Humanoid in the Tower of Babel
Humanoide en la Torre de Babel: Importancia del Análisis Neuronal
Rafael Darío Amador Pérez · ISBN 978-9945302370 · Spanish · Dominican Republic
Title
Humanoide en la Torre de Babel
Subtitle
Importancia del Análisis Neuronal
Author
Rafael Darío Amador Pérez
ISBN
978-9945302370
Language
Spanish (original)
Publisher
Independent — Dominican Republic
Paperback
USD $19.97 on Amazon
Kindle
USD $9.97 on Amazon
Available
Worldwide via Amazon · Direct from author
Audience
University faculty, researchers, policy makers, graduate students
What Does Humanoide en la Torre de Babel Argue?
The book's central argument is that the mathematical neutrality of AI systems is the founding myth of the algorithmic age. Artificial neural networks do not eliminate human bias — they encode it, optimize it, and amplify it at a scale no human institution could reach. The term "artificial intelligence" is a misnomer that obscures this reality: these systems have no intelligence in any meaningful sense. They have pattern-matching capabilities of extraordinary scale, operating on patterns extracted from historical data that already contains the biases of the societies that generated it.
The book's title draws on the biblical Tower of Babel — the story of a unified project that collapsed because its participants could no longer understand each other. I use this metaphor to describe the state of AI development: we are building increasingly complex systems that make consequential decisions at scale, while the human operators nominally responsible for those decisions have increasingly limited understanding of how the decisions are made. Unlike the biblical Babel, where the problem was humans failing to understand each other, the digital Tower of Babel is humans failing to understand the systems they have built.
The book's response is not to slow AI development — it is to require that AI systems be independently audited before they are deployed to populations who will bear the consequences of their bias patterns. The three frameworks I propose (Neural Analysis, Computational Negligence Syndrome, and the Neurological Birth Certificate) are the institutional architecture for that requirement.
The Book's Core Scholarly Contributions
01
Neural Analysis
A pre-deployment diagnostic methodology for artificial neural networks. Neural Analysis treats AI deployment the way clinical medicine treats pharmaceutical approval: no system reaches operational scale without documented independent safety review. It applies saliency maps, TCAV concept activation vectors, and perturbation stress testing to detect hidden bias patterns in model hidden layers before deployment.
02
Computational Negligence Syndrome
The legal-ethical concept that deploying a high-impact AI system without independent pre-deployment bias audit constitutes deliberate assumption of foreseeable risk at the expense of third parties. This is not a technical accident — it is a civil liability exposure that existing law does not yet fully name but is moving toward enforcing. The syndrome is 'computational' because the risk is encoded in the system's mathematical structure; it is 'negligence' because the risk was foreseeable and the audit was omitted.
03
Neurological Birth Certificate
A proposed binding global certification: no artificial neural network may be deployed in high-impact contexts without review and clearance by an independent multidisciplinary commission of physicians, lawyers, neurologists, and sociologists. The commission has legal veto power. It has no financial relationship with the AI developer or operator. Unlike every existing audit regime — including NYC Local Law 144 and EU AI Act conformity assessment — this model eliminates the conflict of interest structurally.
For Scholars, Faculty, Policy Makers, and Practitioners
University Faculty
Suitable as a primary or supplementary text for AI ethics, technology law, philosophy of technology, algorithmic accountability, and Latin American studies with a technology focus. Particularly valuable for HSI faculty building Spanish-language AI ethics curricula.
AI Ethics Researchers
Engages the EU AI Act, UNESCO AI Ethics Recommendation, NIST AI RMF, and FDA §524B critically — not as summaries but as subjects of analysis. Introduces three frameworks absent from existing literature. Primary source for Caribbean and Latin American AI ethics scholarship.
Policy Makers
The Humanoide Framework and Neurological Birth Certificate model are specified with sufficient operational detail to serve as legislative proposals. The book documents the structural failure modes of existing regulation with sufficient specificity to inform reform proposals.
Technology and Law Practitioners
The Computational Negligence Syndrome framework maps to existing civil liability structures in ways that inform legal practice for both developers and organizations deploying AI systems. The three-phase audit methodology is implementable by qualified technical teams.
