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Rhetorical Devices Used in Literary Logic

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Posted 08 October 2017 - 06:36 PM


A related term...


Polysemy - One word used to describe different things. Also can include phrases, symbolic poetic imagery, and different forms of jargon. Example: Look up the word monster in webster. Then look up the same word in an old law dictionary. Some words have up to 30 meanings. They're meant to hit the senses on a deeper level. They are always done on purpose (this is the main difference between the above related homophones) and are especially used in an historical sense; over time words change their meaning but can still be twisted to serve more than one purpose of meaning.
Perhaps this is why it is difficult to teach these in class. It relates to etymology (origins of words) which takes time and study. Worthy study for a greater historical sense in meaning. 
Often, judging how Polysemes are related makes them ambiguous and vague in nature. I think this works with all languages in one form or another as problems arise when non-native speakers learn a new language. At least it's seen when learning English. Inside information can be conveyed using this device. 






I found this post about 'twilight language' to be apt:




The twilight kind?
I think it comes from silent thought.
No sound....
One star starts to speak. It vibrates, it sings, causing it to burst forth in a blast of metaphor to speak on many different levels. The other stars created from that initial idea begin their own movements. All at the same time. Dancing to a piece of music created out of nothing. Layered and full of meaning.
Build a sigal, fill it with symbols, and insert multi analogies in each one.
Which ones mean most to you? 

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Posted 09 October 2017 - 10:13 AM

The Categorical Converter
The Categorial Converter is a visual representation of all possible logical relationships between individual categorical propositions. It may be used to test the validity of an inference from one proposition to another.
In other words, the Categorical Converter represents all possible inferences using the rules of:
From here, you may view the Categorical Converter. You may also learn how to use it, and finally, learn how it was constructed.

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Posted 09 October 2017 - 10:18 AM

So when will there be an app to detect logical fallacies?

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#134 status - Potatoes au Graten

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Posted 09 October 2017 - 10:48 AM

So when will there be an app to detect logical fallacies?



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#135 Ghosty McFly

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Posted 09 October 2017 - 11:29 AM

Have they taught them how to lie?
Facebook built an AI system that learned to lie to get what it wants
The pursuit of Facebook’s AI isn’t too different than other applications of AI, like the game Go. Each anticipates its opponent’s future actions and works to maximize its winnings. But unlike Google’s Go-playing AlphaGo, Facebook’s algorithm needs to make sense to humans while doing so.
From the human conversations (gathered via Amazon Mechanical Turk), and testing its skills against itself, the AI system didn’t only learn how to state its demands, but negotiation tactics as well—specifically, lying. Instead of outright saying what it wanted, sometimes the AI would feign interest in a worthless object, only to later concede it for something that it really wanted. Facebook isn’t sure whether it learned from the human hagglers or whether it stumbled upon the trick accidentally, but either way when the tactic worked, it was rewarded.
Interesting business possibilities
The first thought that comes to mind is taking us humans out of the equation and letting AI do all of the hard work on large contract negotiations.
How great would it be to bring my "AI bot" to the negotiating table (or I guess now it would be the negotiating computer screen) to outsmart, deceive, and manipulate the pathetic human on the other side of the contract negotiations?
We'd win every time.
Of course, other companies would quickly get smart to it and start to bring their own AI bot negotiators. Then it might be like some form of Robot Wars, except instead of two mechanical robots attempting to slice and dice each other physically, we'd have two AI bots duking it out via a computer screen.
We could have them actually run big parts of the business for us. We could get them involved in the highly strategic world of mergers and acquisitions. Every company could have lots of AI bots out there doing the work, building AI bot relationships, strategically maneuvering around the business landscape while us humans hung out in Vegas.
It might get really interesting for us to watch. Who's to say that the AI bots wouldn't form alliances out there to help them lie, deceive and manipulate their way to success? One AI bot could bluff its way into a big business opportunity by aligning with two other AI bots only to reveal later that it was part of a larger plan to buy those other two AI bots out.
Actually, that kind of sounds like human behavior but just done much more effectively.
Google’s DeepMind pits AI against AI to see if they fight or cooperate
Unsurprisingly, they do both
AI computer agents could manage systems from the quotidian (e.g., traffic lights) to the complex (e.g., a nation’s whole economy), but leaving aside the problem of whether or not they can do their jobs well, there is another challenge: will these agents be able to play nice with one another? What happens if one AI’s aims conflict with another’s? Will they fight, or work together?
Google’s AI subsidiary DeepMind has been exploring this problem in a new study published today. The company’s researchers decided to test how AI agents interacted with one another in a series of “social dilemmas.” This is a rather generic term for situations in which individuals can profit from being selfish — but where everyone loses if everyone is selfish. The most famous example of this is the prisoner’s dilemma, where two individuals can choose to betray one another for a prize, but lose out if both choose this option. 
The results of the study, then, show that the behavior of AI agents changes based on the rules they’re faced with. If those rules reward aggressive behavior (“Zap that player to get more apples”) the AI will be more aggressive; if they rewards cooperative behavior (“Work together and you both get points!) they’ll be more cooperative.
That means part of the challenge in controlling AI agents in the future, will be making sure the right rules are in place. As the researchers conclude in their blog post: “As a consequence [of this research], we may be able to better understand and control complex multi-agent systems such as the economy, traffic systems, or the ecological health of our planet - all of which depend on our continued cooperation.”

