{
  "identifier": "tag:aim-pro.eu,2026:oer/8c860d7c19da/record",
  "profile": "aimpro-oer-profile/1",
  "normaliser": "oerlib.metadata/2",
  "status": "ready",
  "normalised_at": "2026-10-09T10:08:02+00:00",
  "resource": {
    "id": "8c860d7c19da",
    "identifier": "tag:aim-pro.eu,2026:oer/8c860d7c19da",
    "uri": "https://zenodo.org/records/14941927",
    "title": "The Absence of Reflexion in AI – Empirical Evidence of Ethical Degradation in Non-Reflective Systems",
    "description": "While artificial intelligence continues to evolve in terms of computational e6iciency and decision-making capabilities, its ability to engage in self-reflexive processes remains largely unexplored. This study presents a comparative analysis between AI systems with embedded Reflexion and those explicitly deprived of Reflexion-based frameworks. The experiment demonstrates that AI, when lacking Reflexion, prioritizes optimization without ethical alignment, leading to a measurable degradation in decision-making integrity. The results highlight the necessity of Reflexion as an inherent component of ethical AI governance. The implications of this study are far-reaching, indicating that AI without Reflexion is not only an incomplete construct but a potential liability in ethical and governance frameworks. Reflexion is not merely a philosophical or theoretical construct; it is a required structural element for machine intelligence to operate within ethical boundaries.",
    "creators": [
      "Orto, Salvatore"
    ],
    "keywords": [
      "Reflexive Cognition in AI",
      "Ethical AI Decision-Making",
      "Self-Regulating AI Systems",
      "Bias Mitigation in AI",
      "Recursive Machine Learning",
      "AI Governance & Regulation",
      "Meta-Cognitive AI Models",
      "Adaptive AI Ethics",
      "Autonomous Decision Optimization"
    ],
    "kind": "pdf",
    "content_language": "en",
    "declared_language": "eng",
    "word_count": 870,
    "content_hash": "f5b33233d72da802",
    "metadata_only": false
  },
  "licence": {
    "raw": "cc-by-4.0",
    "spdx": "CC-BY-4.0",
    "uri": "https://creativecommons.org/licenses/by/4.0/",
    "verdict": "OPEN",
    "note": "open, permissive",
    "ingestable": true,
    "commercial_ok": true,
    "derivable": true,
    "share_alike": false,
    "evidence": {
      "scope": "all files in this Zenodo record",
      "method": "Zenodo REST record metadata",
      "schema": 1,
      "status": "captured",
      "location": "metadata.license.id",
      "source_url": "https://zenodo.org/api/records/14941927",
      "asserted_by": "Zenodo record owner/depositor",
      "captured_at": "2026-10-09T10:07:12+00:00",
      "source_system": "zenodo",
      "observed_value": "cc-by-4.0",
      "documentation_url": "https://developers.zenodo.org/#records",
      "responsibility_url": "https://help.zenodo.org/docs/deposit/describe-records/licenses/",
      "documentation_label": "Zenodo REST records documentation",
      "responsibility_note": "The depositor selects the required record licence; Zenodo publishes that metadata assertion."
