As we look to a future that becomes increasingly automated by artificial intelligence, many economists, sociologists, and philosophers believe we may need to supplement the income earned by workers to compensate for reduced employment opportunities. Sometimes referred to as Universal Basic Income (UBI) or Partial Basic Income (PBI), the basic concept has gained momentum in recent years as AI technology begins to compete with skilled human workers.
Personally, I believe it’s still too early to assess if AI systems will significantly reduce job opportunities, or if it will merely shift employment towards new domains. That said, we might consider a small step in this direction by imposing a “Humanity Tax” on certain categories of largescale AI systems that benefit from the collective works of the human race.
I am referring specifically to two AI technologies that have made remarkable strides over the last few years. One is called Large Language Models (LLMs) which enable automated systems to generate compelling essays and hold convincing conversations, even write successful computer code, all with little or no supervision. The second is called Generative Art which enables AI systems to create unique artwork from simple text prompts. Both are rooted in similar generative AI technologies and show similarly impressive results.
For example, the article you are reading has a header image at the top that is helpful for sharing on social media. In the past, I might have asked the publication to buy a stock image or hire an artist. In this case, I chose to use an AI-based generative artwork system. I gave the system some simple text prompts, describing the artwork I had in mind – a robot painting a picture. In just minutes, the system that I used (called Midjourney) produced a variety of computer-generated images, each one an original and compelling creation:
Generative Robot Artists (Rosenberg using Midjourney)
I’ve used generative systems before, but I never cease to be amazed by the output. I found these images of robots with paintbrushes to be artistic, evocative, and aesthetically pleasing. Still, these options did not capture the sentiment I was looking for, so I tried slightly different text prompts. In the end, it took less than ten minutes for me to converge upon the artwork used at the top of this piece. The process was significantly faster than contracting a human artist and remarkably flexible, allowing me to explore many directions in just a few minutes.
Generative Robot Artist (Rosenberg using Midjourney)
Generative Art will impact every field, especially marketing.
You can easily imagine the impact that this technology will have on many fields, especially marketing where compelling and original content is needed for everything from posts and blogs to packaging, branding, messaging and advertising. We are close to the day when a marketing professional could have a generative AI system automatically write an original blog post and then create original artwork to go with it. The image below was created in minutes.
Generative Advertising Art (Rosenberg using Midjourney)
And it’s not just generative text and images that will impact the field of marketing. The same technologies will soon enter the field of video as well. It won’t be long before generative AI is used to create video content for marketeers in a matter of minutes. A marketing professional could ask for a 30 second video clip of a woman jogging in a particular brand of sneakers on a rainy morning in Chicago using the visual style of Steven Spielberg and compelling clips will get produced. Other generative tools could be used to add original AI-created background music as well, maybe jazz generated in the style of Miles Davis mixed with Kamasi Washington.
The convenience and efficiency are extreme. These generative AI systems will be able to produce in minutes what would take human writers and artists and composers hours or days or weeks to produce. And the output can be generated in a variety of styles at the click of a button. It makes you wonder how human content creators are going to compete. Should young marketers take a traditional copyrighting course, or get specific instruction on how to generate the optimal prompts for a generative AI system? Maybe.
Generative Robot Artist (Rosenberg using Midjourney)
Does this mean AI is now more creative than human artists?
No – generative AI systems are not creative at all. In fact, they’re not even intelligent. I entered a text prompt asking for artwork depicting a robot holding a paintbrush, but the software had no understanding of what a “robot” is or a “paintbrush.” It created the artwork using a statistical process that correlates imagery with the words and phrases in the prompt.
The results are impressive because generative AI systems are generally trained on billions of existing documents captured from the internet – images, essays, articles, drawings, paintings, photographs – everything and anything. Sometimes these systems filter out offensive content before training to avoid producing offensive results, but in general the dataset is fairly comprehensive, enabling the software to create artwork in a wide range of styles.
