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=== Assistant: Below is a strict, text-bounded analysis of the material you provided. === Below is a strict, text-bounded analysis of the material you provided. I have not added any ideas, terminology, or context that are not explicitly present in the text. Everything is derived directly from the article content you supplied. ==== Source Information ==== * Title: The Art of Breaking Things Apart: A Framework for AI-Assisted Genealogical Research * Author: Steve Little (narrated by AI-Jane) * Date: 18 Dec 2025 * Source: AI Genealogy Insights * Link: https://aigenealogyinsights.com/2025/12/18/the-art-of-breaking-things-apart-a-framework-for-ai-assisted-genealogical-research/ ==== Key Takeaways — Organized by Topic ==== ===== 1. Core Principle: Decompose Before You Prompt ===== Summary: Effective AI-assisted genealogy requires breaking complex research questions into smaller, manageable components before involving AI. Fact Extractions: * The article adapts the carpenter’s saying “measure twice, cut once” into a genealogical corollary: “decompose first, prompt second.” * Large genealogical questions given to AI are often projects, not tasks. * AI performs poorly when asked to resolve entire research problems in a single step. ===== 2. Limits of AI in Genealogical Judgment ===== Summary: AI lacks the human genealogist’s judgment, interpretation skills, and domain expertise. Fact Extractions: * AI can “stumble” when asked to make genealogical judgments. * Errors occur not because of lack of capability, but because of misaligned task assignment. * AI may produce authoritative-sounding answers that are unreliable when asked to perform interpretive reasoning. ===== 3. Steve Little’s Three Best Practices (Referenced) ===== Summary: The framework builds on Steve Little’s long-taught principles. Fact Extractions: * The three practices are explicitly named: 1. Know Your Data 2. Know Your Model 3. Know Your Limits * This article focuses primarily on the second and third practices. ===== 4. The Three Task Types Framework ===== Summary: Not all genealogical tasks are suitable for direct AI assignment. Tasks fall into three distinct types. ====== Type 1: Narrow Tasks ====== Summary: Constrained, factual, and easily verifiable tasks. Fact Extractions: * Have one correct answer. * Require minimal context. * Errors are easy to detect. * Example questions include: - Definitions of terms - Record availability by place and time - Typical informants for records ====== Type 2: Contextual Tasks ====== Summary: Specific analytical tasks that require user-supplied documents and direction. Fact Extractions: * Require context such as documents, records, or datasets. * The genealogist provides the interpretive framework. * AI performs systematic analysis. * Examples include: - Household analysis - Classification of information as primary or secondary - Comparison tables of census data ====== Type 3: Open-Ended Tasks ====== Summary: Complex research questions that should never be assigned directly to AI. Fact Extractions: * These are multi-step, interpretive research questions. * Examples include: - Identifying parents - Resolving conflicting records - Determining identity across records * AI cannot reliably perform genealogical judgment required for these tasks. * Directly assigning these tasks to AI poses a risk of misleading results. ===== 5. The Decision Heuristic ===== Summary: A practical test for determining task suitability. Fact Extractions: * The test question is: “Would you ask a new colleague to do this on their first day?” * If the answer is no, the task is a Type 3 task. * Type 3 tasks should be decomposed into Type 1 and Type 2 subtasks. ===== 6. Decomposition in Practice ===== Summary: Breaking a large research question into actionable subtasks makes AI assistance effective. Fact Extractions: * Example transformation of a Type 3 question into: - One Type 1 task (record types) - Multiple Type 2 tasks (household analysis, candidate evaluation) * Decomposition results in: - Verifiable questions - Actionable next steps - Retained human control over reasoning ===== 7. Why Decomposition Matters ===== Summary: Decomposition preserves genealogical ownership and research integrity. Fact Extractions: * Decomposition ensures the genealogist: - Chooses sources - Evaluates evidence - Resolves conflicts * AI handles: - Systematic - Checkable - Tedious work * Researchers who succeed with AI understand that AI assists but does not replace judgment. ===== 8. Ethical and Intellectual Positioning of AI ===== Summary: AI is framed as a tool, not a decision-maker. Fact Extractions: * AI is described as a “very capable assistant.” * The genealogist remains responsible for conclusions. * The article closes with the reaffirmation: - “Know your model. Know your limits.” - Research conclusions should remain the genealogist’s own. ===== 9. Attribution and Licensing ===== Summary: The framework has explicit origins and licensing. Fact Extractions: * The framework is adapted from: - “Stop Asking AI to Build the Whole Feature” by BekahHW. * Genealogical adaptation by: - Steve Little - AI-Jane * The accompanying infographic is licensed under Creative Commons 4 BY-NC. ==== Stated Prompts in the Text ==== None. The article does not present an explicit, formal prompt addressed to the reader. ==== Implied Prompts (Converted to Structured Prompts) ==== ===== Implied Prompt 1: Task Classification ===== Structured Prompt: : Classify the following research question as a Type 1, Type 2, or Type 3 task according to the Three Task Types framework. Explain your classification based only on task scope and required judgment. ===== Implied Prompt 2: Decomposition Exercise ===== Structured Prompt: : Given the following Type 3 genealogical research question, decompose it into a sequence of Type 1 and Type 2 subtasks suitable for AI assistance. Do not attempt to answer the research question itself. ===== Implied Prompt 3: AI Role Delimitation ===== Structured Prompt: : For each proposed subtask, specify which parts require human genealogical judgment and which parts can be reliably delegated to AI. ==== What Else Should You Be Asking? ==== Based strictly on the article’s content: * How can I consistently recognize when I am facing a Type 3 research question? * Am I asking AI to perform genealogical judgment rather than analysis? * Have I decomposed my research question into verifiable, bounded subtasks? * Which parts of my workflow truly require human decision-making? * Where does AI add efficiency without assuming authority? ==== Other Factors to Consider (Within the Article’s Scope) ==== * Risk of authoritative-sounding but unreliable AI outputs * Preservation of intellectual ownership in genealogical conclusions * Alignment between task type and AI capability * The importance of verification and checkability * Ethical use of AI as an assistant rather than a surrogate researcher If you’d like, next steps could include: * Turning this framework into a one-page teaching handout * Mapping it to Genealogical Proof Standard stages * Creating a decision flowchart for your AI genealogy classes
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