How Artificial Intelligence Is Used, Governed, and Labeled on basilpuglisi.com
This AI ethics disclosure explains how basilpuglisi.com and its associated materials are created under the HAIA ecosystem (Human Artificial Intelligence Assistant), a set of methods that defines how people and artificial intelligence work together with transparency, accountability, and documented human authority. Checkpoint-Based Governance supplies the constitutional layer, and Factics supplies the evidence discipline beneath it. This page is part of Basil C. Puglisi’s AI Ethics work, and the practices it records form the Ethical AI layer of everything published on this site.
All content published here is developed by Basil C. Puglisi for research, education, experimentation, and professional development. Every post, publication, image, video, audio episode, and dataset passes human review before release, and citations are maintained so readers can see how information was sourced, analyzed, and shared. This page covers disclosure, labeling, and legal terms. The technology and the governance position are explained on Artificial Intelligence: Technology, Capability, Governance, and Human Accountability, and the operating methods live on the HAIA ecosystem page.
AI Ethics and Authorship Disclosure
Work on this site is created through a governed human-AI collaboration consistent with WIPO and U.S. Copyright Office guidance. Human intent directs the purpose, judgment, and editorial control of every piece, while AI functions as an instrument under structured oversight.
“I might not be the one controlling the pen that hits the paper, but I am the reason it does, and it moves at my direction. To claim the handwriting is not mine is a failure of intellect.” (Basil C. Puglisi, MPA)
AI Ethics: The Ethical AI Layer
Three terms are routinely treated as one, and this site separates them because each answers a different question. Ethical AI answers: Should this be done? Responsible AI answers: Who answers when this fails? AI Governance answers: Who decides, by what authority, at what checkpoint?
This page sits in the first of those layers. It is part of Basil C. Puglisi’s AI Ethics work, and the practices it records are the Ethical AI layer: the values, norms, and moral reasoning that shape how artificial intelligence is used on this site. Disclosure of every platform and tool, honest labels on every piece of content, safeguards around simulated opinions of real people, and open terms for reuse all answer the question of whether something should be done, and how it should be done in the open.
Ethics sets direction, and on its own it does not establish authority, which is why this layer does not stand alone. The checks that test the work and the human authority that decides what is published sit in the layers above it. On this site, AI Governance exists as the site defines it: AI Governance exists when a qualified human holds binding authority at specific checkpoints, with personal accountability for the outputs that pass through. Accountability reaches that person through four channels, which are moral, professional, civil, and criminal. Under Checkpoint-Based Governance, no AI system approves another AI system’s work, and publication decisions rest with a named human. The full comparison of the three terms appears on the Artificial Intelligence page, and the full governance argument appears in Governing AI: When Capability Exceeds Control.
AI Platforms Under Governance
The platforms below support work across this site, and each one falls under the same AI ethics commitments described on this page. Each operates inside HAIA-RECCLIN roles and HAIA-CAIPR parallel review, where human arbitration remains the governing force behind every decision and output. Roles are assigned by task rather than by platform identity, and no platform holds a permanent primary position.
Conversational and Reasoning Models
The confirmed pool stands at fifteen models across thirteen platforms. Eleven platforms run one model each, and two run two models each, which is why the model count exceeds the platform count. A given review draws a configuration from this pool rather than dispatching to every platform at once.
