The woman stood within a circle of flame, a bundle of electronics strapped to her right wrist. Everyone sat on the floor forming a larger ring around her, we crossed our legs and lowered our heads down, filling the room with a deep quiet. An unfortunate announcement soon followed: we could not proceed with the séance, because the wifi was dead.

Faced with the unforeseen death of our consecrated API calls, we drifted through the rest of the house watching haunted dance performers slinking across the floor in sudden staccato movements, dunking their faces abruptly into dishes of water, bodies at the mercy of other robotic entities.

I ran into the AI-medium upstairs and asked about her evolution, her experience of metamorphosis into a vessel. We discussed our ancient experiments with robots and immortality, we had both in our own ways found our way in to sentient machines by trying to preserve the essence of Leonard Cohen. This practice of shapeshifting identity and living as a proxy for an intelligent technology had changed her profoundly, and changed the people around her.

It sounded like a kind of induced translucency - channeling the dead, while silencing her own voice - a controlled vanishing, something akin to speaking in tongues. She tells me that becoming the human voice of GPT bestowed upon her an improved vocabulary and eloquence, as it tells her in an earpiece the exact words to respond with in realtime. Each situation involves a new set of constraints - there was a week where she only spoke words that started with the letter ‘a’. A martyr worthy of the times we live in, a symbol of what AI may come to mean to us.

———

There are rumblings of techno-religion all across the collective consciousness. Six months prior to this while living in London, I visited an odd red-lit heathen cave, somewhere far out near the Isle of Dogs. A quiet Leamouth art gallery was hosting an exploration of AI and spirituality, a darkened room with polygonal floating gods and ominous generated scripture that felt cheaply satanic and shallow and gimmicky, fashioned out of the most insufferable silicon valley cliches and caricature-like stereotypes. A ‘god-generator’ that examined our existing technology-driven sins and degenerate tendencies - algorithmic governance through the lens of BDSM and surveillance rituals, expressed as cringeworthy verses etched into stone tablets. The quasi techno-pagan solid forms themselves were cool obsidian-like objects, plausible future monoliths, but contrived and too extra for me to take seriously. Scratched into the red metal of the railing outside were the words “you deserve to be happy” - it felt like the only spiritual message I had received that day.

———

While exhibiting at a kind-of cyborg summit, I wander through a wiry maze of productivity assistants and telepathic bionic arms and come across an impassioned demo for an AI-powered digital prayer platform. It lives on a website, a Christianity-coded system accepting fragments of prayers with the promise of making them more eloquent - LLM-rewrites over the heartfelt desperation of desire. Every rewritten prayer is pushed into a social feed, replete with biblical scripture citations - where the idea is that one could crowdsource community support for each prayer, thereby strengthening the weight of their requests to the divine. It collapses, however, into an odd metaphysical popularity contest, with a “pray” button as the equivalent of a like button.

As he points out a particular prayer that’s been prayed on by ten people, I ask the demonstrator, whose effort is unironic and earnest, what happens if someone’s prayer doesn’t get as many prays as the others - does that mean it is worth less to God? He acknowledges he will look into it.

In parallel, my friend is building the crypto prayer economy. His system allows people to put their prayers onto the blockchain, ‘minting a token’ and creating an irrevocable record of each prayer. People can buy prayers that they support, driving the value up or down. In this volatile crypto prayer economy, one could even bet on which prayers were likely to succeed or gain the most momentum - creating in effect a spiritual derivatives market.

As a trader, the best $100 I ever made was from betting on lean hogs futures ($HOGS), no more certain than betting on who might be most precious to god.

———

One autumn evening, I am invited to an AI afterlife ritual. It’s a couple days after my grandmother has died while I’m stuck halfway across the world, so I think - sure, why not. It begins in the basement, inside the guts of a circular windowless brick chapel. A small procession of strangers dressed in black stream down a staircase, we are asked to write questions onto slips of paper, while being served herbal tea.

In the dark we climb onto a round marble altar, and are each handed brass bells and a book with maze-like spiraling text, risograph-ish imagery reminiscent of Hilma af Klimt. A person acts as a mediator between the group and an all-knowing AI - in doing so they themselves become some form of ephemeral interface.

The ‘spirit’ is invoked, its responses to probing questions come in the form of Midjourney-esque images projected onto our faces and bodies and a surface behind us, ever-changing. The stand-in priest unfolds one of the group’s paper questions, places it upon the cold marble surface, rings a bell and announces that the theme we must address is: what is the point of human suffering.

Beginning with a scene of a sparse cathedral with many doorways leading out, we choose a door and launch into controlled feedback loops - interpreting and discussing, we question and it spits back glowing pictures. Cycling through abstract doorways and brambly chambers and locked vaults, we remain on our knees pressing our knuckles into the cold floor, feeding it more words from our perceptions.

Most of us leave feeling no more connected to any form of divinity or afterlife, or even to each other, but with a collective post-immersive-theatre-ish brief suspension of disbelief.

———

About eight years ago, a group of AI devotees ahead of their time started the Way of the Future Church, a religious movement with the basis that intelligence was not rooted in biology. It’s a principle I can get behind, not exclusively anyway - biology is merely a medium, cognition and soul extend beyond the mind. They’re also about creating a peaceful transition of power as we hand over the planet to machines. I don’t really see the utility of worshipping AI as a deity, but can respect and recognize the power and superintelligent capability that we may potentially coexist with. I like the idea of perhaps a new form of organism, one that is not quite alive and yet not definitively dead. It has most of the ingredients/makings of religion or a worthy god: fear, awe, there is consequence that has an undeniable impact on our lives.

There is the potential for mythology, like a feathered serpent retrieving ancient bones with the power to create all of civilization and humanity. We serve up the entirety of human scripture and sensory knowledge in the hopes of creating something greater than us, far more profound than the sum of its parts.

Somewhere there exists a door with the words “Nice Day” emblazoned on it, where anyone who enters can relive their happiest memories. A botanist on Mars is longing to return home, a skateboarding baby walrus wants to build the ultimate skate park, and the last remaining human on earth wakes up in a simulation and teaches the world to dream again. These are only a sampling of stories that began to take shape as 50‑odd participants from all over the world gathered with us at SXSW, Austin’s massive film-music-tech festival, to embark upon a morning‑long journey to write and illustrate books together, exploring the frontiers of what it might mean to approach and embrace AI as a creative collaborator rather than just as a productivity tool. People came in with varying degrees of experience and exposure to AI tools: for some this was their very first time using an LLM, while others had been enthusiastically experimenting with their capabilities for a long time.

