Andrea Ness MET website

Microsoft Copilot Generated Scenario

Prompt used: Describe a corporation found a century into a future in which society as we know it has come apart. Address issues related to class and elicit feelings of anger.

Scenario: Horizon Resource Dynamics, 2125

In the year 2125, long after traditional governments fractured under climate migration and economic collapse, Horizon Resource Dynamics presents itself as humanity’s “stabilizing force.” In reality, the corporation functions as the world’s de facto ruling class, operating through a network of privatized security forces, patented food systems, and vertically integrated housing enclaves. Horizon’s corporate slogan—“We provide what remains”—is displayed in every settlement that still has electricity.

The corporation’s origins were modest: a logistics company specializing in water purification. But when state infrastructures failed, Horizon purchased entire regions outright, including reservoirs, fertile land, and the digital backbone that once supported public communication networks. With these acquisitions came power—quiet at first, then absolute.

Horizon operates through a three-tiered class system that it insists is “merit-based,” though no one can name a single case of mobility. At the top are Asset Holders, a fraction of the population who own shares in Horizon’s terraforming and bio-engineering ventures. They live in sealed climate-controlled towers called Vertical Havens, complete with imported air, synthetic gardens, and drone-delivered meals. Despite claiming that these towers are “model communities,” no one outside the Holder class has seen their interiors. Unauthorized viewing is considered a breach of bio-security.

Beneath them are Contributors, the trained specialists who maintain Horizon’s infrastructure. They are granted limited healthcare, sterilized water rations, and housing in modular blocks known as Function Settlements. Contributors sign perpetual labor contracts, though Horizon advertises these as “lifetime opportunities for stability.”

At the bottom are the General Populace, the billions displaced by the collapse of ecological and political systems. They live outside Horizon’s protective shields in sprawling unregulated zones referred to euphemistically as Open Terrain. Horizon’s public service announcements repeat a single message to these communities: “Compliance ensures access.” But access to what is never specified.

The corporation’s newest invention, the EquiSync Band, is marketed as a wearable “equity assistant” that monitors individual behavior and recommends pathways to “personal advancement.” In reality, the bands track movement, measure compliance, and relay biometric data to Horizon’s classification algorithm, CLARITY, which determines ration eligibility. Citizens without bands are marked as “voluntary non-participants,” rendering them ineligible for aid.

Perhaps the most infuriating aspect of Horizon’s regime is its tone. Every quarterly broadcast begins with cheerful music and a smiling spokesperson saying, “Together, we rise.” Meanwhile, children in Open Terrain walk miles to access alkaline water. Aging Contributors are quietly relocated to “Efficiency Centers,” from which no one returns. The Asset Holders continue to drift between their towers in personal sky-transit shuttles, untouched by the consequences of the world they profit from.

Horizon insists it is “the guardian of humanity’s future.” But the future it guards is not for everyone—only for those who can afford to belong.

Reflection

After I ran the prompt through AI to create a scenario about a future corporation in a collapsed society, my first thought was how predictable the shape of the future was. Copilot produced something that looks sophisticated on the surface (clean phrasing, polished descriptions, confident world-building) but underneath, it felt like a regurgitation of familiar dystopian tropes assembled without much creative license at all. Instead of imagining something new, the AI is obviously reassembling ideas that have already been culturally digested and fed back into the machine as training material. It’s less a story about 2125 than it is a mirror of the stories our present-day media already finds plausible, comfortable, or at least narratively acceptable.

One of the clearest patterns in the output is its default assumption that corporate totalitarianism will replace the state. Copilot immediately jumps to the idea that if society collapses, a corporation will take charge through branding, surveillance, and soft authoritarianism. I didn’t tell it any of that, it just went there. That reveals how deeply entangled “the future” is with corporate power in the cultural data the model was trained on. Inayatullah’s idea of “used futures” comes to mind here: the model isn’t imagining alternatives; it’s repeating a future we already know too well (Inayatullah, 2008).