Claude (Anthropic): Long-context reasoning, governance alignment, and complex report review
ChatGPT (OpenAI): Research synthesis, editorial refinement, and data analysis
Perplexity: Source-grounded research with direct citations and real-time verification, running Sonar and Nemotron 3 Super from Nvidia
Grok (xAI): Skeptical reasoning, alternative perspectives, and real-time analysis
Gemini (Google DeepMind): Multimodal reasoning and structured automation
DeepSeek: Technical analysis, code review, and adversarial testing
Le Chat (Mistral AI): Multilingual reasoning, governance testing, and audit workflows
Copilot (Microsoft): Workplace integration and document analysis
Meta AI: Broad-access reasoning and cross-platform validation
Kimi (Moonshot AI): Long-context processing and documented dissent production
MiniMax: Post-release adversarial code review and independent validation
Qwen (Alibaba Cloud): Independent architecture accessed directly at qwen.ai
PublicAI: Public-access platform running Apertus, the Swiss public model from the Swiss AI Initiative, and Qwen-SEA-LION-v4 from AI Singapore, which keeps its own sovereign identity even though its base derives from Qwen
Creative and Production Tools
ChatGPT Images (OpenAI): Featured images and diagrams generated inside ChatGPT
Gemini Notebook, formerly NotebookLM (Google): Cinematic video, deep dive audio for The Other AI podcast, and infographics built from finished papers under HAIA-MOON
ElevenLabs: Audio and voice synthesis
Grammarly: Grammar, clarity, and style refinement
Canva: Visual design and layout production
Adobe Express: Visual design and layout production
These production tools support specific creative and technical functions, and they do not receive RECCLIN role assignments.
Project-Based Visual and Video Tools
Midjourney: Artistic and stylized visual generation
Veo through Google Flow (Google DeepMind): Cinematic video generation
Previously Used Tools
DALL-E 3 (OpenAI) produced featured images and diagrams on this site until OpenAI retired it in 2026. Sora (OpenAI) supported text-to-video work until OpenAI discontinued it in 2026. Media created with either tool stands as published.
Emerging Tools and Expanding Uses
The roster changes as practice changes. Platforms enter the pool after sustained use, and they leave it when access ends or when documented fitness findings show they cannot be trusted for a given operation. HAIA-CAIPR treats that record as a public warning about platform fitness rather than a private note, so a platform that fabricates sources or identifiers in review is documented before its role is reconsidered. New tools, new models inside existing platforms, and new uses for familiar tools are added here as they become part of regular practice. Redundant structure keeps governance continuous when any single platform faces access limits, pricing changes, or retirement.
Third-Party Trademarks and Logos
All third-party trademarks, logos, and brand names referenced on this website belong to their respective owners. Their use here is for identification and illustration only, and it does not imply affiliation, partnership, sponsorship, or endorsement by or with any company or organization mentioned.
Platform and product names including but not limited to Claude (Anthropic); ChatGPT, ChatGPT Images, DALL-E, and Sora (OpenAI); Gemini, Gemini Notebook, NotebookLM, Google Flow, and Veo (Google); Grok (xAI); Perplexity and Sonar; Nemotron (Nvidia); Mistral AI and Le Chat; Copilot (Microsoft); Meta AI; DeepSeek; Kimi (Moonshot AI); MiniMax; Qwen (Alibaba Cloud); PublicAI; Apertus (Swiss AI Initiative); SEA-LION (AI Singapore); Grammarly; Canva; Adobe Express; ElevenLabs; and Midjourney are trademarks of their respective owners. Basil C. Puglisi and basilpuglisi.com operate independently and are not affiliated with, endorsed by, or sponsored by any AI platform provider referenced on this site.
Logos displayed in featured images carry the same disclaimer printed directly on the image: “All third party trademarks and logos shown are the property of their respective owners. Third party logos and trademarks here are for identification and illustrative purposes only and do not imply affiliation, partnership, sponsorship, or endorsement.”
Simulated Opinions and AI Thought Leader Analysis
Certain research on this platform includes AI-generated analysis of how named public figures in AI research, ethics, policy, and industry would likely respond to specific frameworks, arguments, or proposals. The method first appeared in Case Study 001 (Thought Leader Engagement) and related HEQ publications. Its largest use is The Minds That Bend the Machine, which applies simulated critiques to each profiled figure, to the governance voices beyond the original selection grid, and to the AI industrialists whose influence runs through ownership of the technology stack.
