Speculative Future – LMS & NFT

Prologue

In a not-so-distant future, flying cars do not dot the skies, Mars still has not been colonized, and machine learning is limiting the potential of young adolescent students. The year is 2052, learning management systems (LMS) have grown far beyond the scope experts could have foretold. As Sciarrone predicted, neither students nor teachers are bound to a specific location (2018). LMS extracts useful information from learners’ data and supersedes the expectation of inferring students learning styles (Sciarrone, 2018). Teachers have become obsolete and have been replaced by moderators in epic-sized Massive Open Online Courses (MOOCs). To occupy their time, adolescent students collect and trade non-fungible token cards in hopes of improving the likelihood of achieving a brighter future that machine-learned analytics tools do not see in their future. Continue reading

Judging others’ behaviour should not be complicated, but it is. This week’s task facilitated a hypothetical situation where we, as judges, had to choose whether to detain or release individual defendants. The three factors were the defendants’ likelihood of failing to appear in court, the probability of committing a crime if released, and whether that crime would be violent. Setting about judging each individual and having the opportunity to view their pleads to be released was heart-wrenching. Some claimed they would lose custody of their children, and others sought medical attention that would not be accessible if they were detained. 

I have learned that I am a terrible judge and that Keith Porcaro’s goal of demonstrating the dangers of using algorithmic risk assessment tools can lead to inaccuracies was right. Keith set out to show his students “think[ing] critically about how software and data-driven tools can influence legal ecosystems — sometimes in unexpected ways” (Porcaro, 2019). For instance, what I found affected my judgement was the jail’s capacity and fear generated if I had released a defendant the had committed another violent crime. In a sense, my experience was similar to how a machine learning program can be taught to differentiate between a cat or a duck. By using something like a classification application, an algorithm could differentiate between “deciding that some combination of features constitutes a car or a stop sight” (Moyer, 2021). My original task of weighing morality was changed. Instead, the task simply became limiting fear and exceeding the jail’s capacity. 

A computer algorithm’s ability to process data to aid in deciding if a defendant is likely to offend should not be left alone to computers. Although, using computer algorithms and data analytics as a way to aid in making consistent decisions would be a worthwhile exploration in the field of data analytics and AI. 

Check out this podcast by Radiolab that further explores the idea of responsibility within justice and how the time of day may affect our decision-making. 

Radiolab – Revising the Fault Line

Continue reading

Data Analytics – Golden Record Quiz Data

The data set that has been imported into Palladio is represented in the form of data visualization. Data visualization is a helpful tool in data analytics as it can be used to shed light on massive accumulations of data. It makes summarizing data easier and more digestible for a researcher. As Hoppe explains, data analytics “exemplify[s] challenges and potential benefits of using advanced computational methods that combine different methodological approaches”(Hoppe, 2017) to building knowledgeable communities. The use of a web-formatted graph that is able to be stretched and be pulled is marvellous as it provides a researcher with the ability to draw information for the data set in real-time. The benefits of a plug-and-play graph like the one in Palladio also has it’s own drawbacks. With the qualitative data presented, it is challenging to grasp the relevance of the songs my peers had chosen as their Golden Record Task from week eight. Variables such as musical taste, age, understanding of music theory, or even cultural backgrounds may have influenced their choices. Due to a lack of quantitative data, I felt aligned with Lexie Tucker’s goal to narrow the twenty-seven songs down to just ten. My goal was to choose ten songs that represented earth’s vast creativeness rather than a song’s popularity. Tucker’s goal was to “include songs that were representative of our world as a whole and not simply the winners.” (Tucker, 2021). With this in mind and what I felt were similar goals, the ten songs we had selected from the original twenty-seven were far from the same. Tucker and I shared just five choices out of ten. 

Wedding song – Peru

Morning Star and Devil Bird- Australia

Fairie Round – cond David Munroe

Tchenhoukoumen, percussion Senegal

Fairie Round – cond David Munroe

The odds of us choosing the same five songs is 1/125. Even more staggering, the chances of choosing the same ten songs is 1/225. These odds are not as vast as, let say, if we had to pick the same ten songs in the same order, which would come out to 1/30,613,591,008,000. Regardless of the odds, attempting to draw assumptions without further understanding and qualitative data or discussion is merely futile. Our own personal and life experiences are part of why collecting and observing data can be skewed depending on what form of data is presented and analyzed.