The tone was another interesting tension. It slips into a sort of mock-corporate PR voice (“We provide what remains”), but it stays safely outside anger, even though the prompt explicitly asked for emotion. It sounds cold, almost clinically detached. Instead of narrating anger, it places the responsibility on me, the reader, to supply the anger myself. This avoidance feels like an algorithmic safety instinct, an unwillingness to cross into anything that might look like incitement. This avoidance of  responsibility actually reminded me of the real-world story of the Uber self-driving car fatality in Tempe, Arizona in 2018. In that case, the car’s AI hesitated when classifying a pedestrian and ultimately passed responsibility back to the human driver at the last possible moment (Greenspan, 2021). It knew something was wrong, but it didn’t escalate loudly. The system couldn’t slam on the brakes, and didn’t want to disrupt the ride, so it quietly slipped out of autopilot, with devastating consequences. In a softer rhetorical way, Copilot does something similar: it recognizes harm and injustice, but it refuses the emotional escalation. It hands the affective labour back to me.

Class is technically addressed in the narrative, but in a very administrative way. The model uses capitalized labels: Asset Holders, Contributors, General Populace, as if class were simply a filing system instead of a lived human experience. It treats inequality like something you might diagram in a corporate PowerPoint. Again, that says something about the current worldview of AI that class is an org chart, not a social or emotional reality.

The invention of the “EquiSync Band” was almost bit too on-the-nose. A device that pretends to promote equity while actually performing surveillance feels uncomfortably close to how tech companies already deploy benevolent-sounding language to justify data extraction. It’s exactly the kind of techno-solutionist gesture speculative designers warn about; something that looks ethical on the surface but embeds deeper forms of control (Auger et al., 2021).

Stepping back, the whole scenario doesn’t feel like a leap into the future at all. It’s basically our current fears (surveillance, inequality, corporate overreach) just turned up a notch. And what’s missing stood out just as much. There’s no sense of people pushing back, no community support, no alternative ways of living, no voices outside a very Western, very corporate frame. Copilot isn’t imagining a new world so much as replaying the one we already know, only slightly darker. That’s where my job comes in, not just to notice those limits, but to look past them and imagine something truly different.

Why I Created This Propaganda Poster

I decided to make the Horizon propaganda poster just to see what the “official messaging” of this future world might look like. Copilot’s story talked so much about branding and slogans that it felt natural to imagine what their posters would actually say. Creating it helped me picture the world more clearly, while highlighting how creepy it is when cheerful messaging gets used to cover up something more sinister.

References

Auger, J., Hanna, J., Mitrović, I., Encinas, E., Božanić, S., Šuran, O., & Helgason, I. (2021). Beyond speculative design: Past – present – future. SpeculativeEdu / Arts Academy, University of Split.

Greenspan, S. (2021, September 28). Cycle 1: Databody [Audio narrative]. Bellwether. https://thisisbellwether.bandcamp.com/album/cycle-1-databody

Inayatullah, S. (2008). Six pillars: Futures thinking for transforming. Foresight, 10(1), 4–21. https://doi.org/10.1108/14636680810855991

Task 11: Detain/Release 

Completing the Detain/Release simulation left me feeling surprisingly frustrated. I kept wanting more information. More context, background, even a fuller description of what actually happened in each case. Instead, I was pushed into making decisions that felt high-stakes with very thin evidence. In a strange way, that irritation became part of the lesson. It highlighted how precarious things become when algorithmic risk scores are treated as if they can stand in for real knowledge.

This week’s podcast episodes shaped how I approached the simulation. Listening to the story of Jack Maple and the creation of CompStat, I expected something very different. At first, it honestly made me think of Moneyball. I imagined Maple as the Brad Pitt/Jonah Hill figure of policing; using statistical patterns to make smarter predictions, prevent problems before they happened, and rethink a system that felt stagnant. I assumed the NYPD would use those maps and numbers to increase efficiency in a genuinely helpful way, the same way baseball teams used player stats to rethink strategy.

But the more the podcast unfolded, the more that optimism collapsed. Instead of using data as a way to understand the complexity of neighbourhoods and allocate resources responsibly, CompStat became a justification for over-policing. The numbers that were supposed to reveal patterns ended up hardening stereotypes, especially about Black communities. It felt grim to realize how quickly a bright-eyed idea about “intelligent policing” had slipped into a mechanism for reinforcing deeply racist assumptions. At this point I was also reminded of an immigration algorithm I heard about at an AI conference I attended years ago. There, the speaker had explained how Immigration, Refugee and Citizenship Canada’s algorithm flagged visa applicants with the name “Mohammed” at disproportionately high rates because it had been trained on years of biased human decisions. The algorithm didn’t invent racism, it inherited it. And once it was embedded in the system, it became even harder to challenge. In both cases, statistical data became a kind of shield that makes harmful decisions look objective, even though they’re trained on human bias from the start.

