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Higher Ed or No Ed?

Higher Ed...

...or No Ed?

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Higher Ed...or No Ed?

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There’s been a flurry of articles since chatGPT was first released that try to make sense of the burgeoning problem of plagiarism at colleges (and even high schools). But this is entirely the wrong issue…

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2023-04-15

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High Ed - What Hath ChatGPT Wrought?

Academic Honesty - Still a Thing?

There’s been a flurry of discussion ever since the release of chatGPT that attempts to address the burgeoning problem of plagiarism at universities and even high schools. The purported problem is that students are not merely using googled content verbatim to complete assignments, but are now using chatGPT to wholesale outsource their homework to AI tools.

With the release of GPT-4, the quality of AI-generated essays now rivals and often surpasses the abilities of the average college student – at least the ones who attended the classes I took during the pandemic. So now educators are grappling with a world where academic honesty has been turned upside down and are struggling to find ways to determine whether students have, in fact, written their own essays, thereby demonstrating they’ve mastered the time-honored process of reading a chapter from a mind-numbing textbook, posting a brief summary of same on an online discussion board, and then feigning interest in other students equally banal summaries of the same material.

Aside from the fact that such a methodology hardly passes for authentic intellectual discourse, the prospect that students might be tapping into AI to further reduce actual acquired knowledge and/or critical  thinking skills to near zero threatens the very foundation on which the higher-ed system was created.

Educators are scrambling to find alternative methods to verify that students are actually engaged in the learning process. Because if students can efficiently cheat the system, what is the value proposition of a college degree?

But this is entirely the wrong question. Now that AI is rapidly being integrated into every productivity tool, from Gmail to MS Office to ERP applications, it’s increasingly unlikely that the vendable office worker of the future, if there even is one, will need to perform what is becoming an obsolete task – writing their own content, be it a market analysis or a reply to an email.

Rather, the first question educators should be asking themselves – is knowledge obsolete? If everything a student/worker would ever need to know can be acquired, analyzed, and summarized at the touch of a button, is acquiring knowledge, as currently taught at most colleges and universities, still an essential goal?

And, if AI subordinates the role of most humans in the knowledge management process, then the second, and perhaps more important, question should be – what is the end-game relationship between humans and AI and how do students develop the skills to manage that relationship?

These are not futuristic questions. They are here and now questions. And they need to be answered muy pronto before an entire generation of students graduates with degrees that have become obsolete before they even receive their diplomas…

New Role for Higher Ed

During the pandemic of 2020-21, I availed myself of the many online courses offered by my local community college – in retrospect, the only courses that could not be wholesale replaced by AI were technical instruction in design, web and application development. And even the skills in those courses are rapidly aging:

  • I now routinely invoke chatGPT as my primary learning tool for nearly every possible topic.
  • Many visual design functions have already been appropriated by cloud-based AI services, such as Midjourney and DALLE-2.
  • And the chatGPT API for programming editors like MS Visual Code now makes learning coding skills an entirely interactive process, whereby chatGPT has become an infinitely patient private tutor capable of not only explaining software concepts, but providing annotated examples, correcting my mistakes, and amiably encouraging my efforts to improve my skills.

If there is still a role for higher-ed in the future, it would be one of two tracks:

The first track would be practical skills related to work that humans will still need to do once the first generation(s) of AI (and robotics) have assumed their place in the work force. Professional skills would include further development of AI and robotics, as well as skills that will progressively be subsumed by the ever-expanding scope of AI.

Professors soon will not be needed to actually “teach” anything – the classroom of the future will be much like having a private tutor, whereby synthetic media customizes course content to match both the needs of society and the goals and abilities of each student. The synthetic “instructor” will deliver courses to each student in the form of lectures and rich media, including AR and animation, and will patiently interact with each student “one-on-one” to explain concepts the student doesn’t fully understand, and will prepare, administer, and review highly customized testing continuously calibrated to the student’s progress.

The second, and perhaps more urgent, track will be to teach students to fully integrate into an AI-driven world, much like a traveler to a foreign country needs to do. 

The skills needed to interact with AI are changing on a near-daily basis – nevertheless, several abilities are already apparent:

  • Problem and scope definition – in a world of infinite knowledge, scoping is a real issue.
  • Iterative problem solving – even the current generation of LLM’s highlights the phenomenon that “we don’t know what we don’t know”.
  • Collaboration and “cultural” integration – although AI tools have many human-like traits, using them effectively is not quite like working with human beings.

Working in an AI-dominated world will create demand for an entirely new set of skills than the typical college student is taught at most universities. The metrics by which we currently deem someone “educated” have already become obsolete. It is incumbent on the collective education system to reinvent itself – otherwise, it may become a relatively early casualty of the AI revolution and be replaced by highly efficient, scalable and distributable courses generated by integrated systems of AI tools and data sets.

NOTES

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China GDP vs UST Holdings (2010-22) (billions)

(click/tap legend to filter data)
China GDP vs UST Holdings (2010-22) (billions)

Data Source – World Bank

Global FX Exchange Reserves (2001-22) (% of total)

(click/tap legend to filter data)
Global FX Exchange Reserves (2001-22) (% of total)

Data Source – World Bank

Global FX Exchange Reserves (2001-22) (% of total)

(click/tap legend to filter data)
Global FX Exchange Reserves (2001-22) (% of total)

Data Source – World Bank

Western media is starting to pay attention to China’s efforts to influence members of the so-called Global South, or more specifically the BRICS+ and Shanghai Cooperation Organization (with substantially overlapping membership), to denominate international trade in the Chinese Renminbi (RMB), aks the Chinese Yuan (CNY) and/or other local currencies. For very different reasons, Russia has promoted the idea of an entirely new currency for trade settlement. This is an accelerating trend among countries that have formed close economic and political relationships with China.

Coincident with the pivot to the RMB for trade settlement is a growing sentiment among the BRICS+ and SCO members that holding USD as their primary reserve currency poses a risk in the event the US declares sanctions and/or freezes a country’s assets, as happened with Russia and Belarus in 2022.  

The combined effect of these two trends should be observable in a country’s US Treasuries holdings, and that’s exactly what we’re seeing in the chart above – China’s USD and Treasuries holdings peaked at $1.277 trillion in 2013 and declined by more than 32% in 2022.

Things change “slowly at first, then all at once”...

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Chart - Sub Heading - H3

(click/tap legend to filter data)
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