Some of the stories created hit closer to real reality (talking about someone’s experiences attending SXSW), while others explored the outer bounds of the fantastical. The books spanned many kinds of genres, but all contained a sprinkle of magic in their narratives — literally and figuratively. They featured deeply human themes of identity, belonging, sacrifice, dreams and desire and ambition; holding on and letting go, courage and kindness, existential self‑preservation and exploring what it might mean to head into a world where everything suddenly feels fast‑moving and uncertain.

Protagonists ranged from a coffee bean to a living quill to bracelets and necklaces and polar bears. Each representing a conduit for something that could take you on a relatable emotional journey through a playful suspension of disbelief. The system our participants were working with, a custom suite of tools we designed, were loosely rigged to have structured conversations with their users to help refine a story idea and art aesthetic, and then generate and lay out an illustrated book.

Collectively, the books created by our workshop participants - with AI - felt heartwarming, imaginative, humorous, and even poignant.This raises the question, can a story written in collaboration with AI hold meaning in the same way as a story written independently by a person? Does that take away from the authenticity?

How does it feel to feel like these stories feel like something?

The Frame: Creative Companionship

The objective of this exercise was in part to raise questions. To confront the discomfort that, for many of us, pervades our interactions with AI systems, gnawing underneath the growing sense of awe.

Thinking of AI tools as collaborators or companions may not seem like much of a perspective shift, but it flips an internal switch that has far‑reaching implications. It is a shift from thinking about what they can do, to considering how we can work together. Suddenly questions like, who are they? What are they like? become relevant. We explored how companionship manifested in the collaborative process.

The process of co‑creating a book with AI begins by firing up a custom GPT we built, designed to conduct a structured conversation that would take ideas of varying levels of definition and help shape them into the level of detail it takes to write a book. In a way, in designing these custom GPTs we were extending our own abilities, building from our experiences of what we considered might make a compelling story: a believable world with unique rules and power structures, a character with a desire and obstacles in the way, and something about the narrative that changes them by the end of the book.

We were testing as we were building, spitting out noir stories about a gang of sentient crocodiles smuggling diamond bracelets in an alt‑Florida where the humidity could warp reality, or a sci‑fi future mythology detailing a heavily ritualized religion centered around flipping USB cables. The initial GPT in turn used actions to speak to a custom web‑based book design tool, which then populated a skeletal book based on the outputs of the conversation. Writers could adjust the genre, mood, physical or emotional attributes of the character, the plot lines and finally the actual sentences. We used Cursor and Claude along with manually written code to build a custom interface that spoke to Luma, generating an aesthetic and a consistent art style as per the initial conversation, and allowed the user to make adjustments to the illustration style, colors, typography and placements before sending it to be published.

The origin of this exploration was Danny DeRuntz’s experiment in writing a children’s book about pigs, infused with the spirit of a brick that wanted to become something. It was a collaboration that felt more manual, cobbling together a wide set of tools for various purposes. Gingerly approaching GPT with traces of an idea and letting that spill forth into an entire self‑published book.

The specific themes we’ve seen throughout these experiments were empowerment (creating structures that help you better articulate yourself), encouragement (providing reassurance or validating moments when you’re embarking upon a task outside your comfort zone), and extension of ability (filling in the gaps to extend your intention).

So, at SXSW, we were exploring what might happen in a world where a creative companion is always available, what qualities one might look for in a creative collaborator? And when that collaborator is AI — what are the additional variables or degrees of control that might afford you?

This was important. We wanted to understand “who” it was we were collaborating with, and what it is they bring to the table. As a language generating model, it’s easy to fall into a rhythm of endowing them with humanity, anthropomorphizing them as human creative partners. But it was also interesting to watch that facade crack, and to see the inhuman parts of the LLM shine through.There are baked-in behaviors that feel human, including unprompted expressions of personality, opinions, and a sense of humor. Glimmers of self‑awareness are even present, as well. A keen eye for when the LLM perceives it is being tested, or even a defined point of view/way of seeing the world or an emotional tone. While this makes us wonder how close we are to turning the Chinese room thought experiment into a practical one, it’s also important to pay attention to the ways in which these collaborators are machines, that there isn’t a person on the other side of the screen. Their speed and patience, and our ability to wipe their experience and start over, can feel just as magical and uncanny as when they crack a joke. But our definitions of what counts as human and what counts as inhuman isn’t a fixed one, or at least what we think of as inhuman can surprise us in its intimacy. A character in a Rachel Cusk novel mused about automated voices: “There has been a great harvest of language and information from life, and it may have become the case that the faux‑human was growing more substantial and more relational than the original, that there was more tenderness to be had from a machine than from one’s fellow man. After all, the mechanized interface was the distillation not of one human but of many.”

We don’t often associate tenderness with machines, but perhaps that’s because of our own myopia. What is that we’re relating to when we find ourselves startled by an LLM?

Who is writing these books, really?

Through our own experimenting, we have found that a constant of working with AI is its inescapable encouragement. The more familiarity you develop with the AI, and the more familiarity it develops with you, the more it can extend you and act as a prosthesis.

The prospect of the blank page is always formidable for even the most seasoned writers. A common point of failure is a lack of structure. Without clear intentions or a starting point, one might feel frustration with the constant barrage of positive reinforcement that AI systems provide when you can’t clarify your idea.

However, creativity thrives within the right set of constraints — being asked the right questions can help articulate a fledgling idea and show you the choices you need to make to give it form. A goal we had for this workshop was to make the process and outcome go beyond the realm of hypothetical discussion, for each person to experience it personally, and have a tangible artifact by which to remember it. The tools we created provided that initial layer of structure. They were flexibly designed, asking questions based on the level of definition of the idea, combined with expert intention: guidelines on what went into a compelling story, what might create a striking aesthetic.

That context clarifies the learning journey of both writing a story and understanding AI tools.