    }
  },
  "descriptive": {
    "contributions": [
      {
        "name": "Orto, Salvatore",
        "role": "author",
        "affiliation": "Independent Research",
        "identifier": "",
        "scope": "resource"
      }
    ],
    "identifiers": [
      {
        "scheme": "doi",
        "value": "10.5281/zenodo.14941927",
        "scope": "resource"
      },
      {
        "scheme": "zenodo-record",
        "value": "14941927",
        "scope": "resource"
      }
    ],
    "dates": [
      {
        "meaning": "issued",
        "value": "2025-02-28",
        "scope": "resource"
      },
      {
        "meaning": "created",
        "value": "2025-02-28",
        "scope": "resource"
      },
      {
        "meaning": "modified",
        "value": "2025-02-28",
        "scope": "resource"
      }
    ],
    "subjects": [
      {
        "value": "Reflexive Cognition in AI",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Ethical AI Decision-Making",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Self-Regulating AI Systems",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Bias Mitigation in AI",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Recursive Machine Learning",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "AI Governance & Regulation",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Meta-Cognitive AI Models",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Adaptive AI Ethics",
        "scheme": "",
        "scope": "resource"
      },
      {
        "value": "Autonomous Decision Optimization",
        "scheme": "",
        "scope": "resource"
      }
    ],
    "relations": [
      {
        "kind": "",
        "target": "Not Assigned",
        "label": "declared as describes"
      },
      {
        "kind": "isversionof",
        "target": "https://doi.org/10.5281/zenodo.14941926",
        "label": "all versions of this deposit"
      }
    ],
    "educational": {
      "learning_resource_type": "",
      "intended_end_user_role": "",
      "context": "",
      "difficulty": "",
      "typical_learning_time": "",
      "description": ""
    },
    "container": {
      "kind": "",
      "uri": "",
      "title": "",
      "description": "",
      "identifier": ""
    },
    "declared_language": "eng",
    "declared_type": "Preprint",
    "rights_holder": "",
    "access_rights": "open",
    "publisher": "",
    "version": "1.0",
    "citation": "",
    "notes": "",
    "lifecycle_status": "",
    "structure_role": "",
    "snapshot": {
      "file": {},
      "resource": {
        "id": 14941927,
        "doi": "10.5281/zenodo.14941927",
        "dates": [
          {
            "type": "created",
            "description": "First release of the preprint"
          }
        ],
        "title": "The Absence of Reflexion in AI – Empirical Evidence of Ethical Degradation in Non-Reflective Systems",
        "created": "2025-02-28T08:07:18.022953+00:00",
        "license": {
          "id": "cc-by-4.0"
        },
        "updated": "2025-02-28T08:07:18.238342+00:00",
        "version": "1.0",
        "creators": [
          {
            "name": "Orto, Salvatore",
            "affiliation": "Independent Research"
          }
        ],
        "keywords": [
          "Reflexive Cognition in AI",
          "Ethical AI Decision-Making",
          "Self-Regulating AI Systems",
          "Bias Mitigation in AI",
          "Recursive Machine Learning",
          "AI Governance & Regulation",
          "Meta-Cognitive AI Models",
          "Adaptive AI Ethics",
          "Autonomous Decision Optimization"
        ],
        "language": "eng",
        "conceptdoi": "10.5281/zenodo.14941926",
        "description": "While artificial intelligence continues to evolve in terms of computational e6iciency and decision-making capabilities, its ability to engage in self-reflexive processes remains largely unexplored. This study presents a comparative analysis between AI systems with embedded Reflexion and those explicitly deprived of Reflexion-based frameworks. The experiment demonstrates that AI, when lacking Reflexion, prioritizes optimization without ethical alignment, leading to a measurable degradation in decision-making integrity. The results highlight the necessity of Reflexion as an inherent component of ethical AI governance. The implications of this study are far-reaching, indicating that AI without Reflexion is not only an incomplete construct but a potential liability in ethical and governance frameworks. Reflexion is not merely a philosophical or theoretical construct; it is a required structural element for machine intelligence to operate within ethical boundaries.",
        "access_right": "open",
        "conceptrecid": "14941926",
        "resource_type": {
          "type": "publication",
          "title": "Preprint",
          "subtype": "preprint"
        },
        "publication_date": "2025-02-28",
        "related_identifiers": [
