The power of generative AI systems is that they can take a simple, well-crafted prompt and turn it into some pretty impressive text, image, video, and audio outputs. Well, it might be more fair to say that these generative AI systems are really collaging data from multiple sources together into a form that most probably matches what you are looking for in your prompt. To say that the quality is impressive, is a relative term.
In fact, over time, as more people make use of generative AI systems, the more these outputs will start to look increasingly less impressive and more like all the rest of the general content. While generative AI can help you take your basic skills and turn your outputs into something much better than what you could do on your own, so too will generative AI systems provide those higher quality outputs for others as well.
The Great Averaging
Since generative AI systems are really just composing bits and pieces of the yottabytes of training data on which they’ve been trained, the collective digital outputs of human intelligence, they aren’t really producing outputs as much as they are reproducing human outputs in different ways. This means that these systems are basically taking the average of all these outputs and producing a somewhat unique output just for you. So, if your own personal capabilities are below the average of what these systems can produce, these systems will bring you up to, at least, the average level of their training data.
As people and organizations start to make more use of these generative outputs, the expectation will be that there’s no reason to use people’s own creative outputs that are any worse than that average. After all, why accept something worse than what can be generated by a machine?
This “Great Averaging” means that anyone and everyone has the power to be average, at least at the level of these generative AI systems. In this manner, AI systems are in effect raising the bar for what people will expect as a minimum level of quality, such that people will be expected to produce outputs that are at least as good as the AI-generated average outputs. In many ways, these AI systems are producing outputs that are better than today’s average level of human performance since the AI systems benefit from the collection of a massive amount of human output, something that individuals just aren’t capable of.
One of the side effects of setting a new bar for the expected average level of output is that those who don’t leverage AI tools to produce the sorts of output they are competing with, and who perform at a level below that average will find their skills and talents increasingly marginalized. While today, the use of AI is still a relative minority within organizations, in the future, generative AI tools will be so widely used and ubiquitous, like how word processors and spreadsheets are today, that those who don’t use the systems will be in the minority. Indeed, organizations will come to expect that generative AI systems will be involved, if not the starting or even ending point, of many core processes.
What does the Great Average Future Mean for You?
With this Great Average in mind, those who aren’t using generative AI effectively will be at a significant disadvantage to the average of what these AI systems can produce. However, simply using generative AI itself won’t be an advantage since it’s just a great averager. Without some sort of real impediment to generative AI’s use, people need to look to the future to understand that while AI is an enabler for a wide range of business, creative, and personal outputs in ways that can extend your capabilities in new ways, it will provide that same benefit for everyone. Ironically, making today’s amazing AI outputs seem just common tomorrow. Don’t get left behind in tomorrow’s world where the Great Average will be the expected minimum level of acceptable output.