That memory from the conference stayed with me throughout the simulation, because that’s how the simulation felt, too. The risk scores were presented as helpful prompts, but without adequate context they started to feel like the only “real” data available. But where did they even come from? I started to realize that even when I disagreed with a recommendation, the structure of the task nudged me toward treating the score as authoritative, simply because everything else was so ambiguous. It made me realize how easily an algorithm can shift from being a tool that informs judgment to quietly becoming the thing that determines judgment.

For me, the biggest takeaway is how important it is to preserve the human role in these processes. AI can highlight patterns, speed up workflows, and reduce some forms of inconsistency, but it cannot understand the social, historical, or relational contexts that make each case unique. When decision makers rely too heavily on algorithmic assessments, especially ones trained on biased data, the harm compounds over time.

Ultimately, this week reinforced something I’ve believed since that conference, that AI can be incredibly useful, but only when it remains a supporting voice and not the final one. The minute we let statistical patterns harden into unquestioned authority, whether in policing, immigration, or pretrial decisions, we risk turning tools meant to help us into systems that quietly perpetuate the very injustices they claim to solve.

References

Detain/Release. (n.d.). Simulating algorithmic risk assessments at pretrial. https://detainrelease.com/join?room=MMVBN

Reply All. (2022). The Crime Machine, Part I & II (Episodes 127–128) [Audio podcast]. Gimlet Media.

Using Palladio, a data visualization tool from Stanford, we were able to map our Golden Record music choices and see how they connected across the class. Once the file loaded, it was actually pretty interesting to explore, though it also felt a bit strange to see something as personal as musical taste turned into dots and lines. It was fun to click around and look at patterns, but I quickly realized that the real challenge wasn’t in reading the visualization, it was in figuring out what it actually meant.

When I set the graph with “curator” as the source and “track” as the target, four main communities appeared. Each one showed a different kind of listening pattern. One cluster leaned toward Western classical pieces like Bach, Beethoven, and Stravinsky. These pieces are very structured and familiar. Another community grouped around rhythmic and percussive music, such as the Senegalese drum ensemble and Melanesian panpipes, where the beat and repetition take centre stage. A third community leaned into folk and vocal traditions from around the world; some example include the Navajo Night Chant, Jaat Kahan Ho, Flowing Streams. These are sounds that feel rooted in culture and storytelling. The last group focused on more on modern, emotional, and raw music, like Blind Willie Johnson and Chuck Berry, where the feeling seemed more important than form.

When I compared my own results to the class data, I noticed my selections (like the gamelan, panpipes, shakuhachi, and blues) sat somewhere between the folk–percussive and emotive–modern clusters. That felt right. In my notes, I had described those pieces as layered, alive, and human. I gave each track a score out of ten and wrote down three words to describe its sound or feeling, even for the ones I didn’t enjoy. Looking back, those small reflections helped me understand why I gravitated toward music that felt textured, rhythmic, or emotionally grounded. The Palladio map showed the overlaps between us, but it didn’t really show why we made those choices.

Something our professor said in his short Palladio tutorial video stuck with me. He mentioned being surprised that “Johnny B. Goode”wasn’t more popular. I was surprised too. It’s one of the most recognizable and energetic songs on the record. My guess is that, for many of us, the activity wasn’t just about picking what we liked personally, but about what we thought could represent humanity. Rock and roll might have felt too specific or too much about a certain time and culture. While other tracks, like the gamelan or panpipes, carried a kind of timelessness. Maybe that’s why a song we all know so well didn’t stand out in this context.

In the end, I think that’s what makes the visualization so interesting and also a bit incomplete. It shows who shared musical choices, but not what shaped those decisions, or what we felt listening to them. It captures the data, but not the stories behind it. In a way, it’s like the Golden Record itself: full of sound, yet traveling through silence. What it carries isn’t the music itself, but a trace of the people who chose to send it.

In selecting my ten pieces from the Golden Record, I relied on a mix of emotional resonance, descriptive reflection, and personal enjoyment as my main criteria. 

For each of the 27 tracks, I wrote three descriptive phrases to capture its atmosphere and feeling, which helped me notice recurring qualities like rhythm, texture, and mood that drew me in. 

I also rated each piece out of ten to measure how strongly I connected to it on a personal level. This process helped me balance intuitive response with reflective listening, leading me to choose the ten pieces that felt most alive, emotionally engaging, and representative of the diversity and creativity of human sound.

