I think it is possible to create a “Universal Media Literacy Machine” in the same way Alan Turing created a “Universal Computing Machine.”
Alan Turning, the fundamentally complicated and brilliant mathematician, suggested, in his groundbreaking 1936 paper, that a “Universal Computing Machine” could be built that could “compute any computable sequence.” Simply put, Turing was proposing that, unlike any computing machine built up until then, a machine could be built that could easily change its computing process based on the computing problem. And, what is most amazing to me about his proposal is that in spite of the huge innovation in thinking, his idea is breathtakingly simple.
In the times before Turing, a computing machine could only be built to do one thing. An addition machine would do addition. A multiplication machine would do multiplication. And so forth. Turing Proposed that a machine could be built where the “rules” for the computation could be “taken out and exchanged for others.” Not just a programmable computing machine, but a re-programmable computing machine.
Why couldn’t a similar solution be applied to Media Literacy? Why can’t Media Literacy be viewed as a computational problem similar to a math problem? Why can’t the process of determining the “value” of a piece of media be the same as computing the value of 1+2?
Here is the model proposed by Turing in his paper.
There are 3 basic elements: #1) the Tape = the data, #2) the control device = the CPU, and #3) the states: 1…n = the program. The fundamental development Turning proposed was element # 3 the program. Turing proposed that the program could change based on the problem. And, most importantly the program could actually change itself. This idea of a “re-programmble” machine that could re-program itself based on what the data presented was a revolutionary idea.
Now let’s apply this to media literacy.
First let’s define the terms:
- Element #1) the data = all the searchable text, pictures, and videos available.
- Element #2) the CPU = any computer/device that can access the data.
- Element #3) the states = the application that would scan the data and output a conclusion.
Now, let’s use an example.
Let’s start with #1) the data:
This is from http://www.redstate.com/diary/alecstates/2017/01/16/scott-pruitt-can-bring-fresh-leadership-reform-epa/
Over the past eight years, the Obama-led EPA has unleashed an onslaught of harmful, job-killing regulations all while chipping away at the cooperative federalism model that has long undergirded the agency’s relationship with the states.
Now let’s apply #3) the program
Here the 5 Media Literacy Questions the program would ask. The answers to these question would then better inform the consumer of the media. Some of the answers will be “objective” like “who created the message” and “what techniques were used to attract attention.” The others are somewhat subjective. But, never-the-less, answers could still be found to all the question, even given the subjective constraints.
I want to add one more thing to this. Since elements #3, #4, and #5 are somewhat subjective. We need to add a way to value the subjectivity of these elements. The way to do that is through human evaluations and transparency to those humans so the reader can value the subjectivity for themselves.