling of satisfaction when you don’t have to read an article, because a great summary is right at the top? That. Then we grade the sentence from liberal to conservative and convert that into a color. This way you know at a glance the viewpoint, and also the political leaning.
“This will never work because of the possibility for misunderstanding,” says anyone who understands that part of the system. I get it; explaining complicated issues in a few words and colors seems impossible. Enter proof by contradiction.
Proof by Contradiction?
Bounce. Okay, bye. Proof by contradiction is a most important mathematical proof technique, where the mathematician assumes the opposite of what they are trying to prove and then finds a contradiction. Then the proof ends and they say they have proved it.
This is a part of the system to remove bias from reporting the issues because it allows for a realization of the other part of that part of the issue to be formed in the reader’s mind, thereby removing the bias by exploring the other bias; breaking the viewpoint down isn’t enough… it is then necessary to explore the opposite of each smallest part. QED.
Argument Labs means finding every opinion and assembling it into a piece of truth. It is a quest to archive each viewpoint in plain English.Tweet
But Wait, There’s More!
Marketing, social psychology, and behavioral economics all want the answer to one question: how do we make people change their habits? I have the answer: get them to do something different. This is a gross oversimplification – they need to be incentivized properly.
Argument Labs cannot argue with only itself and find, condense, and report the truth. It needs the Wisdom of the Crowd. Therefore, to be inclusive of all viewpoints, democratization will be necessary.
1, 2, 3…
- Pick a topic
- Write down all of the viewpoints for the topic, condense each to a sentence
- Find it’s opposite
- Grade the viewpoints from Conservative to Liberal on a scale from 1-1000
- Color the text
- Crowdsource new viewpoints
- Iterate from 3
In this way, Argument Labs will research viewpoints on all issues, then make some quizzes to help people find their political leanings.
“This sounds interesting, but how is it possible to convert a viewpoint into a number?” says anyone who understands how hard it is to communicate effectively. Yes, it might seem impossible, but here are a couple of ways it might be possible.
Sentiment Analysis is an application of NLP (Natural Language Processing) that uses artificial intelligence to extract sentiment from text. This means that it converts text into a number, just like we want. There are problems to this, to be discussed later.
Crowdsourcing is the same tool to be used to gather the data. We can just get more data points and do statistical magic on them to, you guessed it, implement sentiment analysis.
Problem with Sentiment Analysis to Rate Opinions
The problems of using Artificial Intelligence for anything is that there might not be enough data or the data might not be good enough. There might not be enough because it could be hard to find data that is labelled as “liberal” and “conservative”. The quality of the data can be an issue because the old adage, “garbage in, garbage out” is especially true when it comes to machine learning.
There is hope, though! Sometimes statistics wizards can label their own data, essentially, using a technique called “clustering”. Furthermore, natural language processing is hot! hot! hot right now, and so is open-source software. As Argument Labs grows, the chances are good that it can spread the truth, the first step in educating people.
Argument Labs is an answer to the increasing politicization and radicalization of our information. When you want the viewpoints for an issue, listed in plain English, you can come here.Tweet