From the Author
I wrote this book because I identified a gap that the AI ethics literature had not addressed: there was no Spanish-language scholarly work that engaged with AI governance from a Caribbean and Latin American intellectual perspective, proposed operationally specific audit frameworks rather than principles, and named the structural failure modes of existing regulation with sufficient precision to ground reform proposals. I do not know if this book fills that gap adequately. I know that the gap is real, that it has consequences for millions of people in the Dominican Republic and the broader region, and that someone from within the region needed to attempt it.
— Rafael Darío Amador Pérez, Azua / Santo Domingo, Dominican Republic
About the Book
What is Humanoide en la Torre de Babel about?
Humanoide en la Torre de Babel is a scholarly work on AI ethics, algorithmic bias auditing, and human-AI communication by Dominican writer and researcher Rafael Darío Amador Pérez. It proposes three original frameworks: Neural Analysis (a pre-deployment diagnostic methodology for artificial neural networks), Computational Negligence Syndrome (the legal-ethical concept that deploying AI without independent audit constitutes deliberate assumption of foreseeable risk), and the Neurological Birth Certificate (a binding global certification model requiring independent multidisciplinary commission review before any high-impact AI system may be deployed). The book engages critically with the EU AI Act, UNESCO AI Ethics Recommendation, NIST AI Risk Management Framework, and FDA §524B.
Is this book available in English?
Humanoide en la Torre de Babel is currently available in Spanish, which is by design: the book addresses the documented gap in Spanish-language academic literature on AI ethics. An English edition is under consideration. The book engages English-language frameworks (EU AI Act, NIST RMF, FDA §524B) throughout its text, making it accessible to bilingual readers and usable in bilingual course settings. Faculty at US Hispanic-Serving Institutions can contact the author for exam copies and bilingual course integration support.
What is the Humanoide Framework and how does it work?
The Humanoide Framework is the three-phase mandatory pre-deployment audit methodology proposed in the book. Phase 1 audits the AI system's training data for historical bias embedded at the intake stage — examining representativeness, labeling bias, and demographic sampling disparity. Phase 2 scans the algorithm's black box using interpretability techniques including saliency maps, concept activation vectors (TCAV), and perturbation stress tests to identify hidden discriminatory correlations in hidden layers. Phase 3 simulates the real-world social impact of the system before it reaches populations. The result is either an Ethical Certification (deployment authorized) or a Legal Veto (deployment prohibited pending remediation). The framework requires that the auditing body have no financial relationship with the AI developer or deployer.
Why did Rafael Darío Amador Pérez write this book from the Dominican Republic?
Rafael Darío Amador Pérez wrote this book from the Dominican Republic because the Caribbean and Latin American perspective is structurally absent from the global AI ethics literature. AI systems trained primarily on North American and European data, governed by frameworks designed for OECD institutional contexts, and deployed to populations in the Caribbean and Latin America without regional scholarly input represent a governance gap with direct consequences for millions of people. The book argues that this absence is not incidental — it reflects the same power asymmetries that AI governance is supposed to address. Writing from within the Dominican Republic, rather than about it from outside, is itself a methodological commitment.
What makes this book different from other AI ethics texts?
Three things distinguish this book from the existing AI ethics literature. First, it proposes operationally specific frameworks — not principles or guidelines but audit methodologies specific enough to be enacted as legislation and implemented by technical commissions. Second, it provides a sustained critique of existing frameworks (EU AI Act, NYC Local Law 144, NIST RMF, UNESCO Recommendation) as normative simulations — showing specifically how each falls short and what it would need to do to constitute genuine accountability. Third, it introduces the legal concept of Computational Negligence Syndrome — the argument that deploying a high-impact AI system without independent pre-deployment audit constitutes deliberate assumption of foreseeable risk, with civil liability implications that existing law does not yet fully specify but is moving toward.
Get the Book
Available worldwide on Amazon in paperback and Kindle format. For institutional bulk orders, exam copies, and course adoption support, contact the author directly.
También disponible en español: Ver página del libro en español