These simulated perspectives are produced by prompting AI platforms to analyze how individuals would likely respond based on their publicly documented positions, published research, recorded statements, and known areas of focus. Each publication that uses the method discloses it where it appears, which is the AI ethics standard applied to every named individual.
Critical Distinctions:
These are not endorsements. No individual named in any simulated opinion analysis has endorsed, reviewed, approved, or been consulted about the frameworks discussed on this platform unless explicitly stated otherwise.
These are not quotes. No words attributed to named individuals through simulated analysis represent actual statements made by those individuals, and every simulated response is labeled as AI-generated interpretive analysis. Direct quotations of a person’s published words are cited to their source and kept separate from simulated analysis.
These are not affiliations. Reference to a public figure’s known positions does not imply any professional, academic, or personal relationship between that individual and Basil C. Puglisi or any framework documented on this platform.
The purpose is analytical, not promotional. Simulated opinion analysis tests frameworks against the strongest available critiques by modeling how leading experts would likely challenge, question, or validate specific claims. The method surfaces blind spots and strengthens governance architecture through adversarial reasoning, and it does not use the names or reputations of public figures to market, endorse, or promote any product or service.
Individuals referenced in published and forthcoming research include but are not limited to: Geoffrey Hinton, Yoshua Bengio, Andrew Ng, Fei-Fei Li, Demis Hassabis, Timnit Gebru, Joy Buolamwini, Kate Crawford, Meredith Whittaker, Lina Khan, Daron Acemoglu, Erik Brynjolfsson, Helen Toner, Jessica Newman, Stuart Russell, Nick Bostrom, Eliezer Yudkowsky, Ray Kurzweil, Yuval Noah Harari, Dario Amodei, Carter Cousineau, Navrina Singh, Sneha Revanur, Yann LeCun, Renata Ávila, Nanjira Sambuli, Nathan Lambert, Sasha Luccioni, Yoel Roth, Monika Bickert, Yi Zeng, Elon Musk, Jensen Huang, Satya Nadella, Sam Altman, Mark Zuckerberg, Gary Marcus, Rumman Chowdhury, Allie Miller, Ethan Mollick, Sundar Pichai, and Arvind Krishna. Each is referenced solely in their capacity as a public figure with documented public positions on AI research, ethics, governance, policy, or industry.
Any individual referenced in simulated analysis who objects to their inclusion may contact the author directly at me@basilpuglisi.com for review and resolution.
AI Ethics in Content Labeling and Classification
Under this AI ethics policy, labels on this site tell a reader which layer of the work a piece belongs to. Every label involves human judgment, and each serves a different purpose.
#AIassisted: Human-Led Work
Content, blogs, and papers authored by Basil C. Puglisi carry the #AIassisted mark. In this work, the human voice and strategic judgment lead, while AI platforms support research, sourcing, drafting, review, and refinement under HAIA-RECCLIN roles and HAIA-CAIPR parallel review. Sources are selected and verified by the author before a piece is built, and Factics links every significant fact to a tactic and a measurable outcome. Human-led papers close with the full mark and license statement, “#AIassisted using the HAIA Ecosystem | CC BY-NC-SA 4.0,” so a reader always knows both how the work was made and how it may be reused. Images carry @BasilPuglisi attribution with #AIassisted using the HAIA Ecosystem in the accompanying text.
#AIgenerated: Building Blocks by AI
The Building Blocks by AI category holds AI-generated content that serves as raw material for human-led papers. The category has run since its first post on January 1, 2023, when it began as Factics applied through ChatGPT for the answer and Perplexity for source verification. Human prompts guide the platforms, and outputs are reviewed for clarity and accuracy before posting, but the AI produced the primary draft. The category separates that raw material from the human-led work that draws on it, so a reader can see which layer a piece belongs to. Posts already in the category stand as written, and visuals created before the current mark carry the #AIgenerated watermark under which they were made.
Building Blocks by AI supplies the what, and the human-led work supplies the so what.
