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 Teachers have become obsolete and have been replaced by moderators in epic-sized Massive Open Online Courses (MOOCs).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.

Ljubljana starts her day by booting up her custom-built gaming console before setting off to school. It shares a direct link to her personal device that she carries around with her through the day. The set-up has been optimized to monitor and communicate the non-fungible token (NFT) market and directly relay this information to her personal device. As well, it shredded in League of legends. Ljubljana has had her sights fixed on a set of rare emoji NTF’s of the Jetsons, commemorating the ninetieth anniversary of the show’s release. On top of being a big Jetsons fan, using the emojis to comment on her friend’s e-game streams would really set her apart and improve her online drip.

On her way to the first class of the day, computer science, she bumps into her friend Alam. Their walk takes them through the narrow yet quaint village road that leads to their school. Along the way, they converse about the pending career choice the learning analytics tool will make for them and the nifty blockchain code language developed to certify NFT’s. Ljubljana and Almas’s future career paths will be based on their academic performance, time spent online, engagement with others, and data pertaining to students’ enneagram personality traits collected by their MOOCs analytics tool.

Due to the crippling cloak of binary language, Ljubljana has been deemed a struggling student by the machine-learned data analytic tools employed to predict each student’s future career path with great accuracy. She spends more time than her peers on the MOOC and engages poorly with others. This could be because she leaves the MOOC open while taking breaks to play video games with her peers. It is a shame this information is not made available to students as they would be able to skew the results of the analytic tool.

Regardless of the outcome, Ljubljana knows she can make a living selling NFT’s of all sorts to support herself and her family for the foreseeable future. Ljubljana and Alms share a laugh as they approach the rod iron gates of their decaying school while checking on the availability of those Jetson’s NFT’s.

Epilogue

Just as humankind used its creativity to carve out the oldest figurative art, the Lion-Man (Dalton, 2003). The collecting and trading of artifacts still persist today over digital NFTs, branching humanity’s innate desire to communicate with others and share imagery in a place where oral traditions and stories may lag. The authenticity of the Lion-Man and CryptoPunk #7523 (OpenSea, 2021) may be contested without a paleontology or computer science degree. In the case of CryptoPunk #7523, the lengthy blockchain-based code (Hedera, 2021) developed by humans for computers to understand is a new way to verify the authenticity of never seen. Similarly, the code that artificial intelligence (AI) systems use when taught through machine learning offers interesting possibilities where AI within LMS may develop its own language and need to translate its code to communicate with humanity’s obsolete language that is pictographic in origin.

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