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#136 Feathers


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Posted 09 October 2017 - 12:50 PM






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Posted 27 October 2017 - 03:21 PM


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Posted 27 October 2017 - 03:43 PM

58 cognitive biases that screw up everything we do
We like to think we're rational human beings. 
In fact, we are prone to hundreds of proven biases that cause us to think and act irrationally, and even thinking we're rational despite evidence of irrationality in others is known as blind spot bias.
The study of how often human beings do irrational things was enough for psychologist Daniel Kahneman to win the Nobel Prize in Economics, and it opened the rapidly expanding field of behavioral economics. Similar insights are also reshaping everything from marketing to criminology.
Hoping to clue you — and ourselves — into the biases that frame our decisions, we've collected a long list of the most notable ones.
This is an update of an article that was previously published, with additional contributions by Drake Baer.

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#139 status - Granny Knot

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Posted 01 November 2017 - 10:08 AM

How political rhetoric is making us crazy...

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Posted 03 November 2017 - 04:36 AM

The Origins of Rhetoric
If each act of individual trolling is an act of rhetoric in action, then what is rhetoric itself? Rhetoric is a term frequently used in popular culture as a way to dismiss a person’s words/thoughts. Usually this dismissal involves calling the person in question “biased” or “manipulative,” suggesting that there isn’t any “substance” informing an author/speaker’s claims. Instead, the author/speaker just uses “empty rhetoric.” While this understanding of rhetoric is not without a historical grounding, this understanding is somewhat misinformative. Rhetoric is far more complex than this, and it is for this reason that I provide the following abbreviated history of the subject before detailing contemporary definitions of trolling. This history illustrates that trolling can be traced back at least to Ancient Greece.
The Mythic Origins of Trolling
In the process of investigating the history of rhetoric, Socrates, Plato, and Aristotle all appear to exhibit behavior that adheres to the Urban Dictionary definition of trolling, quoted above, “the art of deliberately, cleverly, and secretly pissing people off… using dialogue.” However, even if we do decide that their behaviors towards the Sophists can be considered trollish behavior, this does not mean that trolls did not exist prior to the period that produced these Athenian Philosophers. Trolls of this variety exist in myth- not as literal trolls, as these mythological figures are often easily out-duped, but as Tricksters.
A handful of figures from world mythologies, Hermes, Odysseus, Papa Legba, Coyote, Raven, Loki, Monkey, and Eshu all represent variations of the troll within the character archetype of the Trickster. Each of these figures are involved within mythologies wherein they too “deliberately, cleverly, and secretly” use their words to deceive another party for their own amusement. Sometimes, as appears to be case with our trio of philosophers, these Tricksters have their own political reasons for their individual acts of trolling, such as Hermes’s desire to evade trouble with Apollo, Papa Legba with his desire to get revenge on his mother, Loki with his disdain for the Aesir, or Monkey’s need to protect his subjects from the monster that is terrorizing them. Other times, as is the case with Odysseus in his famous encounter with Polyphemus within Homer’s Odyssey, survival rests upon the trickster’s ability to troll and conceal one’s identity through clever wordplay. A much more detailed analysis of these Tricksters appears within Lewis Hyde’s Trickster Makes This World, albeit Hyde does not explicitly investigate inherent troll characteristics within the Trickster archetype, nor does Hyde cover all of these Tricksters equally.
But what is a Trickster? Are there any aspects of a Trickster that differs from a troll? 
In the advent of Donald Trump’s presidential bid, a malevolent internet troll presence has gained traction regarding what has since been called the Alt-Right Movement. Using rhetoric that can be classified as sexist, racist, xenophobic, anti-Semitic, homophobic, transphobic, or other variations of discriminatory language, the Alt-Right Trolls take pleasure in “triggering” liberal Internet users into side-stepping their positions and responding emotionally. Much like Socrates within Gorgias, the Alt-Right trolls use their victim’s emotional outbursts to highlight what the Alt-Right perceives as hypocrisies undermining liberal arguments and/or to shut down conversations that advocate against conservative values by denying opposing views from presenting any form of logical argument. It may not be outrageous to suggest that aggressive trolls like those within the Alt-Right Movement are analogous to the Athenian Philosophers. Clearly then, political trolling is not a new phenomenon, even if the digital spaces where this kind of trolling takes place are a fairly new to this kind of rhetorical art

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