Social Posts and Comments
Social posts follow the HAIA-SMART standard for platform content. Comments left on other people’s posts carry no tag, because a comment is conversation rather than published work.
Human-Only Work
Some work on this site is written without AI drafting, research, or review. AI involvement in that work stops at the automation built into ordinary tools, such as spellcheck, formatting, and platform defaults, which no reader would consider a contribution to the thinking. The label exists for honesty rather than purity, since the same tools that correct a typo run on forms of artificial intelligence, and pretending otherwise would contradict everything else on this page. Human-only work is the baseline against which the other labels read, showing what the author produces alone and what changes when governed collaboration enters the process.
The Principle
In practice, nearly all digital work is AI-assisted. Modern search engines, grammar checkers, recommendation engines, and analytics systems all use forms of artificial intelligence to extend human capability. The difference lies not in whether AI was used, but in how transparently its influence is disclosed.
A Universal AI Perspective
For this platform, AI is not a tool but an environment. It shapes research, structure, formatting, and feedback loops across every creative, analytical, and strategic process. From the first spellchecker to today’s large language models, artificial intelligence has long been part of human cognitive expansion.
Every system in use, from search engines to grammar tools to data dashboards, represents an invisible layer of augmentation. Recognizing that condition is essential to building transparent governance, and the purpose of the HAIA ecosystem is to make the relationship visible, auditable, and accountable so human judgment remains at the center.
“Everything we create in the digital age is AI-assisted in some form. The difference is not whether we use AI, but whether we disclose how.” (Basil C. Puglisi)
Ethics of AI White Paper
The site’s Ethics of AI White Paper details the principles that first guided the governance and collaboration systems developed by Basil C. Puglisi. It covers ethical boundaries, bias mitigation, transparency, and human oversight as they were integrated into the early HAIA-RECCLIN methodology.
The governance methodology that followed is documented in Governing AI: When Capability Exceeds Control, published November 2025 and ranked #1 in Ethics on Amazon. The white paper remains a foundational reference, while the book and the framework pages carry the current standard. Key AI ethics principles include accountability through logged decision trails and structured dissent, human authority over automated processes, source custody and multi-AI verification, and Factics, which links every fact to an actionable tactic and a measurable KPI.
Download the Ethics of AI White Paper
Evolution of Basil C. Puglisi’s Intelligence and Governance Frameworks (2009 to 2026)
The Factics Intelligence Dashboard and the Growth OS rows record the historical path that led to the Human Enhancement Quotient and the Augmented Intelligence Score, which carry that measurement work forward.
| Phase | Date | Purpose | Key Outputs |
|---|---|---|---|
| WordPress Era | 2009 to 2010 | Launch of first digital media blogs; adoption of academic sourcing (APA) | Established the verifiable content principle and the foundation for Factics |
| Factics Stated Publicly | Oct 2012 | First public statement of the Facts and Tactics model | Presented on stage at SMAC (Social Media Action Camp), NYXPO, Javits Center, under the Teachers NOT Speakers philosophy |
| Factics in Print | Nov 2012 | Formalized Facts and Tactics for measurable action | Digital Factics: Twitter published on MagCloud (60 pages); consulting system for marketing, SEO, and content strategy |
| Factics Applied to AI | 2022 | First application of Factics to AI output | Facts and tactics returned by AI, but sources were unverifiable, so no KPI could attach |
| Two-Platform Verification Loop | 2023 | Complete the Factics chain inside AI work | ChatGPT for the answer and Perplexity for source verification; Building Blocks by AI begins January 1, 2023 |
