Machines Making

"ThE eNd iS nEaR" headline has been trending in the tech sector for the past few weeks as a joke (not a joke) reaction to the latest release of OpenAI's GPT-3 platform.  Artificial Intelligence that is creative, and quite good at it.  

It's too early to tell where all of this falls on the hype<—>reality spectrum (think bitcoin), but initial reactions are indicative of something significant.


How do we respond when algorithms become creative?   And what if they are really good?

GPT stands for Generative Pretrained Transformer, a text and language neural network.  GPT-3 is the latest version, released in mid July 2020.  In essence, feed it a few sentences describing what you want and it will make it.  The startup community is currently lit-up with the power and capacity that GPT-3 is demonstrating, still in its infancy.  Twitter is filled with makers telling GPT-3 to make things, with some stunning results.  

As the beta-testers are largely software developers, they are largely telling the AI to do their work for them - creating databases, designing apps, telling jokes, and generating code.  It turns out GPT-3 can seemingly create digital anything using any programming language - just tell it what you want and what platform to use. An absolute no-code digital-maker tool.  

This is geeky-nerdy stuff, for sure.  I feel compelled to share with the DPL Maker cohort nonetheless, as the implications are far reaching.  

  For teachers and students, imagine saying...

Make an academic research paper focused on Maker Education using APA style, approximately 50 pages.  Use sources less than 5 years old.
Read my blog and learn my voice.  Make a blog post every few weeks on a randomized schedule, centered on my core themes and patterns.  Post as draft and notify me when ready.
Make an online course using these materials (users/bhinson/desktop/classes/INTE5340) and using the OSCQR design standard.  Put it in Canvas.

These concepts bring up a number of issues, but I'd like to look a bit in the context of Critical Making which examines the relationship between man and technology. Ethical technology.  Technology dependence. Commercialized creativity.   And now -  co-creating with algorithms.  

Also, Critical Making  prioritizes the creative process over the final product; with a high value for human beings experiencing a creative flow-state.  This meditative focus is of greater value than the final thing you make.

The journey is more important than the destination.

Creative AI negates the journey.  The thing is on-demand, and requires minimal human effort or craft.  Instant gratification.  Furthermore, I wonder, does creative AI negate the maker?   This an extreme example, but certainly a part of the AI canon and near-reality.  

The middle-ground, some will argue, is that AI is the maker tool, and we remain distinctly in the creative driver's seat.  

Which leads me to the MIT Collective Wisdom study from a couple of years ago. Part-6 of that study centered on MEDIA CO-CREATION WITH NON-HUMAN SYSTEMS and explores many of the issues across the human<-->AI spectrum.    

~ Read next post in critical making ~

Day 04: Critical Making

Posted by Brad Hinson

2 min read