Thirty years ago, the public launch of the internet fundamentally changed human-computer interaction, making information more accessible. Sixteen years ago, the mobile phone changed our senses, making information more engaging through screen-based touch interactions.

Several other waves have erupted since, with high-speed Internet giving us the benefits of the Internet of Things and cloud-based services like Dropbox, Amazon, and Gmail offering us new personalized ecosystems. It was an evolving coordinated connection of networks beginning to compete for one of the most important aspects of our lives: our attention.

The New Active Participation

Up until now (2022ish), from a human interaction perspective, society has participated in a passive interaction model with information. Most humans have been largely manual contributors to tech, consumers of products and services, manual writers, players of games, and sharers of content on social media—all to feel satisfied by the underlying parameters supported by the digital world, a rules-based contextual relevance network terrained by commercial enterprise and human coders.

However, since 2022 until today, we now see the rise of generative AI (GenAI), a subset of machine learning that’s set a new trajectory for us to live within a new “active” interaction model society. We’re active because we’re now augmented participants and creators of experiences instead of just passive viewers and consumers. Over the past year, generative AI has taken the stage and disrupted single-point activities in our day: helping us to create blogs (Scalenut), create art (MidJourney), write papers (Grammarly), and even have relationships with avatars (Replika). These are just a handful of the hundreds of AI applications out now. Even with the behavior of some users embracing this like magic vs. others calling out its hallucinations, it is undeniable that human emotion is renewed once again in tech, this time supercharged by the AI algorithm.

In its current form, GenAI’s intrinsic value is speed, variation, and high-resolution output, which makes it easy for us to conjure new ideas or discover unseen possibilities quickly. However, when asking futurists and those with more understanding of the way these algorithms work, nothing more clear is the regurgitation of biased data masked as magic, whereby “newbies”’ are stimulated by the theatrics of output at the expense of unknown societal effects. The ease with which GenAI can generate content at scale, and users indulge in its form, presents a new wave of instant gratification. This content generation activity is being taken to the extreme, where even some users hoard and dub their creations as final pieces of art. Much of this is GenAI’s ability to create near-human-like productions at awe-inspiring speeds. It’s both fun and productive. However, it has crossed the line with some groups that debate the social merits of produced content. Only in 2022 did Jason M. Allen, a video game designer in Pueblo, Colorado, who won a local art competition, receive internet pushback from artists after he posted his work online. Reddit further exhibits its polarizing discussion.

Théâtre D’opéra Spatial by Jason Allen Jason Allen via Discord

In the current use of GenAI, our newfound active interaction model within technology (aka rapid participation) is driving many industries to inevitably try and solve more problems quickly. According to Delloite’s recent State of AI Report in the Enterprise, GenAI efforts in business remain more focused on efficiency and cost reduction than innovation. Those that cited more expertise in AI showed earlier signs of moving up the curve, such as using AI for more innovation and growth. Though, in reality, the benefits of GenAI are literally changing by the day.

Emerging Cycles of Human Gratification & Learning

One of the main reasons why GenAI will increasingly succeed is that its fuel rests in the demand for human gratification and production. At the heart of the GenAI/human dialogue is a next-level augmentation of people and their yearn for improvement of skills within a new era of learning. As opposed to traditional ways of learning through teachers, role modeling, and memorization, AI now allows us to accelerate a process of understanding with renewed creative output in order for us to develop new learning loops for ourselves. In general terms, this is generative learning.

One of the recent examples of this idea can be seen by John Nosta from Psychology Today, through his speculative idea of the CIE Axis. In this model, John explains that with LLMs today, users are deeply engaged through a loop of three primary dimensions. 1) Curiosity 2) Iteration, and 3) Engagement. Within his model, it is the iteration of dialogue that perpetuates long-lasting user engagement with learning brought in initially by human curiosity. With the fact that humans are interacting with exceptionally high-resolution AI tools, we now see a new level of excitement behind the efforts of participatory dialog.

The Quest For Our Attention

It appears that the glue that holds all of this active interaction model together is our attention. It is our attention, like a commodity, that provides the means for us to conduct new forms of creative production within emerging sets of AI tools. In a recent article by James Tindall, he explains that as we come to interact with a new generation of AI algorithms and spatial computing, the underlying purpose of these tools and those who control them is not just to the benefit of users but rather to hold those benefited in a mediated state to feed the engine of a techno-induced, value hungry society. He explains further,

“The first is Generative AI. An array of tools that promise frictionless generation of original text, speech, image, music and video. As with the democratisation of publishing content to a global audience, the democratisation of production afforded by these tools is not the empowerment it may at first seem. In reality Generative AI offers only extractive methods of production while further entrenching power over attention.” –Jame Tindall

The quest for attention is by no means new, as it was once the advertising industry that competed for our attention so it could seed ideas to transform our desires into buying behaviors. The ideas and ads to buy cigarettes, drive cars, and drink milk are just a few that made us covet more than what we truly needed. Now our coveting has turned inward, supplemented by a new form of active participation with the intention of creating our own simulated realities of gratification.

A Call For Human Intervention

To no real surprise, what we are witnessing is the dawn of spontaneously simulated feedback loops. The constant creation of new media, videos, content, and personal commodification is on the edge of twisting reality, where our ability to keep up and rationalize becomes more difficult each day. GenAI, with no doubt, marks a double-edged sword, spinning with wonder and learning but also hurling us towards unknown implications. For this reason, we believe human intervention in AI needs to be on the agenda of every business. People need to reflect on and revisit the intentions of technology and understand its deeper implications for society. We believe companies can take a practical stance on AI and should start developing their own points of view on how to use these tools and for what desirable goals. Some of these areas define what jobs are most important to focus on versus others that may be more suited for AI technology. Developing practical frameworks such as user jobs can set the stage and provide a larger framework for organizations to transform themselves in the long term.

Another area to consider is AI policy and the intentions companies will have for society. Societal pressures such as privacy, environmental harm, mental health, and misinformation are now at the center of how big businesses need to rethink their future impact. The reason is that our current state issues have gone far beyond linear progression and into what’s referred to as a a polycrisis.

Conclusion

As we engage in a new active interaction model, it’s important now more than ever to re-engineer human thinking back into our production and daily work. As we learn to create new future artifacts, tools, and content, we must revisit the most important societal values we want to keep and also those we wish to amplify. One thing is for sure: the future will most likely be a much noisier place than it is now. For this reason, we desperately need to establish new areas of peace, liminal space, sustainability, and intentful evolution. The next generation question might ultimately be, What does it mean to be a future human?