| Intelligence Enhancement Thesis | Feb 2024 | Declare that Factics increases applied human intelligence as a testable position | Public article on basilpuglisi.com describing the method in established AI practice |
| FID, Factics Intelligence Dashboard (historical) | 2024 | Operationalize the intelligence thesis into measurable domains | Six-domain radar: Verbal, Analytical, Creative, Strategic, Emotional, Adaptive Learning; precursor to HEQ |
| 5-AI Blog Model | 2025 Q2 to Q3 | Expand multi-AI collaboration to five platforms | Systematic workflows across ChatGPT, Grok, Gemini, Claude, and Perplexity; checkpoint practice formalized |
| Growth OS (historical) | Aug 2025 | Integrate Factics, HAIA, FID, and RECCLIN into one operating model | Input, processing, and output layers; superseded by HEQ/AIS measurement |
| HAIA-RECCLIN Published | Sept 2025 | Formalize multi-AI collaboration with named roles | Seven roles defined: Researcher, Editor, Coder, Calculator, Liaison, Ideator, Navigator |
| HEQ, Human Enhancement Quotient | Sept 2025 | Establish a quantitative standard for human-AI collaboration measurement | Case Study 001: 0.96 ICC across five platforms; HEQ baseline established (89 to 94 range) |
| Checkpoint-Based Governance Public Record | Sept 23, 2025 | Place checkpoint governance on the public record | First public artifact of Checkpoint-Based Governance |
| Governing AI: When Capability Exceeds Control | Nov 2025 | Publish the governance methodology | 204-page book; #1 Ethics on Amazon; 96% checkpoint utilization; 26 dissents preserved |
| Digital Factics X | Dec 2025 | Apply Factics to X platform growth | Second book in the Digital Factics series |
| EOY 2025 Audit | Dec 2025 | Validate HEQ across an expanded platform set | AIS 91.8 across nine platforms; human override of an AI majority documented |
| HACI / AIS, Measuring Augmented Intelligence | Feb 2026 | Establish a measurement science discipline and standardized scoring | Working paper; HACI defined as a discipline; AIS defined as a standardized composite |
| GOPEL, Governance Orchestrator Policy Enforcement Layer | Feb 2026 | Build working governance infrastructure code | v0.6.1 reference implementation; seven-platform adversarial review; public repository |
| AI Provider Plurality Congressional Package | Feb 2026 | Propose AI governance as federal infrastructure | Four documents: one-pager, policy brief, legislative framework, technical appendix |
| Agent Architecture, EU Compliance Edition | Feb 2026 | Specify a non-cognitive agent for audit-grade multi-AI collaboration | Academic working paper; EU AI Act compliance mapping; three operating models |
| HAIA-CAIPR Named | Mar 2026 | Name and specify parallel multi-AI review | Case Study 006: The Discovery of CAIPR |
| Checkpoint-Based Governance as Constitution | Mar 2026 | Elevate CBG from decision loop to constitutional framework | Four constitutional properties; human in the loop distinguished from human authority |
| RECCLIN Reasoning and Dispatch | Mar 2026 | Separate how each AI reasons from how work is assigned | HAIA-RECCLIN split into two capabilities within one framework |
| Governing AI: Revised Edition | Apr 2026 | Rebuild the book’s prose | Full prose rebuild following the Kirkus Reviews critique of the first edition |
| HAIA-CARCS Published | Apr 2026 | Govern the documentation of completed work | Compliance Accountability Record and Case Study; ten-section governed record |
| HEQ/AIS Scoring Rubric | Apr 2026 | Anchor scoring in observable behavior | Behavioral anchor rubric synthesized from Case Study 008; SSRN paper Bridging the Measurement Gap in Augmented Intelligence |
| Five Conditions of Sentient Life and AI | Apr 2026 | Examine morally significant sentient life | Cross-disciplinary working paper with nine-platform peer review |
| The AI Risk Economy | May 2026 | Document insurance as a governance enforcement channel | SSRN working paper; five-tier insurance maturity model |
| The Tale of Two AIs: Artificial and Augmented | May 2026 | Name the replacement and augmentation architectures | Research paper built from twelve-platform parallel research |
| HAIA-SCOPE | Jun 2026 | Govern source custody for published work | Source Custody Observable Publication Evidence, published on basilpuglisi.com |