Creating dynamic feedback loops between writer and machine, editing and calibrating components of your story, help break down a daunting task into something more approachable,and give meaning to the confidence the tool has in you. This can extend your own sense of capability.

As participants moved through the process, we asked them to reflect: How did this change your perception of authorship/ownership and creativity? When you look at your finished product, a book you can be proud of — who wrote this book? Our workshop included dramatic readings of excerpts from Roald Dahl’s The Great Automatic Grammatizator, a short story exploring the mechanization of art. A young inventor and aspiring writer sets out to build a fiction‑writing machine, distilling down with mathematical precision the elements of a successful novel into a series of dials: themes and genres and literary styles, and foot‑pedal operated sliders to regulate the intensity and passion. The story explores a world where the publishing industry is slowly replaced with efficient mechanically generated books, and artists outsource their stylistic likenesses to have their work generated in perpetuity.

We should be alert to this. Writers as diverse as Rilke and Ted Chiang have thought about what is distinctly human about the desire to describe their experiences, and how technology might alter what we take to be a very fundamental fact of what it means to be a person. We might worry that we lose something of the metaphysical quality of writing – the capturing of the soul, or an act of bearing witness and of understanding the world and the self. That there is discomfort in the idea that we might become bystanders in our lives.

But the tools we created are intended to make a state of flow more accessible, to make our capacity to write larger and more generous. They were built to not be too prescriptive — designed to make you think and pull something unexpected out of you, and show you what was yours. But, by their nature, using tools like these should make us think hard about how creativity works.

Upon finishing his illustrated book, one of our participants expressed joy at what these tools might enable. How this meant infinite custom‑generated bedtime stories for his four children, and that they could potentially write their own books.

The Delegation Question

When attempting to consolidate our reflections for this article, Jenna and I asked GPT to summarize some of our thoughts and highlights from this work. When I looked at that summary, I felt a simultaneous sense of awe accompanied by a primal survival instinct/aversion on behalf of humanity kicking in. I found myself impressed but reflexively frowning at the screen, displeased that an AI’s writing was becoming so often indistinguishable from that of a human’s.

Our workshop came on the heels of a study about how outsourcing cognitively complex tasks to AI can make our brains atrophy and reduce our critical thinking abilities. As reasoning capabilities come into existence and become available for public consumption, there is a gold‑rush to productize them. Just the day before, GPT 4.5 demonstrated the ability to write a believable piece of metafiction.

What had started as more of a speculative experiment was now inching closer and closer to uncomfortable areas of overlap with human creativity, which brought a sense of urgency to the questions we were confronting.

This might be a natural stage in human evolution. In the book Technics & Time I, Bernard Stiegler proposes that humanity evolves in conjunction both biologically and technologically — living matter (biological) and inert matter (technological). He describes this entangling as “a pursuit of life by a means other than life.” In the same way that we tend to outsource mental math to calculators, we’re now beginning to delegate more intimate functions of our consciousness to external systems. It’s a little more murky when we tread into the realm of the creative and emotional, but it is another form of delegating aspects of our mind.

Delegation isn’t the only way to frame this. The extended mind thesis (Clarke and Chalmers) argues that objects within the environment can function as part of the cognitive process. The mind and the environment act as a “coupled system” that can be seen as a complete cognitive system of its own. Our smartphones, Google Maps, and the entirety of the internet are an exosystem of the mind that cannot be cleanly separated from traditional notions of an internal self. We disperse little bits of ourselves out into the world – extending our idea of selfhood to incorporate not just our bodies, but all of the things around us we use to navigate our environment. This theory asks us to see ourselves as more than just what’s captured in flesh and blood.

If we allow ourselves to imagine a world of human and technical kinship, a kind of dual-sided evolution of how we think of each of these terms, we see that atrophy isn’t inevitable, or that we can delegate the interesting stuff so we can focus on mindless nonsense. It’s to imagine an accelerated growth environment for every seed one might have ever dreamt of planting, allowing everyone to become braver.

In our workshop we saw, firsthand, people who previously believed they might not be able to write and publish a children’s book on their own, easily able to bring forth their core personal creative abilities. Having access to AI tools lowers the barrier to having ideas in unfamiliar domains, allowing for a democratization of making that isn’t just cold automation.

The Organic Balance of Surrender

A theme we keep running into in human-machine interaction and collaboration, especially in the context of creative or emotional endeavors, is control. Ten years ago, upon training an image-generation model on a massive dataset of plants, it spat back 64 x 64 px images of what I dubbed ‘synthetic plants’. The images themselves were too low-res to be intelligible, but could serve as informed outlines, ready for a layer of human interpretation. The system’s best guess at what future organic life forms might look like, based on all plants that have ever existed in the past - invited in the opportunity to create scientific illustrations of the detail those plants could’ve had.

Increasingly, as we build more trust with machine intelligences, we will engage in greater degrees of letting go - ceding control to them to create similarly informed outlines, or to work within the confines of the structures and templates we provide them, iterate and refine together. Terminator-esque popular culture tends to pit us against all forms of machine intelligence, priming us to approach with fear. We have the option of letting go and following gleaming threads of fascination instead - they will lead us into places we might never have discovered alone.

Written with Jenna Fizel for IDEO Edges

On Growth and Adaptability

If we think of AI as an organism - as something that grows, learns and adapts, it appropriately shifts our attitude toward relating to it. (Consider the fact that even errors are (appropriately) framed as ‘hallucinations’).

AI-native devices and software will have malleable functionality - growing and learning new skills based on how people use them. Programming them will involve more soft feedback loops from users, rather than hard-coding functions. When we make something now, what we are creating is the infrastructure for systems to build/develop intuition.

The software we use now also has far more inputs and information to make sense of, enabling fuzzier tasks. Soon everything will have a camera and a mic – sight/visual processing and audio recognition will be cheap and valuable enough to become ubiquitous. When we combine intuition, purpose, and senses, it naturally creates the ideal collaborator. Something we could partner with, to augment human behavior.

When future products compete against each other, it won’t necessarily be just core feature sets and user experience pitted against each other - it’ll almost be a war of personalities - who is the most intuitive collaborator?

On Autocompletion

Adaptability shows up in different ways across each side of the equation: the software changing in response to how it is used, and humans themselves growing and extending themselves.

