Essays on Meliorism 2.0, the human advantage in an AI economy, and the practice of seeing clearly.
My daughter is graduating from college this spring with a degree in music therapy. In the next ten years, an AI will be trained on her body of work. Without asking her. Without paying her.
Read on Substack →Meditations on Meliorism — Essays on the philosophy: what Meliorism 2.0 is, what subtraction requires, the human advantage in an AI era. Published when there's something worth saying.
No paywall.
Brian Oney is a business advisor and the developer of Meliorism 2.0 who writes about the human advantage in an AI economy. He publishes Meditations on Meliorism on Substack — essays on the philosophy, what subtraction requires, and the human advantage in an AI era.
Meditations on Meliorism is Brian Oney's Substack publication for essays on the philosophy of Meliorism 2.0 — what it is, what subtraction requires, the human advantage in an AI era, and the patterns he notices in advisory work.
It is published when there is something worth saying, not on a schedule. Read it on Substack →
"A Pension for the Trained-On" is an essay by Brian Oney about AI training data and the people whose work gets absorbed into models without consent or compensation. It opens: "My daughter is graduating from college this spring with a degree in music therapy. In the next ten years, an AI will be trained on her body of work. Without asking her. Without paying her."
The piece argues for compensating the human creators whose labor trains AI systems. Read it →
The Meliorism 2.0 briefing is daily and practical — oriented to what trainers, coaches, and educators need to know right now about AI and their field.
Brian Oney's Substack essays are slower and more philosophical — concerned with the deeper questions about Meliorism 2.0, human agency, and what the AI era means for the irreplaceable parts of human work. Same body of thought, two different speeds.
Brian Oney writes about Meliorism 2.0, human agency, the ethics of AI training data, and the parts of human practice that machines cannot replicate.
The recurring premise across his work: the better version is already present, and the work is clearing what conceals it — in people, in businesses, and in the way we adopt new technology.