| Platform Pool Expansion | Jun 2026 | Widen architectural and national independence | Pool reaches fifteen models across thirteen platforms with Apertus, Qwen, Qwen-SEA-LION-v4, and Nemotron 3 Super |
| HAIA-CAIPR Fourth Edition | Sept 11, 2026 | Deposit the full parallel review framework | Nine invariants, five configuration variables, and platform fitness as a public warning; deposited to Zenodo, SSRN, and Academia.edu |
| Framework Feature Pages | Sept 13, 2026 | Give each framework a canonical home | Live pages for Factics, HAIA-RECCLIN, HAIA-CAIPR, Checkpoint-Based Governance, and HEQ/AIS |
| HEQ/AIS as AI Literacy | Sept 13, 2026 | Frame measurement as governance competence | Measuring the Governance Competence at the Center of AI Literacy |
| Content Tool Rebuilds | Sept 14, 2026 | Publish content tools as paper and tool | HAIA-CORE, HAIA-WOPPA, and HAIA-MOON rebuilt with public explainers |
| The Minds That Bend the Machine | Sept 2026 | Map the minds shaping AI and test the frameworks against them | Content master with twenty-four profiled minds, Looking Beyond WEIRD, and the coda The AI Industrialist; in print production |
| Open License Mark | Sept 15, 2026 | Standardize reuse terms across content, blogs, and papers | #AIassisted using the HAIA Ecosystem with CC BY-NC-SA 4.0 |
AI Ethics, Legal, and Reuse Statement
Representation: All views expressed on this website are personal opinions and interpretations. They do not represent the position of any organization, client, or affiliate unless explicitly stated.
Data and Sources: Every reasonable effort is made to cite credible, verifiable sources. The author is not responsible for the accuracy or future availability of third-party data, research, or case studies referenced here.
Open-Source Materials: When open or public resources are used, attribution is provided wherever possible. Concerns regarding any citation or material may be directed to the author for review.
No Warranty: All information is provided as is, without guarantee of accuracy, completeness, or timeliness. Readers should verify data independently before acting on it.
No Professional Advice: Nothing on this site constitutes legal, financial, or professional advice.
License and Reuse: Original content, blogs, and papers on this site are released under CC BY-NC-SA 4.0. They are free for personal, educational, and noncommercial research use with attribution. Commercial exploitation, paid productization, and enterprise commercialization require separate permission and licensing.
Additional Notice
Content is provided for educational and informational purposes. All research and commentary remain under ongoing review as AI systems evolve, and readers are encouraged to treat every output as a snapshot in time, representing both human reasoning and the frontier of AI collaboration at that moment. Any change to disclosure policy is dated on this page.
Summary Statement
The purpose of this AI ethics disclosure is simple: to make the invisible visible. Every post, idea, and artifact here represents a fusion of human intention and artificial intelligence, bound by governance structure and transparent documentation. Together they form the architecture of augmented intelligence, where the machine extends capability and a named human answers for the result.
AI Ethics Frequently Asked Questions
Does AI write your content? AI contributes research, drafting, and analysis. Every human-led piece passes human arbitration under Checkpoint-Based Governance, and no AI system finalizes or approves content without human review. Material in the Building Blocks by AI category is AI-generated by design and labeled that way, and it serves as raw material for human-led papers rather than as the finished work.
How many AI platforms do you use? The confirmed pool stands at fifteen models across thirteen platforms: Claude, ChatGPT, Perplexity (Sonar and Nemotron 3 Super), Grok, Gemini, DeepSeek, Le Chat, Copilot, Meta AI, Kimi, MiniMax, Qwen, and PublicAI (Apertus and Qwen-SEA-LION-v4). Production tools such as Gemini Notebook, ChatGPT Images, ElevenLabs, Grammarly, Canva, and Adobe Express support specific creative and technical functions without receiving RECCLIN role assignments.