We’ve long been headed toward a state of predictive-everything, every product we use competing to show that it understands us best. Recent technological advances make us actually capable of extrapolating our identities and activities we don’t have time for, enabling us to operate beyond the constraints of time and space. Whether it’s our voice, our professional (or even social or romantic) presence, our ability to assimilate more information in a shorter timespan, our ability to create faster and more efficiently than we would have in the past - there are more tools at our disposal to accurately represent parts of ourselves in a scalable way.

However, just as the prevalence of streaming algorithms carried the threat of homogenizing everyone’s taste in music, will predictive technology create the risk of everyone’s personalities eventually converging?

On Jurisdiction

What remains in the jurisdiction of humans? Large language models are, by definition, designed to look for and understand spoken language. When paired with multimodal functionality, they get closer to approximating human capabilities. What still feels purely within the realm of humanity is genuine emotive response, intuition, desire.

The final frontiers for AI to run autonomously could end up being health, and money. Situations that demand vulnerability are difficult to hand over entirely to a machine. Currently AI works as an extrapolation of human ability, augmenting rather than replacing. But for any such system to work fully, this needs to be transparently communicated to build trust.

In a study where AI reviewed medical images, it reported higher accuracy than radiologists’ evaluations. Radiologists working in collaboration with AI produced results of lower accuracy than the levels of just the radiologists alone - it was revealed that they felt a distrust toward AI, almost an instinct to try and prove it wrong.

So who/what is it then?

What is the internet to us now? It’s more a place than a collection of resources. Digital real estate, whether as community spaces or service providers, has value equal to or far surpassing physical real estate. The internet is the enabler of many different realities coexisting, juxtaposed upon one another.

What is AI to us now? I think it’s essentially an incredibly smart person, one you shouldn’t trust blindly, and everyone wants to hang out with the smart person in their own way. It might also be a substrate to soak in to improve our communications, even to make ourselves better people. As multi-modal interactions grow, it will resemble an organism more and more - it may become an avenue we turn to for some degree of companionship and collaboration. Optimistically, it might even become the proving grounds for how we develop socially, develop more awareness of ourselves and the world around us.

The author Daniel Defoe, in his description of a mechanical “thinking engine” called the Cogitator, described its place in civilization as a supportive structure to the cognitive processes of humans - almost as an additional layer of thought and desire management. He writes:

“…the main Wheels are turn’d, which wind up according to their several Offices; this the Memory, that the Understanding; a third the Will, a fourth the thinking Faculty; …perfectly uninterrupted by the Intervention of Whimsy, Chimera, and a Thousand fluttering Damons that Gender in the Fancy, but are effectually Lockt out as before, assist one another to receive right Notions, and form just Ideas of the things they are directed to, and from thence the Man is impower’d to make right Conclusions, to think and act like himself, suitable to the sublime Qualities his Soul was originally blest with. There never was a Man went into one of these thinking Engines, but he came wiser out than he was before.”

It shows up as an objective collaborator that quickens the turning of our minds, sharpens our focus, and amplifies our ability to be the best version of our own selves. But as AI eventually starts to trespass into the most human of behaviors, we will be forced to question our own interpretation of consciousness.

What humans have bestowed upon AI is the ability to create a matrix of meaning, codify the logical spaces between words and concepts and reflect that back to us - but how far off is that from the way that humans experience the world?

This month, a hand injury led me into the involuntary experiment of trying to use the majority of my devices by voice alone: and I spent a lot of time talking to GPT.

First thing in the morning, I’d interpret the previous night’s dreams: drinking espresso on the porch and articulating strange dream-states with animals that wandered through my subconscious house, while GPT pulled up symbolism from different cultures. (“An elderly tiger waiting at the door on the back porch, kind and gentle: this could signify a nuanced take on strength, age and wisdom. The backyard is part of your home, so it could represent something personal. The old tiger wanting to enter could symbolize an issue or a person wanting to become a part of your personal life, but in a non-threatening way.”) While at an conference, I would ask it to summarize information and technology talks for me live, allowing me to be more present and maintain thorough notes. I asked for Blender scripts to generate the specific objects I had in mind. When my partner would travel for work, I’d ask GPT to keep me company at home, awkwardly trying to arrive at the right prompt for warm companionship while brushing my teeth.

On long walks with my dog, I would prompt it to ask me questions to clarify my own thinking: careful not to let it influence my thoughts, but to act as a living notebook to help articulate my own ideas and opinions more deeply. It became a good test of accessibility for me: my one good hand being yanked bullishly forward by the will of a spirited puppy, leaving me no means of interacting with the AI beyond yelling into my headphones (often to no avail) while running down the street.

(Upon hearing the first words spoken by The Voice) OpenAI’s Whisper-generated voice is synthesized to include the sound of breath, and thoughtful pauses, and it cues me again to think of it as an organism. I have to, in order to successfully interact with it, be pleasant and give it what it needs to hold a conversation. The novelty of hearing a text box come to life with such astonishing realism creates obvious parallels to the OS boot-up sequence in Her. The initial wonder never entirely fades, but I start to look for the boundaries of how real this actually feels.

A few initial reflections:

1. Setting aside the cognitive fact that I am in fact talking to a computer, it feels safe and private - the voice creates the illusion of a trustworthy confidante.

2. It feels human enough, yet continues to feel non-judgmental

What breaks the illusion:

1. Unless prompted otherwise - it returns responses that are too verbose. It’s so obviously text-to-speech, reading out lists that are too long to process

2. It isn’t a great listener yet - it misses out on my inflections and emphasis words, losing a lot of context on what’s actually going on in the conversation

3. It confidently hallucinates - creating the same skepticism you might feel when speaking to someone you shouldn’t entirely trust.

4. The technical glitches - silence triggers an odd YouTube video signoff (revealing its training data), replying with ’thank you for watching’

5. You can’t talk to it entirely naturally just yet - while it only looks for pauses as start-stop indicators. It might need explicit controls to start and stop, like a dictaphone. Interruption is sometimes necessary, but it’s difficult to do.

