Building the future of human–AI co-creation.
For twenty years, I have worked across computational creativity, music, attribution, and the economics of human–AI collaboration—building tools and systems that expand human agency and make contribution visible and valuable.
A single direction, expressed through different work.
-
2008
Research
Metacreation
Early systems and methods for computational creativity.
-
2014
Co-creation
Pyatt Hall
Machine-generated music performed by human musicians.
-
2018
Product
Spliqs
Generative music designed to augment rather than replace.
-
Today
Infrastructure
Musical AI
Attribution connecting contribution to credit and compensation.
Musical AI
The first rights management and attribution platform for generative AI. At Musical AI, we are building patent-pending technology that traces how training data influences AI-generated outputs, so creators get credited and paid.
- $4.5M
- Latest Raise
- 20M+
- Licensed tracks in catalog
- Patent Pending
- Model & modal agnostic attribution
Symphonic Distribution · Pro Sound Effects · SourceAudio · APM Music · Kanjian
Visit Musical AI →In the News
Selected coverage
Also Mentioned In: MixMag · MusicTech · Music Business Worldwide · Music Connection · Digital Music News · Musically
Human contribution requires attribution infrastructure.
When a human and a machine create value together, who is acknowledged, and who is paid?
Ideas emerging from the work.
The Three Waves of Zero
Ownership. Access. Generation. Each wave collapses the marginal value of the last — and the biggest obstacle ahead isn't technological. It's psychological.
Read →
A Logical Takedown of OpenAI's Proposals for the US AI Action Plan
Or: "A not-so-brief list of the unsurmountable pile of logical fallacies used in the arguments in favour of fair use for AI training"
Read →Reflections 1 & 2
Composition performed at the Pyatt Hall, Vancouver 2014.
An Early Framework for the Quantitative Evaluation of Generative AI Output
In 2013, I introduced a quantitative method for comparing generative output with human-authored corpora, bringing statistical analysis to model bias and creative variance.
Explore the research →I'm open to conversations about AI, attribution, music, leadership, conscious business, and creative technology.
Get in touch