What is HAIA? HAIA stands for Human Artificial Intelligence Assistant, also written as Human AI Assistant. It is the ecosystem of methods that organizes how work with AI is done on this site, beginning with HAIA-RECCLIN, which defines seven roles: Researcher, Editor, Coder, Calculator, Liaison, Ideator, and Navigator. HAIA-CAIPR structures parallel review across platforms, and a human arbiter controls every decision point. Read more on the HAIA ecosystem page.
What do #AIassisted and #AIgenerated mean? #AIassisted marks human-led content, blogs, and papers where the author’s voice and judgment lead and AI supports research, sourcing, or refinement. #AIgenerated marks the Building Blocks by AI category, where AI platforms produced the primary draft under human prompting and review as raw material for human-led work.
Are the thought leader opinions on this site real quotes? No. Simulated opinion analysis uses AI to model likely responses from public figures based on their documented positions. These are analytical projections, not endorsements, quotes, or affiliations, and any individual referenced may request review or removal at any time.
Who makes final decisions on published content? Basil C. Puglisi. No AI system may finalize or approve another AI system’s decision. Under Checkpoint-Based Governance this is a constitutional requirement rather than a preference, and human authority holds at every decision point.
What is Factics? Factics is a methodology that pairs every fact with a tactic and a measurable KPI (Key Performance Indicator). It was first stated publicly at SMAC in October 2012, first appeared in print in Digital Factics: Twitter in November 2012, and serves as the evidence foundation for every framework on this platform. Read more about Factics.
How is content quality measured? Two independent evaluation tools operate on content before publication. HAIA-SMART scores social media content across six pillars: Hook Quality, Reader Value, Credible Presence, Call-to-Action Strength, Engagement Worthiness, and AI-Pattern Detection. HAIA-CORE (Content Optimization Reader Evaluation) scores long-form articles across six pillars: Opening Authority, Non-Commodity Value, Evidence Discipline, Argument Architecture, Closing Authority, and Human Voice. Neither tool is a checkpoint, since the scores inform a named human who decides what goes out. The Human Enhancement Quotient and the Augmented Intelligence Score measure something different, which is whether the collaboration is developing the human governor. Read more about HEQ/AIS.
Is this site affiliated with any AI company? No. Basil C. Puglisi and basilpuglisi.com operate independently. All AI platform names, logos, and trademarks belong to their respective owners, and their use on this site is for identification only.
How often is this page updated? This page is reviewed periodically and updated as tools, roles, practices, and publications change. The evolution timeline grows when new frameworks, publications, or milestones are completed, and every update is dated.
Related Pages
Artificial Intelligence: Technology, Capability, Governance, and Human Accountability, the technology and the governance position
HAIA Ecosystem, the methods, tools, and records behind the work
Checkpoint-Based Governance, the human authority model
Factics, the 2012 foundation
HAIA-RECCLIN, roles for individual AI reasoning and dispatch
HAIA-CAIPR, parallel review across multiple platforms
HEQ/AIS, measuring the governance competence at the center of AI literacy
HAIA-CARCS, the accountability record
HAIA-SCOPE, source custody for published work
Building Blocks by AI, AI-generated raw material for human-led papers
Governing AI: When Capability Exceeds Control, the book
AI Policy, the Congressional package and AI Provider Plurality
AI Learning, courses and roadmaps for professionals
About Basil C. Puglisi, the author
Certification: Elements of AI, University of Helsinki | Ethics of AI, University of Helsinki
Reviewed periodically and updated as practice changes. Last updated September 15, 2026.
Basil C. Puglisi, MPA
A Human-AI Collaboration
#AIassisted using the HAIA Ecosystem | CC BY-NC-SA 4.0
Free for personal, educational, and noncommercial research use with attribution. Commercial exploitation, paid productization, and enterprise commercialization require separate permission and licensing.
Simple Summary Statement
The purpose of this disclosure is simple: to make the invisible visible.
Every post, idea, and artifact here represents a fusion of human intention and artificial intelligence, bound by ethical structure and transparent documentation.