I am leaving this task with gratitude that with the development of the internet, a learning tool such as Palladio has made data analytics accessible for a thought experiment that I can only imagine would have taken months to complete otherwise. 

Continue reading

Attention Economy

I had a difficult time completing this task for what I believe is for two reasons. First, I had to unlearn all the navigation skills I had built up over my lifetime to surf the internet. The second is the website User Inyerface is dumb and purposefully designed to frustrate users. It has employed dark patterns in an almost comically frustrating way while not abiding by user experience (UX) and user interface (UI) principles. 

The Laws of UX (2020) by Jon Yablonski had curated the best practices a designer would possess to build a successful user experience. These practices were divided into categories such as heuristic, principle, gestalt and cognitive bias. Each category contributes and is considerate of what it takes to enrich a user’s interaction with online tools and space. On the other hand, dark patterns have used similar principles but have taken a more sinister approach to “take advantage of our customers in the most effective manner” (Brignull, 2011). Navigating through each step of the User Inyerface website involved much more care and attention in order to avoid having to re-complete fillable windows or waste time exiting pop-up windows. 

Contrarily, the user interface is more focused on the design of software or websites. The user interface design can be summarized down into four key factors as highlighted by Nick Babich in his article, The 4 Golden Rules of UI Design (2019). Babich’s key ideas aid in guiding users to use technology to navigate different designs within the software effectively. The key points consisted of:

  • Place users in control of the interface
  • Make it comfortable to interact with a product
  • Reduce cognitive load
  • Make user interfaces consistent

Nevertheless, User Inyerface managed to do the complete opposite from what Babich has highlighted as the key points of consideration for the user interface. It is the principles from both Yablonski (2020) and Babich (2019) theories that are skewed and meddled with that Brignull (2011) highlights as dark patterns that are employed in a sinister way by User Inyerface to frustrate and manipulate users.

Continue reading

Golden Record Curation – The best of the best?

I had chosen the following digitized musical pieces from the Voyager’s Golden Record (Bevisangue, 2008) on the premise of representation rather than popularity. Content is often popularized due to its ability to be shared and viewed. Just as the digitized musical pieces had been chosen on their merit to portray the diversity of culture on Earth, narrowing down the twenty-seven tracks to ten posed quite the difficult task. I feel the pieces I have chosen accurately represented the world upon the Voyager’s departure and resemble the diversity that the digitization of the original works hoped to preserve.

Continue reading

Mode-Bending What is in My Bag

My redesign of our class’s first task in a new semiotic mode takes inspiration from the digital literacy difficulties created by a digital divide. As Dobson and Willinsky describe, “print and digital forms of literacy… is often overlooked, much is made of the democratic qualities of digital literacy, as it affords greater access to knowledge as well as the ability to speak out and make one’s views widely available.” (Dobson & Willinsky, 2009) The ability to access information that is not necessarily scholarly in nature, although informative, has effected the “growing global dimensions of people’s participation in digital literacy… [,] a worthwhile human rights goal.” (Dobson & Willinsky, 2009)

Whilst digital navigation may come to many users without much difficulty. Users’ age and the opportunities afforded to users to assess varying forms of digital media may limit their ability to navigate various forms of digital communication literacies effectively. 

As such, while reusing the original audio from our first task. I have embedded screenshots taken from the search results of images I had taken of each item from my bag from the Google Lens tool. Each screenshot is not necessarily challenging to pick information out of. Although, at particular points, it may be difficult to process or locate where exactly a viewer should be looking in order to grasp what item is being described in the video. 

Continue reading

Potato Printing Press

As with most famous last words, starting this task thinking to myself, “how hard can this be?!” should have been my hint I was drastically overestimating my potato carving abilities. Taking inspiration from the late Bob Ross, “We don’t make mistakes, just happy little accidents.” I found myself with many accidents—each of which could have been easily avoided if I was in the mindset of a printing press craftsman.

