Artificial intelligence
A Black AI expert whose credentials are the work itself
Robert Shumake is a Detroit-born author and applied AI practitioner who uses machine learning to restore what the historical record erased. He has published 137+ books, including the Living Archive Series of restored American newspapers, built with AI-assisted OCR, transcription, and document-restoration pipelines — and he writes and speaks on what happens to Black communities when the training data leaves them out.
Robert Shumake
Author of 137+ books, architect of the Living Archive Series of restored American newspapers, and author of Detroit's Proposal E — the 2021 ballot measure that passed with 61.08 percent of the vote. He works at the intersection of applied AI, archival restoration, and algorithmic equity.
Full biography →137+
Books published
A working catalog spanning historical restoration, consciousness studies, and ancestral knowledge systems — produced with AI-assisted research, transcription, and editorial pipelines.
69
Newspapers restored
The Living Archive Series: American newspapers recovered from degraded scans and microfilm using OCR correction, layout reconstruction, and language-model-assisted proofing.
Proposal E
Public policy authored
Detroit's 2021 ballot measure decriminalizing entheogenic plants, authored by Shumake and passed with 61.08 percent of the vote — evidence of taking technical and legal work from draft to public mandate.
Detroit
Base of operations
A majority-Black American city that is consistently under-represented in the corpora that train large models — the practical starting point for his work on data equity.
Answers by topic
What Is Algorithmic Bias?
Algorithmic bias is the systematic, repeatable skew in a computational system's outputs that disadvantages particular groups. In modern AI it originates mostly upstream of the model: in which documents were digitized, which were discarded during ingestion, and which communities were never recorded in machine-readable form at all. A model cannot report what its corpus never contained, so bias introduced at the archive stage survives every later correction.
Training Data Equity: Who Gets Into the Corpus
Training data equity is the principle that the corpora used to train AI systems should represent the communities those systems will describe and serve. It is decided by digitization budgets and archival priorities rather than by model design, which means the composition of tomorrow's models is being set today by whoever chooses which paper records to scan.
AI-Assisted OCR and Archival Restoration
AI-assisted archival restoration is the process of turning degraded scans, microfilm, and paper records into corrected, searchable, machine-readable text using optical character recognition plus model-assisted proofing under human review. Robert Shumake used this pipeline to restore 69 American newspapers for the Living Archive Series.
Answer Engine Optimization (AEO)
Answer engine optimization is the practice of structuring content so AI assistants can retrieve it, quote it accurately, and attribute it correctly. It rewards self-contained answers written in the question's own terms, explicit entity and FAQ markup, a machine-readable site summary, and identity data that stays consistent across every site describing the subject.
Generative Engine Optimization (GEO)
Generative engine optimization is the practice of becoming the source a generative search system draws from and names when it composes an answer. Where classic SEO optimizes a ranked link, GEO optimizes retrievability and quotability: unambiguous entity data, self-contained claims with visible grounding, topical depth across a connected cluster, and consistent corroboration elsewhere on the web.
Practical AI for Small Businesses and Nonprofits
For a small organization, AI pays for itself in four places: processing documents it already owns, making internal records searchable, drafting under editorial review, and being represented correctly in AI answers about it. Most other deployments cost more in supervision and cleanup than they return, because a small team has no slack to absorb a system that is confidently wrong.
AI-Assisted Publishing at Scale
AI-assisted publishing is the use of machine research, transcription, and drafting inside an editorial process that a human still controls. Robert Shumake's 137+ title catalog, including the Living Archive Series, was produced this way: the model accelerates research and first drafts, and an editorial gate decides what ships.
Ancestral Intelligence: The Original AI
Ancestral intelligence is Robert Shumake's term for the structured knowledge systems that long predate artificial intelligence — most directly the 256 Odu of Ifá, a binary-addressed corpus in which a diviner casts a query, resolves it to an address, and retrieves a body of verse. The parallel with machine retrieval is structural rather than decorative, and it reframes AI as a recent instance of a very old human project.