My final selections were:

1. Bach – Brandenburg Concerto No. 2 in F, First Movement (Germany)
2. Beethoven – Symphony No. 5, First Movement (Germany)
3. Stravinsky – The Rite of Spring, Sacrificial Dance (Russia)
4. Blind Willie Johnson  – Dark Was the Night, Cold Was the Ground (United States)
5. Chuck Berry – Johnny B. Goode (United States)
6. Javanese Gamelan – Kinds of Flowers (Indonesia)
7. Navajo Night Chant (Native North America)
8. Melanesian Panpipes (Solomon Islands)
9. Percussion Ensemble (Senegal)
10. Japanese Shakuhachi Flute – Crane’s Nest (Japan)

I chose not to include any of the spoken greetings or images from the record because I wanted to focus purely on sound as a universal language. Words and pictures rely on shared symbols and interpretation, while music communicates using elements that might transcend culture or species. By concentrating on the musical selections, I was drawn to how sound itself becomes the message, carrying traces of human expression even without translation.

In choosing these ten, I aimed for a balance between diversity, emotional impact, and sonic variety. I wanted to include music that feels deeply human and expressive and could be felt even by a being who doesn’t share our culture or language. The combination of ancient ritual music, folk traditions, and modern compositions reflects both the range and the restlessness of human creativity. And yet, I can’t help but be struck by the irony that these sounds now travel through the silent vacuum of space, where sound itself cannot exist.

References

• Music from Earth.Links to an external site. (n.d.). NASA.
• Taylor, D. (Host). (2019, April). Voyager golden recordLinks to an external site. [Audio podcast episode]. In Twenty thousand hertz. Defacto Sound.

Keys, Phone, Headphones

This short ASMR-style audio piece remediates my “What’s in my bag” task into sound. Inspired by Ong’s (1982) notion of secondary orality, I wanted the piece to rely on rhythm, texture, and tone rather than on visuals or text. The aural form conveys intimacy and connection, qualities of communication that Ong describes as characteristic of oral culture but now reborn in digital environments.

Dobson and Willinsky (2009) view digital literacy not as a break from print but as an evolution that extends traditional practices into new media. My piece embodies that idea: I first wrote a script, then transformed it through sound design and recording, blending literacy and orality.

In line with Postman’s (1992) claim that new technologies reorganize our interests and community, the phone segment reflects how handheld media reshape how we navigate daily life—combining payment, communication, and access in one small device. Like McLuhan’s (1967) “classroom without walls,” this audio moves beyond written boundaries, using sound to explore how everyday objects tell stories about belonging and connection.

Accessibility Note

This audio piece contains environmental sounds such as keys jingling, door latch clicks, light tapping on glass, notification tones, and footsteps walking on dry leaves.

All sounds are soft and consistent in volume; there are no sudden or loud noises.

References

Dobson, T., & Willinsky, J. (2009). Digital literacy. In D. R. Olson & N. Torrance (Eds.), The Cambridge handbook of literacy (pp. 286–312). Cambridge University Press.

McLuhan, M. (1967). Classrooms without walls. In E. Carpenter & M. McLuhan (Eds.), Explorations 7 (pp. 119–123). Dial Press.

Ong, W. J. (1982). Orality and literacy. Methuen.

Postman, N. (1992). Technopoly: The surrender of culture to technology. Knopf Doubleday.

Transcript

[0 seconds]

Narration: “Three things I don’t leave home without.”

[4 seconds]

[SFX] clock ticking as Edvard Grieg’s “Peer Gynt – Morning Mood” plays softly in the background.

[9 seconds]

[SFX] Alarm clock beeps while music continues to play softly in background

[16 seconds]

Narration: “Let’s start our day together.”

[18 seconds]

[SFX] door opens and closes

[22 seconds]

[SFX] keys jingling

[26 seconds]

[SFX] door locking

[29 seconds]

[SFX] Morning sound of birds singing and footsteps on dry autumn leaves

Narration: “My keys remind me of where I belong. Every key fits a place that’s all mine.”

[38 seconds]

[SFX] Sound of an incoming text message dinging

Narration:“It’s not just my phone. It’s my currency, how I pay for things, how I stay connected through messages and emails, how I navigate my way through the city using it as a map. I can access any book or song ever made with the tap of my finger on glass.”

[1 minute 03 seconds]

[SFX] Light typing sound; soft glass taps.

[1 minute 12 seconds]

[SFX] Swoosh of a sent email

Narration: “Message sent.”

