/Abstract

Entertainment media has a strange habit of appearing absurd right before becoming accurate. This explores how speculative entertainment has anticipated future technological and educational developments before institutions fully imagined or engineered them. Using the film Accepted and the television franchise Star Trek as central examples, this paper examines how fictional narratives foreshadowed participatory learning environments, conversational artificial intelligence (AI), wearable technology, and human-centered computing. Drawing upon the Fully Online Learning Community (FOLC) model and digital learning theory, this discussion reflects on how entertainment media may function less as escapism and more as an informal research and development department for civilization. Particular attention is given to AI prompting, collaborative learning ecosystems, and the potential for fiction to become reality.

Introduction

There is a moment in nearly every technological era where society collectively realizes that science fiction writers were either:

  1. remarkably insightful,
  2. secretly time travelers,
  3. or somehow sitting on advisory boards they never told us about.

Oscar Wilde famously wrote that “Life imitates Art far more than Art imitates Life” (Wilde, 1889/2006, p. 38), and modern technology increasingly makes that statement feel less philosophical and more mildly concerning.

Popular culture is filled with examples.

The animated television series The Simpsons has spent decades accidentally predicting future events with unsettling consistency. Viewers have frequently pointed to episodes such as:

  • Bart to the Future (Season 11, Episode 17, 2000), which referenced a future Donald Trump presidency,
  • Lisa’s Wedding (Season 6, Episode 19, 1995), which depicted video calling and smartwatch-like wearable communication,
  • Last Exit to Springfield (Season 4, Episode 17, 1993), which portrayed technologically integrated workplace systems and automation,
  • and Treehouse of Horror XIX (Season 20, Episode 4, 2008), which humorously referenced autocorrect-style text failures before predictive text became universally frustrating (Kogen & Kirkland, 1993).

At this point, The Simpsons feels less like satire and more like a federally unrecognized forecasting agency.

Preceding the Simpsons, the comic strip Dick Tracy introduced a two-way wrist radio in 1946, decades before modern smartwatches made everyone look like they were quietly coordinating tactical operations while buying coffee (Gould, 1946).

At some point, speculative fiction stopped feeling speculative and started feeling like delayed product announcements.

Researchers often describe this phenomenon as sociotechnical imaginaries, or the collectively held visions societies create regarding desirable futures shaped through science and technology (Tidwell & Tidwell, 2018). The concept emphasizes how technological systems are not merely engineered artifacts, but cultural expressions of what societies imagine the “good life” to be.

Interestingly, Tidwell and Tidwell (2018) critique how governments, institutions, and experts often dominate these visions through top-down policymaking that may be disconnected from everyday public experience. Their analysis of energy policy research argues that institutional and governmental visions frequently privilege expert narratives while overlooking the “messiness and variation” of local communities and ordinary people. In simpler terms: sometimes the people designing the future are not especially representative of the people who actually have to live in it.

Which, admittedly, explains a surprising amount about modern software updates.

Tidwell and Tidwell further argue that governments and expert institutions often mistake “standardized” or institutional visions for universally shared public desires, even when those visions may conflict with local cultural realities and lived experience. Their critique of nuclear policy imaginaries and national energy planning demonstrates how elite visions of progress can miss the mark when disconnected from broader public imagination and community identity.

This reflective essay explores two particularly fascinating examples of how entertainment, rather than governments and expert institutions get things right:

  • Accepted, which accidentally anticipated participatory digital learning culture,
  • and Star Trek, which effectively invented conversational AI interaction decades before ChatGPT existed.

Viewed through the lens of the Fully Online Learning Community (FOLC) model, both works reveal something important: sometimes entertainment understands the future faster than institutions do.

Accepted: The Fake College That Accidentally Became Educational Theory

When Accepted (Weitz, 2006) was released, it was largely interpreted as a ridiculous comedy about rejected students inventing a fake university called the South Harmon Institute of Technology.

Even the acronym alone should have warned viewers this was not intended to become a legitimate pedagogical framework.

Yet here we are.

The film follows Bartleby Gaines, portrayed by Justin Long, after being rejected from multiple colleges. To avoid disappointing their families, Bartleby and his friends create a fictional institution that unexpectedly evolves into an unconventional learning community.

Students:

  • design their own courses,
  • pursue meaningful interests,
  • collaborate socially,
  • and reject rigid institutional hierarchies.

At the time, this appeared comedic because higher education still strongly operated under industrial-era assumptions:

  • standardized curriculum,
  • instructor-centered authority,
  • and passive information delivery.

Today, however, revisiting Accepted feels oddly like watching an exaggerated prototype of:

  • online learning communities,
  • creator-based education,
  • experiential learning,
  • Discord study groups,
  • and self-directed digital learning ecosystems.

This becomes even more interesting when compared to the Fully Online Learning Community (FOLC) model developed by van Oostveen (2017). FOLC emphasizes:

  • learner agency,
  • collaborative inquiry,
  • social presence,
  • and community-driven learning environments.

In other words:
South Harmon was chaotic, but educationally it may have been accidentally onto something.

Veletsianos (2016) similarly argued that meaningful digital learning environments should foster collaboration, engagement, reflection, and authentic participation rather than passive instructional consumption.

Ironically, what made Accepted funny in 2006 is partially what makes it educationally recognizable today.

Apparently the joke was:

“What if students actually enjoyed learning?”

Higher education has spent the last decade cautiously realizing that maybe this was not entirely unreasonable.

Star Trek: The Franchise That Basically Invented the Future by Accident

If Accepted anticipated participatory learning culture, Star Trek spent decades quietly designing modern technology before Silicon Valley got around to manufacturing it.

Consider the list:

  • tablets,
  • touchscreens,
  • wearable communicators,
  • universal translators,
  • voice assistants,
  • AI interfaces,
  • immersive simulations,
  • and advanced medical imaging systems.

