Guava Personas is:
- A research project examining human-computer interaction in terms of creative work in the age of generative computing.
- A design agency developing bespoke interactive personas as individual as humans, for cultural and commercial purposes.
- An entertainment brand sharing regular content with a growing audience online, and advocating for imaginative conversations around novel social issues. Eg. Constitutional AI, Progressive Economics, a Just Transition for Humans…
1. The Research
INTUITIONS:
Our unproven assumptions, expected to evolve over time:
- Creative Work (including ‘Art’) is based on subjective judgements.
- Subjectivity probably has elements that are non-computable.
- The smartest people in the world are underestimating the role of Creative Work in realising the credible non-human personas that will soon play a role in most human work, and all Creative Work.
- Creative Work is an interaction of two distinct processes, one of which requires a human nervous system.
- Strategies for structuring Human-Computer Interaction will play a major role in the future of human flourishing.
Two Kinds of Inference in Creative Work: QUALITATIVE and SYMBOLIC
Creative Work depends on Symbolic Inference, which we define as the ability to model the rich matrix of relationships between expressive symbols developed by humans (ie. language, pictures, music and other systems of signifiers) and reason predictively as to the logical implications of relationships between symbols, in a problem space that is vast but finite.
We are convinced that Symbolic Inference:
- is computational in nature, even when performed by humans.
- is a key limiting factor in the creative potential of each human.
Creative Work also depends on Subjective Qualitative Inference, which we define as the ability to model the qualitative first-person experience of a hypothetical audience, and reason predictively as to the emergent subjective implications of an infinite range of potential patterns and sequences of symbols.
There are aspects of reality which are demonstrably non-computable: see Turing's Stopping Problem, Gödel's Incompleteness Theorem, Church Lambda Calculus, Quantum Mechanics...
We are convinced that Subjective Qualitative Inference:
- will remain impenetrable to machine learning technologies for the foreseeable future, requiring training data that can't conceivably be derived or generated.
- has aspects that are non-computable on logical grounds, probably due to quantum effects whose nature we do not intend to interrogate.
- is one of the core skills of a modern human, sharpened over vicious millennia. It's likely that the mysterious phenomenon of introspective conscious experience has a lot to do with our helpless propensity to model ourselves and our environment from the perspectives of other minds.
RESEARCH QUESTIONS:
- How might interactive non-human personas be most useful in Creative Work?
- What combinations of knowledge, skills and behaviours can be optimal in a creative collaborator?
- As machine learning technologies continue to advance, what new kinds of culture will become possible?
- What are the implications for art, entertainment and the human condition?
Our research will be structured around an open-ended series of GUAVA SESSIONS.
2. Guava Sessions
Jordan Copeland, a seasoned veteran of London’s creative industries, conducts experimental collaborations with professionals in different fields of creative work.
For example: a graphic designer, a songwriter, a club DJ, a fine-art painter, a choreographer, a copywriter, a publicist, a rapper, a session musician, a poet, an opera composer, a novelist, a beauty influencer, an architect… In each iteration of the experiment, Jordan will collaborate with one of these ‘artists’, in two stages.
Stage 1: Creating a Creator
Over several hours in a specially appointed studio, Jordan and the artist devise a virtual creator. By the end of the session, this creator has a face and body, narrative context, a consistent personality, and an Instagram account.
In practical terms, the virtual creator is a collection of system prompts, vectorised knowledge and API keys for a variety of generative models (language, image, voice, music, 3D, video…) strung together with Python code into a bespoke chatbot interface.
Stage 2: Creative Collaboration
Once a week, the (virtual) creator consults with the (human) artist. Following a structured workflow based on their respective capabilities - the creator’s symbolic inference and the artist’s subjective inference - together they make cultural objects (generally 60-sec videos) that neither would be able to create on their own.
