Week 8: Programming & Publishing – the future of the industry

Happy Halloween! After reading week, the Tuesday cohort came together (some in costume, some not) on Halloween, just before the spooky festivities would be beginning outside the classroom.
We started off by reviewing last week’s topics and discussing the latest blog post question. The question led to an in-depth debate on what “proper” publishing is and whether traditional publishing solely encompasses that. Then after an enrapturing presentation from some of our classmates on the Twilight novels, we delved into the subjects of the week 8 lesson.

Image sourced from SEO

Owen (looking very dignified in a pickle costume) started off by having us look at digitization, digitalization and automation. Each has varying levels of human involvement, and he explained what that meant in terms of traditional publishing. While digitization relies heavily on human involvement, automation is the idea of machines working and doing these jobs with no help at all. This was further dissected by an article from Gideon Rosenblatt which unpacked automation in terms of publishing, looking at employment and product.
Next, we looked at the Turing test – how the test may one day not be able to distinguish between AI and humans. It’s likely to start with poetry — seeing as poetry already has (purposefully) strange word choices, the test may become muddled with AI’s “works”. We discussed AI generated stories and writing, how it can compare to human authors. Several points were made about the morality and difference in tone between the “writers”, which circled back to the Turing test and its usage. Owen also mentioned GPT-3, a natural language system. It was designed solely to predict the next word in a sequence of others. It is fascinating and terrifying – incredibly articulate and has since recognized problems in itself and fixed them on its own accord, surprising even its programmers.
All of the previous topics led into discussion of bias. Artificial Intelligence takes information and writing from the internet, somewhere well-known to often harbor hateful, prejudiced and cruel ideas. So it isn’t unexpected that the program would repeat and recycle these ideas in its own generative writing.
After this, Owen taught us about periodicals. Specifically, the different types of periodicals. Popular magazines and newspapers are usually written for general audiences, though many popular magazines are written for special interest readerships, such as the famed Cat Fancy Magazine. They are also profit-driven, writing what they believe will sell the most copies. Trade periodicals are written for a specialized readership, writing more in-depth on articles written for and pertaining to said readership. Lastly, scholarly periodicals are academically motivated publications, relaying lengthy and comprehensive articles written for an audience with a high-level reading comprehension. This was important for us to understand, as we had all just done our Periodical Case Study assignment.

Image sourced from The University of Sydney

This weeks class was interesting and nuanced. While I found the topic of periodicals to be important, I wanted my discussion question to reflect the first half of class. Namely; is there a way to ethically incorporate artificial intelligence into traditional publishing? If there is, I imagine it to be a revolutionary concept for the industry. I’m excited to hear people’s opinions, and for next weeks class. Huzzah!

– Quin B