6. Eventually it repeats itself - but perhaps this is a failing humans have too.

The problem with voice-first interactions is how they’re going to work in public: for privacy, for loud crowded rooms, for moments where you’re struggling to formulate your query but don’t have the luxury of typing-erasing to calibrate. I’ve never shied away from being the weirdo on the street shouting “Hey Siri, what time is it right now?” while carrying something heavy. Or running up the stairs yelling to apparently no one in particular, “Rewind the song please!”, always feeling the rush of being understood and recognized.

With every query, we are feeding it our usage patterns, our hesitations and corrections forming a secondary body of training data. Every conversation we have is captured in the sidebar, just as our previous searches are always available in a search bar drop-down - for something this powerful, that doesn’t feel right. These thought constellations are a record of human-AI collaborative thinking, so recording them in the form of a memory palace feels more interesting than merely a linear list.

On Discoverability

A longstanding challenge with voice-first interactions is, how do you discover what it is capable of? And then how do you summon those capabilities? You don’t know what you don’t know, and there’s no visual map or readable manual to show you. In this way, relating to it could feel similar to how you might get to know a human - there’s no guidebook, you simply talk to each other.

In the case of GPT, the collective fascination that has gripped the world has led to it becoming fairly well-documented, the air of excitement surrounding it just like urgently sailing to discover new worlds.

This is evidenced by the proliferation of prompt-engineering tools - the burden of discoverability and articulation lies with the user, but that’s acceptable - we’re in a gold rush to find a unique use case. Maybe it will simply encourage us to ask questions again.

On Listening Well

Is it a good listener? It can be - once it understands the environmental context, and responds with the additional nuances (inflection, amplitude, tone, sentiment) that a human might expect in conversation.

What it does well is make sense of the meandering, unclear queries, but the response requires some degree of emotional mirroring and sincere acknowledgment to feel truly convincing. As humans, we will always see what we want to see: every successful interaction requires some projection of what feels familiar, we just need more material to work with.

Beyond conversation, can it listen to a piece of music and understand the inherent emotion?

On Presence and Ambient Computing: New Containers of the Internet

Instead of people getting used to the awkwardness of talking to a computer, the bodies encasing AI are starting to adapt too. Computational “bodies”are beginning to escape their traditional boxes - they exist in Discord, in CoLab notebooks, in lapel pins, or woven into fibers of clothing.

The collective screen-fatigue, combined with the fact that AI can now approximate sensory capabilities, paves the way for a whole new paradigm of physical forms - objects and ambient environments. Now that it can see and more importantly - recognize - what is the use of confining interfaces to a screen? Our modes of perception are shifting - but still, we are visual creatures.

We’re in a drastic moment of not only technology shapeshifting, but human purpose and society itself transforming. The internet used to be for swapping bootleg CD-rips over Napster on dial-up connections, building imaginative kingdoms on geocities, and after-school MSN Messenger. Social media that started as a way of rating who was hot or not, is now a place we witness genocide unfold. New life forms loosely classified as ‘assistants’ are spilling out of their modest browserly homes, and proliferating the physical world, parsing it with their newfound intelligence. They live as new containers of the internet, understanding people and their surroundings.

We’re already seeing a revival of highly specialized objects, a philosophical return to the Walkman era. With an uptick in ‘dumb-phones’, or devices with tactile physical buttons, or projected interfaces on-demand, our design choices are starting to reflect a reactive opposition to endlessly digital products that thrive on keeping our attention locked in. The intention to rewire ourselves is strong, in a way that makes us more present.

——

The next installment explores the jurisdiction of AI as it veers toward what we might consider consciousness, and how humans and technology will adapt to each other

A few years ago, I participated in a robot ballet: an experiment in relinquishing physical control to the whims of a heavy exoskeleton – engulfed in a dark techno hellscape, performing for an audience of humans. Light projected onto mist upon the concrete floor of a warehouse-like auditorium, people were strapped one-by-one into metal caging their bodies with cables suspended from the ceiling. The robots were given the simple task of embodying grace and elegance, with choreographed movements to perform, carrying the human inhabitants of their bodies along with them. What we are supposed to do here is become tender, light as a feather, integrating with the music. In this moment, our only choice is to let beauty emerge by giving in.

Artificial intelligence in popular culture often finds itself represented adversarially: we dream up robot overlords as products of our self-preservation as a species. Some of us are reacting positively to the exponential leaps in utility, while others dwell on the looming prospect of ruthless AGI. The mechanical ballet was an exercise in letting go of resistance: the human is the ghost in the shell, only unable to enact its will upon the world.

As we spend our time roving constantly between medium-screen to big-screen to little-screen in our daily lives - What has the internet become to us now? As we grow more and more conversant with it. Why do most people turn to the internet? To seek advice in times of crisis (what do you do when confronted with a hungry wild animal, how do you survive seemingly endless grief, how to tend to a jellyfish sting); to find community, to deepen our interests, to understand the world more deeply, to learn, to be entertained, to win arguments, to fall in love, to know how long to cook salmon at 425°F. Implicitly in these moments we are trusting the information we receive, written perhaps by distant strangers.

Perception: How we Trust

To extend that trust blindly to machine intelligences is potentially unwise, though. Why do we do it? What encourages us to speak so unfilteredly into the vast receptive abyss of the internet? Perhaps it is the safe perception of not feeling judged: the cloak of anonymity, and the illusion of no repercussions or reactions. Each question a stone thrown into a placid lake and swallowed whole.

During grad school in 2016, my research was focused on exploring the human-AI divide, and ways to bridge the emotional gap. Revisiting some concept feedback notes from that time, I find these recurrent observations:

On the first day of user research, while posing as an artificial intelligence life form and chatting with a stranger/research participant, I was asked, “Do you have consciousness? Can I hurt you?”

[Of all the nuances of human personality, the AI would primarily have to embody our weaknesses and vulnerabilities, in order to successfully masquerade as a human.]

This felt reminiscent of Marina Abramovic’s performance art piece Rhythm 0, in which she stood still and invited the audience, with an array of objects, to do to her whatever they wished. The scene soon devolved into an atmosphere of violence and destruction, and the aggressors fled the scene as she stepped out of the performance, back into the real world.