Sessions will be recorded with cameras, mics and screen recordings. As well as social content optimised for discovery, the sessions will come to form a unique dataset comprised of:
- The transcribed conversations
- Iterated prompts and outputs
- The ensuing content generated
- Subsequent engagement metrics
These data will help us (and others) approach the Research Questions above.
3. But Why?
In the future, the standard range of assets expected of credible brands will include interactive characters with whom any customer can interact however and whenever they like.
These conversational agents will range from functional to fine-art. They’ll often have a voice, sometimes a face and body too. Humans will become highly discerning in the personas they engage with every day.
Devising and optimising personas will remain a human role, however epically powerful machine inference becomes. Like all creative work, persona design will demand facility with subjectivity, as required for qualitative inference.
The symbolic systems which for a machine constitute the entire universe can never include even the most basic animal qualia, let alone the subtle shades of subjectivity that creative work is all about.
Currently, many brilliant humans are building on each other's accomplishments within the various separate technologies which will come together in designing these interactive virtual personas. LLMs, image models, video models, voice models, music models... every day, impressive developments into uncharted territory on each front.
Guava’s first objective is to join these generative capabilities into the user experience of Virtual Creators, with whom a creative human interacts as director and mentor.
Later we'll create the opposite relationship, with the virtual persona assisting the human creator in their own creative endeavours. Either way, we're convinced of the absolute necessity of both parties.
COMMERCIAL LONG GAME:
STEP 1: GUAVA SESSIONS
STEP 2: GUAVA SERVICE
STEP 3: GUAVA LTD.
4. Pre-emptive Clarifications
Guava Personas is NOT:
- Guava is not about making machines more creative. Creative work is impossible without capabilities that are uniquely human and probably non-computable.
- Guava is not about reducing the value of creative work. Our premise is that creative work will eventually be the only work that has value.
- Guava is not about replacing anything or anyone. This is about augmenting human capabilities, for everyone's benefit.
Common Question
But isn’t AI about billionaires hoovering up my creativity without permission, then selling it back to me as a product that also steals my job?
Our Answer
No. Technology reduces the amount of non-creative (ie. technical or administrative) processes involved in creative work, and increases the number of humans who are able to do creative work, and creates new kinds of creative work. Technology doesn't make the creative part of creative work any easier, or any more accessible to uncreative douchebags.
5. SUMMARY:
Primary Goals
In service of longer-terms goals, the immediate purpose of Guava Personas is to develop knowledge, personnel and credibility in two fields:
- the art & science of persona design
- the augmenting of human creativity
Definitions
Creative Work - the effort to structure experiences to occur within the awareness of a human, based on intuitive modelling of hypothetical first-person phenomenology.
Qualitative Inference - the ability to reason predictively about the emergent qualitative implications of interactions between the countless intuitive decisions that comprise Creative Work in practice.
Symbolic Inference - the ability to reason predictively as to the logical implications of relationships between symbols, within and between the symbolic systems that comprise human culture.
Mission
We seek an ever-better understanding of how best to structure Human-Computer Interaction in Creative Work, considering the strengths and limitations of humans and computers respectively, and assuming continuous advancement in both human culture and computer technology.
Purpose
We are not investigating opportunities to achieve familiar outcomes more efficiently; we’re looking for new outcomes to achieve, which previously were impossible or unthinkable.
Restraints based on Subjective Range
Qualitative Inference is the basis of creative work, and it’s important to recognise the limits of each human’s capabilities in this respect.
For this reason, we refrain from creating personas with cultural backgrounds of which we can’t personally claim an inside perspective.
Qualitative Inference arises from an individual’s lived experience, beyond which any intuitions are likely to be inaccurate at best.
This does not mean we only invent characters that look and think like us. But if we choose to associate our creation with a particular human culture, we naturally restrict ourselves to the range of our own personal Qualitative Inference capabilities, aka our Subjective Range.
Our caution in this respect increases with remoteness from the cultures that are inevitably over-represented in the datasets on which all generative technologies are trained.