After beginning the task of cutting out the potato stamps, I stumbled across my first problem. I need to make dinner. Very carefully, I quartered a single small potato to create my stamps. With only four pieces, I carved out my “r” and “h” stamps on a single potato chunk. Feeling confident and resourceful, I marched outside and began stamping. Stamping the potatoes with a steady hand went well. Although, to my utter disappointment, I realized I should have mirrored the letters for my potato stamps. Each letter other than “c” and “i” needed to be flipped in order for them to be read in the correct direction. As Leigh writes, “When our writerly spirit is crushed, we develop what I call writer woundedness, a state of being that prevents us from trusting ourselves as capable of writing something we can feel good about.” (p. xi). On top of a spelling error on my second go-around, it occurred to me I should be writing the whole word backwards and flip the photo on my phone. Taking my errors in stride and realizing how much we take for granted the luxuries or mass production distribution of written work.

The process of mechanizing my writing took less than an hour. It was incredibly hilarious as I discovered what must have been novice problems only an apprentice printing press artisan would have made. Considering I had pristine paper, paints of any kind within a 15-minute drive, and the finest of potatoes, the speed at which I could experiment with the mechanize my writing seemed artificially enhanced and too easy.

References

S Rebecca Leigh. (2014). Wounded Writers Ask Am I Doing it Write? Rotterdam Sensepublishers.

Voice To Text

Hey there everyone!

For this post, I will be delivering an unscripted narrative of the events and steps of stock breakout. Using google voice type, whatever I have spoken will be accounted for and converted into writing. Needless to say, voice type got the job done but is not perfect. Click on the link to view the unedited voice-to-text paragraph. If you would like, listen to the record that I had done simultaneously with the voice-to-text passage. See if you can spot some of the differences that I had between the recording and voice-to-text portion.

I find it astonishing that in a matter of milliseconds, the Google documents tool, voice typing, was able to processes my speech, best present the text, and simultaneously record what I was saying in writing. It is as if the words I had spoken had become material in an instant. This pales in contrast to the first forms of record-keeping used 5200 years ago in Mesopotamia. Where farmers shaped and backed clay to measure the amount of produce they had or were owed. The meticulous time these farmers had to perfect the shape of their clay wasn’t a luxury that Google’s voice typing gave me. I was astonished that voice typing could keep up with my fast-paced rhetoric. Although, a lack of clarity, perfect pronunciation, and slang may have lent to more than a dozen botched interpretations. Here are several of my favourites :

  • for sending – or something
  • table – stable
  • my pink cupping – might be cupping
  • cut it to link – cut it to length
  • boat I’m – bowtie
  • weave – we’ve
  • is a zoo quickly see – cuz as you’ll quickly see
  • 567 in – 5, 6, 7 inches
  • stock has been – stock that’s been

At no fault of its own, Google’s voice type had done its best to make meaning of the meaningless pauses, hesitations and sounds I made while pondering where my train of thought was taking me. There was a brief moment in the recording at one minute and fifty-six seconds where I had made a mistake and acknowledged out loud that there was no going back. Sure enough, that error was evident in the voice-to-text conversion.
Once more, I had another brain fart and looked at the screen as it was recording and exclaimed, “sorry I’m looking at the screen now I’m getting a little bit distracted as these words are coming up, [it’]s pretty fun” at three minutes and eighteen seconds. Just as I was susceptible to making mistakes as I talked, spoking succumbs to its own problems. Whiles language can be influenced by accents, speech impediments and informal slang. The writing process is filtered, paused and edited until perfection. Written language is often stringently enforced and regimented for ease of use. Whiles many people can communicate relatively easily and understand each other regardless of slang and accents. Writing allows anyone to read and understand what was try to be communicated.

Listening back to the recording and reading through the artifact that my own voice created. I have a weird sense of pride that the person I am had a moment to shine unfiltered and unedited. I would not attempt to create and share unedited work like this with my students. Although, at this moment, I now understand the struggle humanity has faced in documenting oral traditions and stories. Even though we may pull words from oral stories and preserve them, such stories may lose the meaning and emotion our elders and ancestors had once given them. Considering the many forms of communication that have developed in the past century, like video, augmented, or virtual reality medias. Such content may have bridged the gap in preserving the intended means of communicating face to face that written storytelling has lost whilst voice-to-text may be attempting to bridge.