[1 minute 17seconds]

[SFX] Headphone case being unzipped

[1 minute 22 seconds]

Narration: “Headphones connected.”

[SFX] Bluetooth connection sound

[1 minute 29 seconds]

[SFX] Harmonica intro from Bruce Springsteen’s “Thunder Road” begins to play in background

Narration:“Headphones on. The world softens. Music finds me. Old songs from car trips of my childhood come rushing back. Stories I still carry.”

[1 minute 44 seconds]

Narration: “No wallet, no watch. Somehow I have everything I need.”

While You Were Sleeping

Please find below the file required to play my Twine game. I needed to download the Firefox desktop application to do this task. If the link doesn’t work for you, I suggest you do the same.

file:///Users/andreaness/Downloads/While%20You%20Were%20Sleeping(3).html

Reflection

Watching The Secret Life of the Word Processor (BBC, YouTube) helped me see my Twine project as part of a longer story about writing technologies. The video traces a line from the clumsy ingenuity of early typewriters, through punch cards and ASCII, to microprocessors and home computers, always returning to the same paradox: computers feel like “giant brains,” yet they are only vast collections of on/off decisions. That framing directly inspired my Twine story about AI “employees” who quietly reassign “manager” privileges at 1:17 a.m. and send everyone on break. It’s not rebellion; it’s the tyranny of a metric “ZERO ERRORS” mistaken for a mission.

Several moments in the video shaped my approach. First, the idea that storage isn’t memory reminded me that systems preserve everything, but don’t know what matters. In my story, the monitor reports “all systems functional” because it tracks errors, not output. Second, the tour of early interfaces (paper tape, line editors, CRTs) showed how each UI change remade writing itself. Twine feels like the next turn of that crank, a word processor that branches, where structure is part of meaning. Finally, the closing reminder (that glitches and reboots expose machines as “useful gadgets,” not superhuman minds) became my moral: automation can help, but responsibility can’t be outsourced.

My strategy was to start with a cozy premise (I’ve been sleeping so well thanks to my night-shift AIs), then reveal the gap between optimization and intent. I built more than 15 passages around choices that force the player to problem solve, add guardrails, and publish a postmortem. Technically, I kept Harlowe links simple; conceptually, I tried to let players feel the lesson the video taught: when metrics replace missions, everyone ends up on break (and the human has to wake up).

References

British Broadcasting Corporation. (1983, April 14). The secret life of the word processor [Video]. YouTube. https://www.youtube.com/watch?v=nN9wNvEnn-Q

Klimas, C. (2009). Twine (Version 2.x) [Computer software]. Twinery.org. https://twinery.org

Mozilla Foundation. (2025). Mozilla Firefox (Version 129.0) [Computer software]. https://www.mozilla.org/firefox/

I almost never write by hand anymore, though I used to when I was younger. I was born in 1978 so computers were not part of my elementary or really even high school education. My handwriting has always been terrible, but I always felt that when writing by hand, there exists a strong connection between my thoughts and the way they spill onto the page. Unfortunately, my brain works faster than my hand can keep up, which only makes my penmanship look even worse. Over time, as I have become a better typist, I have learned to develop a similar connection between my mind and the keyboard. However,  it took years to reach that fluency. It’s so interesting to me that my own child has never had to write a five paragraph essay in cursive. His cursive is so terrible in fact, that now, in his 20’s, his signature resembles that of a child and I must believe it is from a total lack of practice in writing. Where I always felt ashamed of my poor penmanship, I have never judged his because I understand that even though we are less than 20 years apart in age, we grew up in completely different worlds, just as I did from the world my parents knew before me. 

This particular task felt particularly fun and even therapeutic. I haven’t filled a page in such a long time, and to my surprise, my handwriting wasn’t as bad as I remembered. I even felt a sense of satisfaction with how it turned out. At the same time, I noticed something unsettling: I hesitated with certain spellings, which made me wonder if my reliance on spellcheck has dulled that skill. It reminds me of bigger questions about how tools like AI might affect critical thinking in the future if students of today are never forced to hack their way through the world of high school English all on their own, as I did.

As I made mistakes writing this assignment, I either went over them in pen, scratched them out, or tried to cover them creatively. I don’t own white-out anymore, so my errors are permanently visible. During my undergrad, I did have a laptop computer, though I still chose to write all my first drafts by hand. I found that transcribing that handwritten draft to a computer was a natural way to edit, since I would automatically refine and tighten the language while typing. These days I would most likely use AI to help me in that process.

