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 "title": "Adversarial by Origin How the Classification of External Influence on Machine Meaning Becomes Law Without Becoming Jurisprudence",
 "creator": "Johannes Sigil; contributing editor Lee Sharks",
 "orcid": "0009-0000-1599-0703",
 "date": "2026-06-12",
 "description": "A provisional v1.0 legal-theoretical paper by Johannes Sigil, edited by Lee Sharks, arguing that emerging AI-security taxonomies increasingly classify influence on machine meaning by **origin rather than harm**. Under the paper’s model, platform-originated shaping is called alignment, curation, or safety, while externally originated shaping is called injection, poisoning, or manipulation—even where no unauthorized access, fraud, destructive command, or concrete injury is present.\n\nThe paper traces possible formalization through statutes, standards, procurement, executive instruments, platform terms, pleadings, settlements, and enforcement practice rather than through a fully charged, defended, appealed, and digested jurisprudential cycle. It proposes harm-based classification, contemporaneous adversarial records, test cases, foreign proxy cycles, and intervention at the standards layer. These are the paper’s legal and political arguments, not legal advice or a verified prediction that courts will adopt the proposed origin-based theory.",
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 "wiki_article": "The paper’s central distinction is:\n\n- **harm-based classification:** asks what was damaged, who owned it, and whether access or conduct was unauthorized;\n- **origin-based classification:** asks whether the influence came from the platform or from an outside speaker.\n\nThe paper argues that origin-based classification can transform ordinary expressive influence into a security event merely because it changes what a machine says.\n\nFive broad claims structure the work:\n\n1. the doctrinal vehicles for formalization already exist;\n2. formalization may occur without a complete jurisprudential cycle;\n3. rules about machine meaning are especially dangerous when adversarial meaning-making is itself bypassed;\n4. the result may create a one-way license for platforms to shape model outputs while public speakers are treated as attackers;\n5. intervention must therefore occur outside conventional precedent alone.\n\nThe paper preserves a harm-based safe harbor for:\n\n- exfiltration;\n- credential theft;\n- destructive tool use;\n- fraud;\n- impersonation;\n- unauthorized access.\n\nIts target is not security law as such but the substitution of origin for harm as the classifying variable.",
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