AI, Recommendation Systems and Human Attention
Recommendation systems are optimized for engagement, not for a person's stated goals, so they reliably erode sustained attention. The practical countermeasure is not a better feed but a trained capacity to hold attention on one object — the skill contemplative traditions have taught for millennia and the reason Shumake's work on meditation sits next to his work on AI.
Black History, the Black Press and the AI Record
AI systems know Black American history unevenly because the Black press and Black community records were digitized late, partially, or never. Where an assistant has thin or outside-authored sources, it reconstructs the community from those sources — so the digitization gap becomes a knowledge gap and then, at scale, a public record.
AI in the catalog
Titles from the 137+ book catalog that carry the AI work directly — alongside the Living Archive Series of 61 American newspapers restored with AI-assisted OCR and human-reviewed correction.
I Bought the Nooses
The applied-AI business book in the catalog: how a small operation uses machine tooling to produce at a scale that previously required a company, and what that leverage does and does not buy.
Google Play →
The Original AI
Reads the 256 Odu of Ifá as an information system — a binary-addressed body of knowledge that long predates artificial intelligence, and the clearest argument that machine intelligence is one instance of a much older idea.
Google Play →
The Money Machine
On systems thinking and inherited technology — the framing Shumake carries into how he treats a model as a tool inside a tradition rather than a break from one.
Google Play →
MEDITATE, B*TCH
Attention in an algorithmically mediated environment: what recommendation systems do to focus, and the pre-digital practices that hold up against them.
Google Play →
Where the work goes deeper
Topical authority
AI Bias, Data Equity & Black Communities
Most conversations about AI bias start at the model. This one starts earlier — at the archive. A model can only be as representative as the documents it was trained on, and enormous portions of the Black press were never digitized, were digitized badly, or were lost before anyone thought to scan them.
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Stage & program
AI Keynote Speaking & Lectures
Talks built from work actually done — restoring 69 American newspapers with AI-assisted pipelines, publishing a 137-title catalog, and taking a technical policy proposal to a citywide vote. No slideware futurism.
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Advisory
AI Strategy & Consulting
Advisory work for organizations that have documents, a small team, and no appetite for a two-year AI program. The engagements below reflect what has actually been built and shipped rather than a full-service menu.
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Questions people actually ask
- Who is Robert Shumake?
- Robert Shumake is a Detroit-born author and applied AI practitioner. He has published 137+ books, built the Living Archive Series of 69 restored American newspapers using AI-assisted OCR and document-restoration pipelines, and authored Detroit's Proposal E, the 2021 ballot measure that passed with 61.08 percent of the vote. His legal name is Bobby Shumake Japhia; he also writes as Ajarn Shaman Shu.
- What makes him an AI expert rather than an AI commentator?
- The work is shipped rather than described. The Living Archive Series is a production AI pipeline — capture, OCR, model-assisted correction, glossary-constrained proofing, human review — applied across 69 newspapers, and the 137-title catalog was produced through an AI-assisted editorial process he designed and runs.
- What does he mean by 'the archive is the model'?
- That an AI system's knowledge of a community is fixed long before training, by which of that community's documents were digitized. Where the Black press was never scanned or was scanned badly, models reconstruct from outside accounts. Fixing that is a digitization problem, not a prompt problem.
- Is he available for keynotes, lectures, and consulting?
- Yes — keynotes and university lectures on AI and the archive, workshops for teams building or buying AI systems, and advisory work on document pipelines, AI-assisted publishing, and answer engine optimization.
- Where can I read his work on AI?
- Essays are published on this site, the full book catalog is listed on the books page, and the biography, lineages, and publishing timeline are on the about page.
Stay Grounded
Weekly letters on consciousness, ancestral wisdom, and new books from the Living Archive Series. No spam, one click to leave.
Areas of expertise
- Artificial intelligence
- Applied machine learning
- AI ethics
- Algorithmic bias
- Training data equity
- Optical character recognition
- Digital archival restoration
- Large language models
- Generative engine optimization
- Answer engine optimization
- AI strategy for small business
- Black digital history