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AI and Human Creativity - Could it Lead to General Cognitive Decline?

How can we ensure AI doesn't make us mentally lazy? A Systems View and invitation to share ideas.

ai-and-human-creativity---could-it-lead-to-general-cognitive-decline

#artificialintelligence, #creativity, #imagination, #innovation, #insight, #inspiration, #mentaltraining, #motivation, #paradigms, #paradigmshifts, #systemsthinking

Could using AI as a substitute for human creativity lead to a decline in our collective creative thinking ability?

I am hoping to find new perspectives that challenge that assumption, but the answers coming from AI itself aren't particularly encouraging.

Of course, it is all about how we use AI. Read along and let's explore the topic.

Consider this an interactive thought experiment to explore possible futures.

How much of a danger to human creativity does AI see itself as? I asked ChatGPT what it thought.

One way to challenge the assumption that AI getting better will lead to diminished human creativity is to demonstrate how AI can actually enhance and augment human creativity, rather than replace it. This can be done by providing examples of how AI is currently being used in creative fields such as music, art, and design, and showing how it is being used to generate new and unique ideas, rather than simply replicating existing ones.

Additionally, highlighting the importance of the human element in the creative process, such as the ability to interpret, understand, and reflect on one's own emotions and experiences, can also help to challenge this assumption.

Another way is to point out that AI is a tool, and like any tool, its impact on society and the economy is determined by how it is used, rather than its intrinsic properties.

-ChatGPT

Hmmm, I am not so convinced.

AI might be able to generate new and novel ideas by remixing what is fed into it, but that doesn't necessarily help the humans who create the input improve their access to their own creative powers.

It's not just about the quality of what is generated, it is also about improving our thinking skills. Creativity might be innate but we can always get better at inviting its presence.

In my experience, that's a mental skill that improves with practice.

And highlighting the importance of the human element in creativity is all well and good but creators in a hurry could be ever more inclined to just press a button to get the output to meet a deadline instead of going inside, reflecting, and finding that creative state necessary to doing it on their own.

Painter on assembly line as metaphor for AI artAnd, of course, yes, AI is a tool and it is about how you use it. I think it is also about how you frame its purpose and how that relates to our values as a society. Consider the relative importance of the intrinsic value of creativity versus a context that gives more weight to the speed of delivery and amount of output.

These are things worth considering deeply, are they not? Since we are early in the AI game, as the twig is bent, so the tree grows. Let's bend it in service of valuing the creative state itself and the window into the soul (or, if you prefer, unconscious mind) of the creator and its connection to the beyond (or, if you prefer, collective unconscious) that true art provides.

Given all that, let's search for insight by applying Systems Thinking with some causal looping.

Wait..."What is causal looping?" You ask.

Well, let's ask ChatGPT.

Causal looping refers to a phenomenon in which the causal relationship between variables forms a loop, such that a change in one variable leads to a change in another variable, which then in turn leads to a change in the first variable, and so on.

This creates a feedback loop where the variables are mutually dependent on each other, and the relationship between them is not simply linear. Causal loop diagrams are used to represent these complex relationships, which can help to identify the key variables and feedback mechanisms involved in a system, and to understand how changes in one part of the system can propagate through the entire system.

Causal loop diagrams are commonly used in systems thinking, and in fields such as systems dynamics, operations research, and management science.

-ChatGPT
So causal looping helps us get our minds around how to best impact a complex system. With such systems, linear thinking won't do, because they have minds of their own and behave seemingly unpredictably.

Systems Thinking helps lasso in some of the wildness of complex systems so we become "less wrong" in predicting their behavior and more insightful in finding ways to impact them. We look for leverage points - ways to get significant results without a lot of effort or expense. That's the reward of Systems Thinking and, to me, makes it well worth learning our way around tools like causal loops.

Basics of Causal Loop Diagrams

  • Each circle represents a variable that changes over time.
  • A circle connected with a plus ("+") sign to the prior circle increases as the prior circle's value increases.
  • Conversely, a circle connected with a minus ("-") sign decreases as the prior connecting value increases.
  • A causal loop with an odd number of minus signs is a "balancing" loop that will seek a state of equilibrium.
  • If the minus signs total to an even number, it is a "reinforcing" loop that will snowball to forever grow or decline...
  • ... except that every reinforcing loop will eventually connect to a balancing loop to limit its expansion or decline.
  • Playing with causal loops can give you a deeper understanding of the dynamics of situation that won't come from rational or reductionist analysis.

Coming up is my first stab at a causal loop on AI's influence on human creativity.

And, considering that need to enhance and augment human thinking, I am using a wonderful, free online causal looping tool called Loopy. It rocks and I recommend it - and Systems Thinking in general, for that matter - for finding those counter-intuitive "leverage points" that can bring breakthroughs.

Such models are built on assumptions. This one assumes that:
  • it is the creative output of humans that trains AI.
  • As AI gets better, it will meet the need for output more easily and reduce the incentive to "think for ourselves", so to speak.
  • As a result, our creativity will collectively atrophy.
So, as AI becomes a better regurgitation machine, the "truly new" could decline, if these assumptions play out and if there aren't corrective measures taken. Well, at least according to this admittedly very incomplete (but hopefully helpful) model.

Loopy is very easy and intuitive to use. I encourage you to click on the model to run it or even dive in by clicking "remix" and evolve the model



Of course, this isn't the end of the story.

How can we apply human creativity to ensure AI doesn't lead to human creativity declining?

Will sharp minds be revered like super-fit bodies so we develop tech-assisted mind gyms to elevate our mental fitness with the additional leisure time AI affords?

This is an evolving piece - a bit of a first draft while I wait on my wife in our SUV, so there's more to come.

Have an idea to improve the model? Ping me on Twitter and, if it makes sense. I'll post it here.




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