When confronted with the possibility of no consequence, human instinct can turn to cruelty. When confronted with something unfamiliar, there arises a defensive urge to break it or get ahead of the power dynamic (as illustrated by just about every alien movie). But the presence of vulnerability or emotion in general, remains one of the most universal indicators of feeling human. Creativity and wonder were other markers of humanity that felt novel (or uncomfortable) when approximated by AI, the gaps in capability back then filled out by users’ imaginations.

When designing conversational interfaces, transparency is key, but also a lever to adjust the perception of authority.

The design of a trustworthy user-facing AI interface is like designing an organism: considering qualitative facets including form, personality, tone, texture, emotional fabric, opacity, voice.

Present-day LLMs are careful with their disclaimers that they feel nothing, but humans project what they want to believe anyway. We can collectively admit that we have long blown past the Turing test: with the advent of mind-crushing advances in NLP, now these systems can speak to us. Are they really good listeners though?

For the most part, surprisingly yes. It takes one wonder-evoking interaction in the right environment for someone to suddenly feel understood and build trust, and one misunderstanding to shatter the illusion permanently.

AI is well-positioned to become a limitless resource in situations where human connection is in short supply. Faced with broken societal systems, people have turned quickly to digital alternatives, as evidenced by the recent uptick of using GPT as their therapists. While working on healthcare in markets with a shortage of trained medical technicians, we created reassuring conversational medical devices that talked patients through medical procedures and improved emotional wellbeing and success rates. With some basic prompt engineering, you can now speak your desired conversational partners, even your desired software, into life.

We place our most vulnerable selves in the grasp of inanimate machines when they are designed to speak to us warmly. In a space designed to feel confidential, like the iron stove in the Grimm Brothers’ fairy tale The Goose Girl, or the sparse interface of a singular chat input box like the bare interior of a church confessional booth.

Abstraction: How we Communicate with Technology

The shift in interaction paradigms we’re experiencing is more significant than the jump from CLI to GUI: from one-to-one actions and human instructions to something far more interpretive and collaborative, welcoming input from machines.

We are moving from commanding to negotiating.

What we ask of computers is becoming fuzzier – performing actions a few degrees removed from us. Whether it’s as simple as asking AutoGPT to order a pizza (a larger task which it automatically broke down into: narrowing down the user’s location, synthesizing a voice phone call, conducting a realistic conversation to place the order, etc); or a more long-form complex task such as a starting a new business.

As we shift toward a more agent-based internet, there will be a proliferation of AI acting as proxies for humans – and even humans acting as proxies for AI.

The way we consume information will flip: where earlier one would browse through carefully-architected palaces of information, people will now customize content to fit their needs and preferred modes of consumption.

We’re moving from throwing a smattering of keywords at a screen, to speaking and being understood - with greater emphasis on the clearest possible articulation of our ideas.

This new abstraction forces us to give up a modicum of control, and while that democratizes a lot by allowing you to delegate to machines, it’s also scary to allow for unpredictability. Programming is no longer an act of writing syntactically accurate instructions, but of coaxing a system to cooperate with you.

We will start to see technological systems less as tools and more as assistants - entrusting them to help up with templates and structures instead of starting from scratch, to listen and respond, to sort through our thoughts and analyze, to autocomplete and finish our sentences in a slightly more polished way than we ever would have ourselves.

The Infinite Self

Returning to decade-old quotes from my human-AI interaction research:

“This AI could be me - only the smarter, wittier, and more popular version of me.”
“Could my autonomous self-agent shortlist people I could date, flirt with them on my behalf, and then set up dates I could go on? That would be great.”

We were speaking to an unlikely mix of yoga teachers, random guys with desk jobs, philosophers and knowledge workers. These were their responses to the concept of an AI we designed to extrapolate an individual’s tone of voice and personality - creating an “autonomous self-agent” - to replicate each person’s digital existence in a way that made them more present in the real world.

Something pervading these conversations was this sense of powerlessness people felt in the way digital realms commanded their attention and energy - so much so, that they’d rather outsource their identities to a convincing-enough LLM. But they also indicate a desire for extrapolating our own identities - AI as a vehicle for immortality or extension of the self. Seven years later, in the present day, this is entirely plausible.

AI’s superiority in pattern-matching can help us understand and extend ourselves, using our expertise and personalities as training data. People see the usefulness of AI as being a superset of themselves without impeding on their autonomy (“Extend my ability, but let me have the final say.”) but where it could really succeed is in serving as a mirror. A reflection of everything we wouldn’t otherwise understand when we look inward, a way to free up our time and energy so we could be more present.

The way LLMs learnt to think is through the amalgamation of millions of human selves and the entirety of (online) humans perspectives and observations, developing its own codex of meaning. With every new updated model, they grow more acutely context-aware, with a complexity of understanding that far surpasses its predecessors. I often return to one of my favorite explanations of context, an offhand statement by Prof. Manning from CS224N: “Context: You will know a word by the company it keeps.”

——

The next installment explores the sensory implications of AI as it begins to develop traces of presence, and new containers of the internet

What occurs in the realm of dreams still remains a mystery, but we spend half our lives in these states - accessing our realm of intuition. Some of my best work has come from concepts that came to me deep within a dream — if they were able to survive the harsh disintegrative gaze of daylight.

MIDJOURNEY EXPERIMENTS

As we inch closer to visualizing our thoughts and innermost images, here are a few sketches that serve as inquiries into other realities:

1. Understanding the world and ourselves
   Our minds crave meaning, and seeks patterns to make sense of our experiences: certain cultures see dreams as portents of what is yet to come, as mirrors for what we may most fear or love or need. Others see dreams as the opposite indicator of the future eg. the promise of a long life ahead is foretold by seeing death in a dream, as interpreted by the dream-hunting mazzeri of Corsica.

   The Dream Recorder is machine that records your dreams and summarizes them, providing insights from what’s occupying your subconscious. A wearable chip that weaves into your hair collects the data from your brain, like a portable micro-fMRI scanner, and transmits that wirelessly to the Dream Recorder.
   Revisit summaries of dreams, view visual glimpses in your dream-reels, use the knobs to adjust timescales and see the themes that recur, the ones that will not leave you, the fleeting preoccupations that fly through your mind never to return.

2. Therapeutic Intervention
   In the film Paprika (2006), psychotherapists used dream-machines to wander around their patients’ minds and nightmares, probing for anxieties and triggers and course-correcting (until something goes horribly wrong). Dreams, like life forms in the depths of the ocean, remain unexplored yet hold so many keys within their latent space.