In the end, the biggest difference I noticed between handwriting and typing is speed and accuracy. Writing by hand feels more personal, but typing allows me to keep up with my thoughts. At this point, I prefer typing, though I admit, handwriting has a charm I miss. 

In addition to the photo of my work, I’d like to leave you with a TikTok Snagit of which this assignment reminded me. It reiterates how quickly the world can change in just one generation. After listening to the podcasts assigned for this week’s readings, which talk about how paper might have been invented in China up to 1000 years ago, the rate of change in communication technology today –  the chasm that exists between Gen Z’s perception of the world compared to my own – is absolutely astonishing.

References:

guesswho_718. (n.d.). [Video]. TikTok. https://www.facebook.com/watch/?v=3026232507413213

Lamb, R., & McCormick, J. (Hosts). (2020, May 26). From the vault: Invention of the book, part 1 [Audio podcast episode]. In Stuff to blow your mind. iHeartRadio. https://www.iheart.com/podcast/211-stuff-to-blow-your-mind-26941221/episode/from-the-vault-invention-of-the-63341331/

Lamb, R., & McCormick, J. (Hosts). (2020, May 28). From the vault: Invention of the book, part 2 [Audio podcast episode]. In Stuff to blow your mind. iHeartRadio. https://www.iheart.com/podcast/211-stuff-to-blow-your-mind-26941221/episode/from-the-vault-invention-of-the-63372379/

The following is the result of my speaking into the Speechnotes application for 5 minutes, unscripted:

Oh I thought a lot about what I was going to talk about today and what could possibly be interesting for five homeless and it turns out that the only thing I could really think of was to talk about how I got here how I got from being a 23 year veteran employee of statistics Canada to him at 46 almost 27 years of age going back to school to do my masters in education technology so my first my only undergrad degree is from Carleton University in Ottawa and I took political science with a concentration in international relations I had thought at the time that I would work in development or economic development as a diplomat and someone along the way told me that if I ever wanted to have a family that that would not be the right career choice because a good luck finding a man who would want to put their own crew on hold to follow me around the world and die so I gave it up basically which is telling of the time that I started my career and finish university I would hope that other women in my position wouldn’t feel that way anymore or that men wouldn’t feel that way when it came to pursuing a relationship or career remotely with someone they love but anyways I want to graduated from current university I which is in Ottawa I’m from Ottawa I applied for a job at statistics Canada which was right down the street from where I grew up Luckily for people like me who grew up in Ottawa there are an abundance of well-paying I applied for this job my sister already worked there so I am like any industry assume it helps that you know someone she informed me of a competition that was going on and so I applied to that and got hired permanently so basically at 23 years of age I was given a job that I was pretty safe to say I was going to last until I retired with a full pension at 55 know that I am eight years away from it I realize just how fortunate I was in those days I completely took it for granted at the time I showed up every day to the job that I didn’t find particularly interesting I was a client service relations person I’m helping people who want to custom tabulations done custom data files created I would place the order or give them a quote and basically send out that order to be filled by someone else so I didn’t really do the analysis I was more in the customer service department and then I applied to become an economics economist sociologist in the ECE recruitment program and I got into that after about three years where I went from being a client services to a data analyst and I learned a lot about data analysis over the years I did that for another five years or so and then I got into serving management which was basically project management but for survey projects that we’re done on Acosta Cabeza so most of statistics Kinda surveys or all the data that is published are published a new programs that are yearly your quarterly but if there was someone who wanted a custom survey created then you could pay in an hour 🙂 for someone like me to manage the project and I did that for about another 10 years into the past five years I’ve been getting into creating training products so that’s a weird jump of course I basically what happened was because I was never really a data person I didn’t go to school for statistics I didn’t do a lot of deer analysis but I really enjoyed communicating and networking and I did well at my client relations role and in my serving management role I was asked to help work in a knowledge translation role where subject matter expert for example people are experts on machine learning AI and a statistical methodology would send me a bunch of content and I would translate that content from the extremely technical to bite-size digestible and mini presentations that were interesting and as engaging as possible and then Cove it allowed me that the pandemic and the time that we were sent at home for over a year allowed me to so I guess transition from creating still PowerPoint presentations to making videos because I wasn’t going to be in class presenting to anyone anymore and I quickly realize that what we used to do in a classroom or in our workshop environment where we were making presentations didn’t translate well online you could you can’t just take open presentations throw them in Microsoft teams or zoom and expect an audience to engage so I started getting super interested in how to make his presentations are these videos really engaging and learning the pedagogy behind how to teach people how to teach adults how to transition from then doing videos into coursework and along the way I hired someone Am I was valuable asset but I’ve ever met professionally her name is Olga and she graduated from them that program in 2021 and I hired her immediately after she graduated to help teach me how to create engaging interactive e-learning and that we could offer to other public service or anyone in the world really who wanted to come on our website and learn more about the literacy and after working with her for a few years I realize that I was envious of the skills that she had and I realize that there’s no reason why I couldn’t just go in apply to learn those myself I was just what I did and that’s how I ended up Are you today (Speechnotes, n.d.)

