We are at a crossroads between shared and hoarded knowledge and information. At a time when data is collected at every turn in the physical and digital realm, we are increasingly letting go of or losing control of the information our presence generates.

The traces we leave behind are harvested by agencies and bodies, often commercial actors that act in the interest of benefactors and investors rather than a sense of “common good”. This data allows for the development of a range of tools and technologies. Some liberate us, allowing us to create in new ways, while others monitor and control.

Boundaries and biases of AI technology

In many cases, these technologies mirror our own biases, marked by the limited range of the data sets they are built upon, further perpetrating values and systems of the past. Gary Marcus, an emeritus professor of psychology and neural science at N.Y.U., is one of the leading figures voicing concern about these technologies. In a recent interview with The New York Times on the launch of OpenAI’s chatbot ChatGPT, he pointed out that the real problem of the technology is that it is built on human-generated text without having a real grasp of context. Marcus argues that the results can be ridden with misinformation, especially if used uncritically. Equally, it can perform genuinely helpful tasks for educators, administrative workers and even commercial copywriters with astonishing precision.

While OpenAI’s technology is free and available to all, it is not open-source. Additionally, companies seeking profit develop an overwhelming majority of AI technologies. That profit is built on intellectual property ensured by patents. The development of the tools, as well as their outcomes are sealed off from the public. A worry is that they may lack the broader perspective that peer review and collaboration offer. These are potentially limited by the production and testing environment.

Repurposing tech

At the other end of the scale lies that which is less controllable and predictable, something much more open-ended. We can see parts of it in the community sharing that has occurred since the very birth of the digital age—sharing findings, hardware, code and whole software in the hope of reaching a deeper understanding of a problem and its possible solutions. In the pre-internet era that often meant exchange between research communities and whole countries. The case today is that people across the world, fields and levels of experience can access software.

That, in turn, means that software and code can be used in novel ways that developers did not anticipate. Innovation is unpredictable, as when communities facing particular challenges find a tool to repurpose so that it answers their needs—hardware or software. Weather technology often finds its way into new fields—from traffic optimisation to surveillance. Mikkel Vestergaard Frandsen and his company Sceye, for example, build their stratospheric platforms on satellite hardware to prevent human trafficking and monitor climate change. Lending cues and tools from other fields can revolutionise and open up new understandings of current problems, as when biologists and city planners paired up to allow slime mould to find the most efficient routes for a network of new tunnels in Tokyo.

More recently, nonprofit research platforms such as OpenAI have launched collaborative tools such as the visual generator DALL-E 2 and ChatGPT, which use deep learning to solve natural language tasks. In the weeks following their release, the internet was flooded with novelty imagery and expression, each more absurd or ingenious than the other. DALL-E and ChatGPT opened the floodgates for an overwhelming creative flow among professionals and amateurs, facilitating the creation of genuinely new types of expression in collaboration with AI without discrimination. Anyone with access to a computer could create something, whatever their reason for creating—fun, experimentation, collaboration or business.

The IP conundrum

Vast tools prompt equally vast questions, one of the most common being: who owns work generated based on others’ creative expression? How do we prevent intellectual property theft and avoid appropriation of others' work—and are those the right questions? Are we headed towards a paradigm shift in our idea of artistic expression and property?

IP-related dilemmas continue to haunt new platforms, largely because they repurpose existing material to generate artwork, text or similar based on prompts from the user. While some revel in forging art “in the style of” Monet, what happens when artworks of contemporary artists are increasingly fed through the algorithm? Can AI generate imagery as profound as that of a painter working at a canvas for days, weeks, months? Who gets a say in that question? What if you consider it a co-creator instead of something you use?

While Non-fungible tokens (NFTs) and their early promise has occasionally been overshadowed by plagiarism, the system undoubtedly offers an opportunity for artists to monetise their art outside the establishment. Concurrently, debates are raging about whether the idea of authorship and ownership of creative expression will be relevant at all in the future. Many argue that ideas of ownership are compatible with capitalist structures that have proven not to serve us well.

Shifting perspectives

What is the role of the artist when anyone can use any piece of art as a tool for further digital development and reproduction? Will art start losing its value, both economic and intellectual? Or will it transcend into something more universal?

What motivates the creation of art will look different. But this assumes that there will be a future where we create—the uncertain nature of our being, especially now, will certainly play into how and why we create.

Worth considering is the possibility of broad societal application and the effect of this on the user. If we create meaningful impact across society and take it outside of the tech bubble, i.e. those in the know, we could make more people aware of and fluent in the tools. That could mean kindergartens, on the street, in elderly homes. Some consider this the key to opening up power structures within tech and AI. If more people understand the tools and their impact, they are better equipped to take a critical standpoint.

Expanding on this idea, could these tools allow a future where it will be possible to see situations from other people’s perspectives—experiencing what it is like to be old, a different gender or ethnicity? Could it help us gain a more compassionate view of the world? To break ancient chains?

Opening the toolbox

Many argue that AI tools have the potential to be truly democratic, shifting the gaze from that of the bourgeoisie to that of the ordinary person, equally capable of creation. OpenAI, for example, seeks to make truly powerful tools available to all with access to a computer, a mission surely motivated by the highly patented sphere of commercial hardware and software development. Innovation often bubbles up when patents expire and tools are either made publicly available or sold at a significantly lower price than previously.

Wang & Söderström is a Copenhagen-based art and design practice that imagines how possible futures—near and far—could look. As the patent licence for an architectural software they were unable to afford expired, the company dropped the price, thereby unleashing a boundaryless exploration. Today the design duo stretch the software far beyond what it was created for, creating work that expands our idea of what is possible, wiping boundaries between the physical and virtual world by exploring the role of haptics in an increasingly digital world. They often speak of the immense value and potential of open-source and affordable tools beyond their original fields and demographics.

So, what could the potential of a wider democratisation of tools be? A world with far shorter pathways from developers to consumers or collaborators could, ultimately, have the potential for moving both artistic expression and society forward. While many of us increasingly hope that technology will save us from a range of human-created challenges and crises on a global scale, it is equally valuable to consider what tech can do for society on a local scale. Many argue for increasingly using tools as they make sense locally in the context of culture, climate and socioeconomic conditions. What if shorter patent licences or more nonprofit development led to the adaptation of tools to assist specific communities in their daily lives? Whether that means climate change adaptation, manufacturing locally or providing adapted education to secluded communities.

Hive mind

Would it lead to more collaboration or more autonomous communities? Could sharing information, knowledge and tools help us reach an unprecedented age of faster creation cycles and problem-solving by connecting the right people with the right tech? The collaborative race to find a Covid-19 vaccine and the sharing of findings goes to show what astonishing results open sharing of information and tools can produce. There is, in other words, a genuine potential for moving society forward.

Another question to ask oneself is what the motivation is to do so. Rather than economic growth, could this collective effort contribute to communal growth and help us reach a more equitable relationship with not only each other but also the planet?

Could this sharing of tools and information lead to a collective hive mind? And could that allow easier matching of tools, data and expertise that becomes a tool for greater good? Or might it use data as a tool of suppression or domination, as is increasingly happening around the world today?

This narrative is based on a scenario collectively conceived and developed by core group participants in a Collaborative Foresight cycle. The group's voice was captured and creatively expanded by the writer.