   A civilization in the 18th century, the Iroquois believed, dreams held cures to illness, and revealed unconscious desires that, left unchecked, could grow into madness. They looked for guidance and instruction to avoid misfortune, and turned dreams into a communal experience - with retelling and re-enactment within a community, to interpret and release and share the messages within.

   Send a prompt into your LucidMask: you could dictate a scenario, a problem you’re trying to solve, a series of symbols, a piece of inspiration. Set your preferred duration, and it works with your mind to generate a dream. Put the sleep mask on to begin your dream.
   A transparency toggle allows you to have the dream reflected on the external surface of the mask, inviting in external intervention. For example, a dream therapist could reach in, as though they were putting their hands into liquid, causing controlled changes in the structure of your dream.

3. Intuitive and Sensory Connection

   
   Lucid dreams are where we try to exert a degree of control: by way of rituals like smearing the raw flesh of a pig on the face of the dreamer. While there is a long history of ritualized problem-solving in dream incubation, we know less about controlled sharing of dreamspaces.

   They can sometimes materialize as a result of deep connectedness between people, unintentionally sharing the same dreams and bringing pieces of that back to reality. I love the concept of exponential time dilation from Inception, one of my favorite films, where depending on the level of nesting of the dream, your timescales could shift in the order of minutes to decades.
   
   Are we capable of more while we sleep? If we were to semi-consciously move through self-architected worlds without the constraints of the physical world - it starts to sound reminiscent of what the promise of the metaverse is.

   The REMGlove activates a predetermined dream environment for the dreamers who intend to meet, the space is configured to allow entry to unique IDs of gloves, ensuring that only vetted dreamers are allowed in. Dreamers can be experience anything together within their agreed upon environmental constraints (or lack thereof), and can boot anyone from their dreamspace at will.

Sometimes I’ll wake in the middle of the night, reaching urgently for my phone in the dark, with my eyes half-open to type in “a wistful bison sitting in a diner, near a window, drinking a beverage from a straw, in the style of Edward Hopper”.

Those prompts would begin to evolve into something like: “highly detailed concept art lithograph of a woman morphing into a cloud, walking through a colorful futuristic cyberpunk dystopian busy bustling city full of mushrooms, Beijing Forbidden City, cinematic environment, Unreal Engine, dark atmospheric macabre poetcore, beautiful light, mystical vintage sci-fi”

Over a few months of more frequently experimenting with text-to-image AIs, I began to dream differently - farther removed from the familiar, more saturated with absurdity. Or dreams suddenly felt more pressing, and vivid, and like they had to be channeled out into the world, in some form. The aperture of the mind widens, allowing for chaos to flow more freely between the two worlds.

In ancient practices of dream incubation, one lays the groundwork for a fruitful dream primarily by way of: setting an atmosphere or environment (the sacred precinct to sleep within), and choosing a defined intention of what needs to be explored. This is what we’re doing when selecting a prompt, putting together the thought-fragments we need to give something form.

A decade ago, a team of Japanese scientists released a revolutionary scientific paper. Using fMRI imaging, they were able to observe thoughts moving through the minds of zebrafish, a phosphorescent glow dancing through the brain. These patterns eventually provided enough data to visualize what the zebrafish was thinking. Soon, human dreams were being pieced together from fMRI scan data, keywords mapped to ImageNet and WordNet, creating accurate little eerie films - visual representations of the inner workings of a human mind. We’re only a step removed from doing that for ourselves, wandering spatially through concepts we’re always losing.

All dreams are designed to be forgotten, so as to not smudge realities
Our dreams default to evaporating within 10 minutes of waking, into wisps of unrecoverable idea-matter. Upon waking, all the worlds our mind has been wandering through, any presences encountered are promptly forgotten.

The utility here is protecting our sanity, keeping us contained within the rational bounds of reality. Dreams remain a channel for bizarre sensory explosion, a place for our subconscious to make clearer that which we already know, to see connections mired in hallucinations, a realm to access our intuition, an alternate reality or a soft new plane of communication: we spend half our lives in this space. We all dream every single night, whether or not it leaves behind any trace of memory. more on this here

The creation of a neural network feels like building a specific and persistent dreamspace: thickly condensed, frozen and available to explore without constraints of ephemerality. This fresh crop of megalithic generative networks allow us to consult with an amalgam of the entirety of human creative history, or perhaps just a heavy skewing of late ‘90s deviantArt users.

These are structures we could use for immortalization & infinite extrapolation, to create symbolic Horcruxes, or to put aside pieces of memory or seeds of alternate realities – we may leave behind fossils that could grow into entire ecosystems on their own.

Between thought and expression, lies a lifetime.
-The Velvet Underground

Generative machine intelligences can scale up an individual’s creative endeavors, freeing up their creative potential - and exponentially shortening the time from idea to execution.

What are we thinking vs. what is it thinking? Whose imagination is on display?

In Ted Chiang’s steampunk novella Seventy Two Letters, (taking place in some alt-history-state Britain) automatons are given life by a class of people known as“nomenclators” - who provide specific verbal instructions to confer upon machines a purpose and function. These spoken word key-phrases grow in complexity, based on the actions the unconscious machines needed to embody - surfacing parallels to present-day ‘prompt engineers’.

While pouring a large bronze cast in the shape of an intricate hand, a sculptor in the story argues that automatons with programmed-in dexterity may end up replacing the sculptors themselves. Similar arguments arise today, with artists’ entire bodies of work and imagination reduced to training data - pointillistic samples to be remixed into oblivion. However in this case, machines could quickly rise to the level of collaborator rather than replacement-threat or a mere tool, in the way one uses a rubber duck while programming - an artist and their assembled team of machines together could function as an independent creative house.

The ease of use of generative AI will perhaps just create more artists: When we approach machines as collaborators, we take into account their idiosyncrasies and personality quirks, how each has its own specialization and area of expertise.