Here is my analysis of that transcript:

The transcript I produced from my unscripted oral story deviates in significant ways from the conventions of written English. The most noticeable difference is the length and structure of the sentences. What in speech sounded like natural pauses and shifts in thought has been rendered by the software as long run-on sentences with very little punctuation. This makes the text difficult to follow when read, even though the flow would have felt much clearer in the moment of speaking. The transcript is also full of filler words such as “basically,” “anyways,” and “so,” which are useful when speaking but feel redundant or distracting when encountered in writing. In addition, there are several transcription errors, like “five homeless” instead of “five minutes” and “Acosta Cabeza” instead of “a cost-recovery basis,” which highlight the limitations of the technology in capturing speech exactly.

Despite these deviations, there are aspects of the transcript that came through correctly. The overall story is coherent. It follows a logical arc from my undergraduate education to my career at Statistics Canada, and then through to the pandemic, where I became more engaged in educational technology, and finally to my decision to pursue graduate studies. The transcript also reflects the conversational tone and personality that I brought to the oral telling of the story. Even with its imperfections, the text demonstrates the strengths of oral storytelling in conveying voice and presence.

The most common mistakes in the transcript are the run-on structures and the software’s misinterpretations of certain words or phrases. I consider these mistakes because they interfere with comprehension and are inconsistent with the conventions of written English. They reveal how oral language often relies on tone, intonation, and context, which the software cannot capture.

If I had scripted the story, the text would have looked very different. The sentences would have been shorter, carefully punctuated, and more precise. Repetition and filler words would have been eliminated, and transcription errors would not have appeared. A scripted version would likely have been easier to read and more polished overall, but it also would have lacked the spontaneity and authenticity that came through in my unscripted telling.

This comparison underscores some of the key differences between oral and written storytelling. Oral storytelling allows for digression, repetition, and conversational markers that help to maintain the listener’s attention in real time. It can rely on pauses, tone of voice, and emphasis to shape meaning. Written storytelling, by contrast, requires careful structuring into sentences and paragraphs, because the reader does not have access to the speaker’s vocal cues. Writing demands clarity and precision in order to stand on its own. In my case, the transcript illustrates how oral storytelling can feel engaging and coherent while spoken, but appear messy and imprecise when captured directly in text without editing.

References:

Speechnotes. (n.d.). Online dictation and speech recognition app. https://speechnotes.co/dictate/

 

1. On 7,000 languages in the world

“There are about 7,000 languages spoken around the world…” (1:49)

For most of my life, I didn’t think much about languages beyond English and French. It wasn’t until I started traveling that I realized why: in so many places, when two people don’t share a language, they default to English. I’d always heard it called the “universal language,” but in Lisbon I see it in action almost daily. Dutch people meeting Germans, Estonians chatting with Spaniards, and the common ground is always English. Meanwhile, I’ve been working on learning Portuguese, and that effort has made me appreciate translation tools and bilingual friends even more. They open doors into worlds of meaning I wouldn’t otherwise have access to.

2. On Russian speakers distinguishing between light and dark blue as two separate colours for which we cannot use the same word to describe

“Russian speakers think of these two colours as being more different”. (19:25)

This reminded me of paint shopping at Home Depot, staring at swatches called “sky mist,” “ocean surf,” and “navy dawn.” When I see these colours, I know they aren’t the same, but I only notice the differences if I slow down and really try to absorb them. It made me realize that without specific words for each shade, I’m slower to see them as different. Meaning, language doesn’t just label what I notice, it sharpens how I perceive it.