I don’t mean to imply these systems are unimpressive – they’re amazing technologies and profoundly useful. They’re just not “creative” in the way we humans think of creativity. This may seem hard to believe, as the robot images above are clearly creative pieces, instilled with character and emotion.
From that perspective it’s hard to deny that the software produced authentic artwork, and yet the AI did not feel anything while creating it, nor did it draw upon any inherent artistic sensibilities. The same is true of generative systems that produce text. The output may read smoothly, use effective and colorful language, and have genuine emotional impact, but the AI itself has no understanding of the content it wrote or the emotions it was aiming to evoke.
Generative Robot Artist (Rosenberg using Midjourney)
So who instilled the work with creativity and artistic expression?
No human can be credited with crafting the work, although a person kicked off the process by providing the prompts – they are a collaborator of sorts, but not the artist. After all, each piece is generated with a unique style and composition. Who is responsible for crafting that work?
My view is that we all created that artwork – humanity itself.
Yes, the collective we call humanity is the artist. And I don’t just mean people who are alive today, but every person who contributed to the billions of creative artifacts that generative AI systems are trained upon. And it’s not just the countless human artists who had their creative works vacuumed up and digested by these AI systems, but also members of the public who shared the artwork, or described it in social media posts, or even just upvoted it so it became more prominent in the global distributed database we call the internet.
Yes, I’m saying that humanity should be the artist of record.
To support this, I ask that you imagine an identical AI technology on some other planet, developed by some other intelligent species and trained on a database of their creative artifacts. The output might be visually pleasing to them – evocative and impactful. To us, it would probably be incomprehensible. I doubt we would recognize it as artwork.
In other words, without being trained on a database of humanity’s creative artifacts, an identical AI system would not generate anything that we recognize as pleasing or evocative artwork. It certainly would not create the robot pictures in my example above. Hence my assertion that humanity should be considered the artist of record for large-scale generative art.
This brings me to the topic of compensation.
Had an individual artist created the robot pictures above, they would be compensated. Similarly, if a team of artists had created the work, they too would be compensated. Big budget films can be staffed with hundreds of artists across many disciplines, all contributing to a single piece of artwork, all of them compensated. But what about generative artwork created by AI systems trained on millions upon millions of creative human artifacts?
If we accept that the true artist is humanity itself – who should be compensated? Clearly the software companies that provide the generative AI tools and the many servers full of computing power deserve substantial compensation. I have no regrets about paying the subscription fee that was required to generate the artwork examples above. It was reasonable and justified. But there were also vast numbers of humans who participated in that artwork, their contributions inherent in the massive web of content the AI system was trained on.
Humanity should be compensated.
Which is why I believe we should consider a “humanity tax” on large-scale generative systems trained on massive datasets of human artifacts. It could be a modest fee on transactions, maybe paid into a centralized “humanity fund” or paid to decentralized accounts using blockchain. I know this may sound like a strange idea, but if a spaceship showed up with some entrepreneurial aliens and they asked humanity to contribute our collective works to a database so they could generate derivative artifacts for profit, we’d likely ask for compensation.
Here on earth, this is already happening. Without being asked for consent, we humans have contributed a vast record of our collective works to some of the largest corporations this planet has ever seen – corporations that can now use generative AI systems to sell derivative works for a profit. This suggests that a “humanity tax” is not a crazy idea but a reasonable first step to consider in a world that’s likely to adopt a great many generative AI tools and technologies in the coming years.
Louis Rosenberg, PhD is a pioneer in the fields of VR, AR, and AI. His work began over thirty years ago in labs at Stanford and NASA. In 1992 he developed the first augmented reality system at Air Force Research Laboratory. In 1993 he founded the early VR company Immersion Corporation (public on Nasdaq). In 2004 he founded the early AR company Outland Research. He is currently the Founder and CEO of Unanimous AI a company that amplifies group intelligence. He’s been awarded over 300 patents for VR, AR, and AI and published over 100 academic papers. He holds a PhD from Stanford and was a professor at California State University. Louis also serves on the Advisory Board of the Future of Marketing Institute, a think-tank located at York University in Toronto.