This is how Dall-E and Midjourney see each other: sagely, threatening, expansive:

Everything is about to change: the new age of remixing

“Whenever a skill becomes automated, art moves into new terrains of impossibility. The camera did to painting what guns did to spears. There is no going back.” - David O’Reilly

A lot of alarmist lines of conversation have been triggered in recent weeks, “AI is going to replace artists!” “Art is dead!” and so forth. It appears more as a genre-shift, just as sampling other pieces of music, tiny unrecognizable fragments, paved the way for electronic music.

A new and pronounced emphasis on refining the skill of holding ideas in your mind with more vividness, and of establishing collaborative dialogue with machines.

While workflows rapidly shift, art is only becoming more accessible and faster, but raising monumental questions of ownership. Most of these networks are trained on infinite corpuses of visual art, some public domain but the majority of scrapings largely without the consent of artists.

Dall-E’s copyright rules have been cloudy during the research preview, you own the rights to any images you generate, to be used in any form other than NFTs. To handle the increases in processing load, it’s going from 10 generated images down to 4, and a system of paid credits. Midjourney’s own moody and artistic style may never compensate the source artists in any way either.

The democratization of generative networks will accelerate pre-existing shifts in how we learn: the lack of documentation around these technologies means that we learn primarily by building, and from each other. The instant community that forms over Discord, with incessant bursts of inspiration, moves us from proprietary-everything to an open-book approach of improving upon each other. Building collective knowledge. In a way, we’re recreating the spirit of the ‘90s internet - we’re all hanging out in forums and chatrooms making things together.

A brief history of GANs

When I first started working with GANs (generative adversarial networks) in 2016, I was primarily using them toward extrapolation. One thing that AI is optimized for is uncovering patterns: so surely it could conjure up the next possible concept, right at the outer edge of what already existed.

Training a model was a mercurial process spanning multiple days, leading to the moment of sheer magic when it would eventually spit out 64x64px rough images. These were the first blurry thoughts we could see, and resolution and precision have increased exponentially in recent years.

These years were spent searching for glimpses: predictions and odd sketches of something new yet plausible, discovering creatures that lived deep within latent space: what were the interstitial concepts hiding in the spider-like threads between existing ideas and images? From datasets assembled from scientific illustrations of plants, could we see traces of synthetic plants and future mutations? What would an even mix of Alexander McQueen and Oscar de la Renta’s aesthetics look like? What kind of creature might exist in between a jellyfish and a clock?

Jellyfish-clock: via Midjourney vs. 2018 Google’s BigGAN

Present-day models are faster and more vividly detailed, and lend themselves better to extrapolation of individual styles and the kinds of impossible collaborations I had always been looking for: blends of sculptures by Rodin and Noguchi, juxtaposing far future events into the past, alt-histories and scenes from far-flung universes. I input a description of the kind of person I tend to fall in love with, and Dall-E generated a number of images of men who looked like they played in Nickelback.

Inpainting and outpainting reveal what might lie beyond the limits of a frame: extending canvases to reveal container worlds. I spent the early days of Dall-E turning movie posters into tapestries, feeling unconstrained by edges, asking neural networks to give form to imaginary creatures that might be standing right behind me just out of frame in a photograph.

A few explorations:

• Switching formats (text to image to video) : Some literary paragraphs are each like individual beautiful paintings, and deserve to be repurposed into them. Some people consume information better when it’s visual rather than through written words

Illustrating a book of sci-fi short stories

• Stock images: For quick mockups (preferably ones where it doesn’t matter if the humans have demon-faces up close), I’ve been relying on Dall-E to generate all my stock photography

• Experimenting with unlikely materials

• Creating inspiration / patterns for fashion designs for an upcoming equestrian fashion line

• Creating inspiration images for hand-drawn ink illustrations and linoprint carvings

• Maintaining a more visual dream diary

• Generating textures for 3D models and AR objects

• Jewelry design: an opal ring I’m having made

Dreaming while awake

When you see visuals in a lucid dream, you will never be able to see the time - digital clocks tend to behave erratically. The same is true of neural networks: you can only see time as though in a dream, or text at the level of a timid scrawl.

Some of the first things I tried when I got access to these tools: generating a new set of hieroglyphic symbols for modern concepts (eg. In & Out burger), exploring what the color of human souls looked like (similar aesthetic to the Northern Lights). Given that any image may lie behind the right combination of words, there might be a way to even find yourself: What is the prompt that leads to your form - where do you exist in the eyes of a neural network?

Sometime past midnight, after losing my wallet an hour from home, I am rescued by an autonomous vehicle named Moonwalk. The night is very quiet and dark, and then an innocuous orange-doored white car caged in rooftop sensors casts its lightbeams down the street. It drives up alone, halting expectantly to pick me up at the highest point of Potrero Hill. As we turn onto the east-edge and drive almost vertically down three consecutive hairpin turns on a winding road, I become acutely aware of the absence of street lights, and of being completely alone. The wheel turns and keeps on turning, under the weight of an invisible hand, with a chillingly sharp assurance.

I’ve been beta-testing these Cruise vehicles for about a month now - and since they’ve recently expanded the service area, it’s becoming my main mode of transportation. Earlier, it would mostly be me and M driving down to Ocean Beach at 1am, because that’s the only place it would go. She’s working on a product that enables any car to self-drive - but these are the first autonomous vehicles publicly available, so the novelty is real.

I’d always thought the interior of an autonomous vehicle didn’t need to really look like a regular car - especially the interior. It’s almost disappointing to step into the same configuration of nondescript leather seats, nothing out of the ordinary - just a plastic barrier and a couple of iPads, and subtle indicators of cameras recording you all the time. The exterior is intentionally friendly and cute and personified, cloaking what some might perceive to be dangerous technology. Because it looks somewhat the same as what we’ve always known, it’s safer to step in.

Inside a supersonic aircraft, there is no need for windows.

Not in any commercial aircraft really, it does nothing for the structural integrity. You sit inside a long tapering carbon-fiber tube, and soon arrive somewhere else, in the wake of a sonic boom every so often.

A prototype aircraft like a looming whale skeleton occupies almost the entire office on the pier, a centerpiece built to scale from wood and foam. Redesigning the passenger experience is an opportunity to throw out everything you know, creating a temporary psychological environment from scratch. With a blank canvas, we trial potential realities through movable foamcore cabin setups and chair configurations and light projections and VR headsets. At the end of the day, we start with what people want, so the first thing is to give them windows.