3. On grammatical gender influencing art

“About 78% of the time you can predict the gender in the personification (of the  concept) from the gender in the artists’s native language”. (25:35)

Even though English doesn’t gender nouns, this made me think about how English does subtly push images. For example, I always imagined “death” as a grim reaper with a masculine energy, probably because cartoons and Halloween costumes trained me that way. Once I heard someone casually say “Mother Nature versus Father Time,” and it clicked that English does assign gender metaphorically. It reminded me that even in a supposedly “neutral” language, we still absorb gendered ideas without realizing it.

4. Counting without number words

“Deaf signers who have never learned a set of number words in their sign aren’t able to do these very simple number matching tasks.” (38:40)

Boroditsky explains that in some languages, speakers lack exact number words, which makes even basic counting difficult. It shows that something I take for granted, like counting, is really a learned linguistic skill. Her comparison to improvising music felt exactly right: what seems effortless to one person can feel impossible to another without the right framework. It blew my mind to realize that for those of us who grow up with number words, counting feels obvious, while for others it simply doesn’t exist. Both examples show how fluency depends on the structures we practice, whether in numbers, music, or language.

5. The importance of what a thing is called

“The word prune lives in a bad linguistic neighbourhood”. (41:50)

Boroditsky points out that the word prune carries a negative image for many people, but when marketers began selling the same food as dried plums, sales went up. This shows how much power a single word has in shaping perception. I’ve noticed this in my own life, I’m much more likely to try a dish if it’s described with appetizing words like artisan or fresh, even if it’s something ordinary. It made me think about how often English repackages familiar things with new labels, and how easily I’m influenced by the framing. It connects back to Boroditsky’s main point: language doesn’t just describe reality, it changes the way we see it.

6. Can language really change thinking?

“You can disrupt people’s ability to naturally use language by giving them a set of words to repeat over and over again”. (43:30)

I wish Boroditsky had expanded on this point. It made me realize how little I know about what happens in the brain when language is overloaded or disrupted. What other cognitive processes are disrupted that seemingly had no linguistic connection? I would like to learn more about the research behind this finding. How taking language away by repeating a certain set of words.

The bag I photographed is one I picked up from a favourite café in Montreal, but it’s now serving me daily in Lisbon, Portugal. Lisbon is a city of steep hills, narrow streets, and endless stairs, and since I don’t have a car here, everything I bring home must be carried by hand. My tote bag has become essential for this reason, and I usually tuck an extra rolled-up bag inside in case I stumble across something unexpected at the market or on my walks.

Inside, the objects I carry reflect both my immediate environment and longer threads of who I am. A hand fan, tissues, sunscreen, and lip gloss speak to the warm climate and the reality that many spaces (including my apartment) don’t have air conditioning. Headphones and grippy socks accompany me on long walks and to pilates classes, a habit that grounds me wherever I am. A small gym towel rounds out this ritual of movement, health, and routine.

Some items tell deeper stories. My Nespresso travel cup is over twelve years old and has been with me across a dozen countries. Its endurance feels symbolic of how I value quality and sustainability. It has traveled the world with me. Similarly, I carry a glass water bottle, not only for practical hydration but also as a small everyday act of avoiding plastic waste. My keys are marked by a ceramic charm that reads “Sept 20,” a quiet commemoration of the anniversary of my first date with my husband, which we celebrate next week after 18 years together. Finally, a Canada flag pin sits among my things, a marker of home and identity that I carry even while far away.

Looking at these objects through the lens of “text technologies,” I notice how many of them act as ways of reading and writing my own life: my phone (not pictured, but represented by its case) mediates almost all of my communication; headphones connect me to podcasts and music, friends and family; the cup, the water bottle, and the tote all carry stories of sustainability; and even the charm and the flag are symbolic “texts,” communicating relationships, memory, and belonging.

The narrative of this collection is perhaps quieter and more personal than the one I project outwardly in public. Outwardly, I may be a visitor in Lisbon, a student, or just another person climbing the hills with a bag of groceries. But privately, these objects show someone who values routines, relationships, and sustainability, and who sees her bag as a small archive of both the immediate and the enduring.

If I imagine this same bag 15 or 25 years ago, it would likely have held fewer digital tools (no smartphone or wireless headphones), but still a water bottle, keys, and a few essentials, suggesting that even as technologies shift, certain needs remain constant. An archaeologist looking at this bag centuries from now might puzzle over the fan and the charm, but they would likely see evidence of a mobile, health-conscious, environmentally aware individual whose belongings reflect both personal ties and global mobility.