At this point, Star Trek feels less like entertainment and more like an extremely patient prototype catalog.

The Personal Access Display Device (PADD) strongly resembles modern tablets such as the iPad. Ars Technica documented how Star Trek designers conceptualized touchscreen computing systems decades before those devices became commercially viable (Foresman, 2016).

The franchise also imagined medical diagnostic technologies resembling emerging MRI and CT immersive visualization systems now being explored in healthcare environments (University of Hawai‘i, n.d.).

And then there is conversational computing.

Long before modern AI assistants existed, Star Trek characters casually interacted with computers using natural language:

“Computer, analyze this signal.”
“Computer, run a simulation.”
“Computer, locate Commander Data.”

No command line.
No coding syntax.
No Stack Overflow tabs open in panic.

Just conversation.

Watching these scenes today feels suspiciously similar to modern AI prompting.

A particularly fascinating example appears in Star Trek: The Next Generation Season 4, Episode 19, “The Nth Degree” (Bole, 1991). In the episode, the character Reginald Barclay begins interacting with the Enterprise computer using increasingly sophisticated conversational instructions.

Barclay:

  • creates holodeck simulations of sophisticated machinery,
  • dynamically generates interfaces between those virtual machines,
  • vigorously collaborates with a holographic simulation of Albert Einstein, interactively solving complex theoretical problems through dialogue.

This is essentially prompt engineering wearing a costume on a sound stage.

The interaction patterns strongly resemble modern generative AI workflows:

  • contextual prompting,
  • iterative refinement,
  • conversational problem-solving,
  • and collaborative computational assistance.

The truly remarkable part is not merely that Star Trek imagined advanced technology. It imagined how humans would emotionally and cognitively relate to that technology. And that may have been the more difficult prediction.

Prompt Engineering: Or, Teaching Computers Through Vibes and Context

One of the strangest developments in modern computing is that after decades of increasingly complex programming languages, society has circled back to:

“Just explain what you want clearly.”

Modern AI prompting increasingly depends upon:

  • context,
  • tone,
  • iteration,
  • semantic framing,
  • and conversational intent.

In other words, effective AI interaction increasingly resembles:

  • management,
  • teaching,
  • negotiation,
  • or therapy.

Sometimes all four simultaneously.

Bozkurt et al. (2023) argued that generative AI systems are reshaping collaboration, authorship, and knowledge production within education.

What becomes fascinating is that entertainment media may have psychologically prepared society for this interaction model long before the technology matured.

People were already culturally trained by science fiction to believe:

  • computers could converse,
  • machines could collaborate,
  • and technology could behave socially.

Which means speculative fiction may not simply predict the future. It may effortlessly teach society how to behave once the future arrives.

Reflections on Learning, AI, and Professional Training

These ideas become particularly interesting when applied to professional learning environments.

Fields such as:

  • emergency services,
  • healthcare,
  • aviation,
  • and military training

increasingly rely upon:

  • immersive simulations,
  • collaborative digital learning,
  • adaptive training systems,
  • and AI-supported decision-making.

Within fire service education specifically, future systems may include:

  • conversational scenario generation,
  • AI-assisted after-action review,
  • adaptive simulations,
  • and collaborative synchronous learning communities.

This aligns strongly with FOLC principles emphasizing socially embedded and participatory learning environments (van Oostveen, 2017).

The modern learner increasingly resembles less of a passive student and more of:

  • a systems navigator,
  • collaborator,
  • reflective practitioner,
  • and increasingly,
  • someone who knows how to phrase prompts effectively enough to avoid accidentally generating nonsense.

Which, admittedly, may become one of the defining literacy skills of the AI era.

Conclusion

Entertainment media often behaves like civilization’s unofficial prototype laboratory.

Accepted unintentionally anticipated growing dissatisfaction with passive educational systems and reflected emerging desires for collaborative, learner-centered learning environments.

Meanwhile, Star Trek not only imagined advanced technologies but also normalized conversational relationships with intelligent systems long before generative AI became operational reality.

Together, these works illustrate how speculative entertainment shapes sociotechnical imagination by helping society conceptualize future systems of learning, communication, and human-machine interaction.

Perhaps Wilde (1889/2006) was correct all along:
life imitates art.

Although at this point, one could surmise that art occasionally looks at humanity and says:

“Please stop turning my satire into infrastructure.”

Or perhaps, as the creators of fictional tablets and conversational computers might reasonably argue:

“We’re still waiting for our finder’s fee, Mr. Jobs.”

/Disclosure: This paper was constructed with the help of LLM AI for structure, syntax and organization, however all ideas, concepts and observations are my own.

References

Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., & Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53–130.

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Foresman, C. (2016, September 10). How Star Trek artists imagined the iPad… nearly 30 years ago. Ars Technica. https://arstechnica.com/gadgets/2016/09/how-star-trek-artists-imagined-the-ipad-23-years-ago/

Gould, C. (1946, January 13). Dick Tracy [Comic strip]. The Chicago Tribune.

Kogen, J. (Writer), & Kirkland, M. (Director). (1993, March 11). Last exit to Springfield (Season 4, Episode 17) [TV series episode]. In M. Groening (Executive Producer), The Simpsons. Gracie Films; 20th Century Fox.

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University of Hawai‘i. (n.d.). Star Trek technology becomes a medical reality at UH. University of Hawai‘i Office of the Vice President for Research and Innovation. https://research.hawaii.edu/noelo/star-trek-technology-becomes-a-medical-reality-at-uh/

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Veletsianos, G. (2016). Digital learning environments. In N. Rushby & D. W. Surry (Eds.), The Wiley handbook of learning technology (pp. 242–260). Wiley.

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