A Kierson

Prototypes

Most prototypes should answer a question: Is this feasible? Will people hate it? Does this project achieve its purpose? For these prototypes, there were three areas that needed to be prototyped: role, look/feel, and technical

I created some early musings about the project. I was trying to decide on the best method of using a typewriter as a printer and how best to write poems from streams of words.

Role

For my role prototype, I looked at art installations that interact with the viewers and created a short storyboard from those. The idea was that the typewriter would appear apart from the gallery until the viewers leave and notice that the typewriter has made a poem just for them.

Look/Feel

For the look feel prototype, I purchased a word processor and set it on my desk for a few days to decide if it was cool enough. I also looked at the Media Archaeology Lab for more refined typewriters such as the fully mechanical ones. I decided that the typewriter should ideally be connected to the computer housing in a permanent way.

Next, I sketched some tables-housings. The table design should ideally match the typewriter. If I am able to get a mechanical typewriter, the table should be a refined one but, if I can only get a word-processor, a plastic table is almost preferred.

Technical

For my technical implement, I did several iterations on the same algorithm of using Markov chain text and the nltk Python library. The algorithm would take in a string of text, the longer the better. I used the Sugar Hill Gang’s “Rapper’s Delight” and the full corpus of Shakespeare’s sonnets.

I first started with haikus as 5 -7 -5 to test out the syllable library. Next, I made basic sonnets of 14 lines with 10 syllables each in the style of Shakespeare. My last step was to add rhymeing in the form of ABAB-CDCD-EFEF-GG. I ran into some trouble because occasionally words don’t have rhymes, but in a further prototype or the final iteration this could be achieved through recursive programming and chaning the parameters each time. This would allow for less exact rhymes and for the program to rewrite lines that don’t fit into the sonnet.

https://github.com/akierson/capstone-prototype

What do prototypes prototype?

• Create prototype for audience
• Should show roles, implementation, look and feel

For my prototype, I would like to make a working prototype of converting a data stream into visual graphics. Specifically, I would like to work toward an Authenticity app and the fashion side of this. Though it is nebulous, I think by using sample data from Google trends and Twitter data I could compile the relative popularity of common brands such as Nike and Adidas by urban area.

By creating a focused data set and having set desired outcomes, I could work towards a more nebulous idea of assigning regional popular to various items using data scrapped from various websites. There will be the added challenge of having to backpropagate my data based on future sales releases and data from the aforementioned companies.

However, if scarpaing the data from Instagram, Twitter, and Google proves harder then expected (as they are tightening their APIs), I may also look into fake fashion writing by analyzing top fashion blogs and associated images and counterfeiting them. This coulld also be incorporated into taking pictures of viewers and spitting out a fashion/tablod piece on them.

AAR: Case Studies

I looked into several projects that circled inthe general direction of my project. I am still missing one idea but the other three are almost fully fleshed out.

Klout

The first case study is Klout. It was an early attempt at codifying someone’s personal impact on social media with a single numeric metric. There were several issues with this. Critics of it came from both sides a the social media gamut. The proponents of social media said that codifying social media into a single number showed users the man behind the curtain and that metrics should be more holistic. They believed that users would modify their behaviors if they were shown how the direct impact of their actions in a “Hawthorne Effect”. Critics of social media worried that giving users the tools to enhance their social media presence would lead to things like the Cambridge Analytica incident in 2016. Of course, they ended up being right.

I also found it interesting to look at how, while heavily criticized for trying to gamify social media, Klout changed how social media giants track data and use data. Facebook and Instagram changed their timelines to increase attention. Facebook also started to offer data tracking to companies in exchange for their data. Other apps have also tried to capitalize on the void by appealing to “influencers” on Youtube and Instagram.

Deepfakes

My second case study is on Deepfakes and GAN. GAN, generative adversarial networks, were first proposed by Ian Goodfellow in 2014 as a new way of training neural networks, whereby a generator neural network is taught to try and convince a detector neural network it is legitimate. He made the analogy to counterfeiters and police. Deepfakes, a portmanteau of “deep learning” and “fakes”, arrived two years later as fake celebrity porn. A Reddit user by the same name had usedGANs to mask the face of celebrities onto adult actresses. This opened up the whole conversation of what lines this crossed, what it could be used for, and if we could ever trust images and videos again. Since then, interest in Deepfakes has waned outside of porn studios.

I found it interesting to look at as it is the cutting edge of creating fakes and can be used to fool all but the most trained eye. While making a porno of the founding fathers would be interesting, it is also interesting to look at how it had a sudden spike in intest and then people forgot about it as though they couldn’t be fooled.

PhoneStory

The third case study is on informing the public. I wanted to look at PhoneStory by MollieIndustria. PhoneStory tells the story of creating an iPhone with a series of dark minigames. It was quickly removed from Apple’s AppStore but has since been added to Google’s Play Store. I wanted to look at how the public can be informed about the error of their ways in non-aggreivating ways.

Subversion

For my last case study, I wanted to look at something subversive. While most of the previous case studies can be construed as subversive, it was not their explicit intent. I wanted to look at something that subverted the commercial narrative. I looked into Garbage Pail kids and the uthors previous venture, Wacky Packages. However, the pictures were often not political and solely sold for their shock and wae. I was also ooking at other rtist’s efforts to create pieces to raise convecern about McDonald’s , The Catholic Church or others. Lastly, I am looking at other commercial attempts to high jck diasters or others to subvert the narrative. in their favor.