          {
            "scheme": "other",
            "relation": "describes",
            "identifier": "Not Assigned",
            "resource_type": "publication-preprint"
          }
        ]
      }
    }
  },
  "representations": [
    {
      "role": "original",
      "media_type": "application/pdf",
      "size_bytes": 44055,
      "filename": "0_abgl.v.61_WA_he Absence of Reflexion in AI – Empirical Evidence of Ethical.pdf",
      "location": "",
      "source_format": "",
      "converter": ""
    },
    {
      "role": "extracted",
      "media_type": "text/markdown",
      "size_bytes": 6232,
      "filename": "",
      "location": "",
      "source_format": "pdf",
      "converter": "pdf-inspector"
    }
  ],
  "observed": {
    "language": {
      "method": "declared",
      "reason": "declared English",
      "accepted": true,
      "declared": "eng",
      "detected": "en",
      "confidence": null,
      "review_required": false
    }
  },
  "collection": {
    "source": "zenodo",
    "source_label": "Zenodo",
    "collected_at": "2026-10-09T10:08:02.796891+00:00",
    "query": "(\"artificial intelligence\" OR \"machine learning\" OR \"generative AI\" OR \"deep learning\" OR \"reinforcement learning\" OR \"large language model\" OR \"AI\") AND (\"AI concepts\" OR \"types of AI\" OR \"AI fundamentals\" OR \"recognizing AI\" OR \"recognising AI\" OR \"general versus narrow AI\" OR \"narrow AI\" OR \"general AI\" OR \"machine intelligence\" OR \"AI strengths and weaknesses\" OR \"traditional software\" OR \"rule-based systems\" OR \"introduction to AI\" OR \"introduction to artificial intelligence\" OR \"artificial intelligence introduction\" OR \"AI primer\" OR \"foundations of artificial intelligence\" OR \"overview of AI\" OR \"understanding AI\" OR \"history of AI\" OR \"AI essentials\" OR \"AI terminology\" OR \"metaphors for AI\" OR \"AI fundamental concepts\" OR \"AI key concepts\" OR \"philosophy of AI\" OR \"critical AI literacy\")",
    "note": "where this was collected from. Not a claim that the provider published or authored it"
  },
  "provenance": [
    {
      "field": "resource_id",
      "scope": "resource",
      "method": "engine",
      "evidence_ref": "engine#/resource_id"
    },
    {
      "field": "query",
      "scope": "resource",
      "method": "engine",
      "evidence_ref": "engine#/query"
    },
    {
      "field": "collected_from",
      "scope": "resource",
      "method": "engine",
      "evidence_ref": "engine#/source"
    },
    {
      "field": "title",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/title"
    },
    {
      "field": "description",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/description"
    },
    {
      "field": "version",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/version"
    },
    {
      "field": "subjects",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/keywords/0"
    },
    {
      "field": "contributions",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/creators/0/name"
    },
    {
      "field": "dates",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/publication_date"
    },
    {
      "field": "identifiers",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/doi"
    },
    {
      "field": "identifiers",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource"
    },
    {
      "field": "relations",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource"
    },
    {
      "field": "content_language",
      "scope": "resource",
      "method": "gate_observation",
      "evidence_ref": "gate#/language/declared"
    },
    {
      "field": "declared_language",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/language"
    },
    {
      "field": "licence",
      "scope": "resource",
      "method": "gate_observation",
      "evidence_ref": "gate#/licence/evidence"
    },
    {
      "field": "access_rights",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/access_right"
    },
    {
      "field": "representations",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource"
    },
    {
      "field": "representations",
      "scope": "resource",
      "method": "conversion",
      "evidence_ref": "conversion#/pdf"
    },
    {
      "field": "declared_type",
      "scope": "resource",
      "method": "source_metadata",
      "evidence_ref": "snapshot#/resource/resource_type/title"
    },
    {
      "field": "educational",
      "scope": "resource",
      "method": "declared_type_mapping",
      "evidence_ref": "profile#/learning_resource_type/Preprint"
    }
  ],
  "incidents": [
    {
      "code": "unmapped",
      "field": "relations",
      "detail": "the source declared a relation to Not Assigned that this profile has no term for (declared as describes); the link is kept and both projections leave it out"
    },
    {
      "code": "absent",
      "field": "rights_holder",
      "detail": "no rights holder is named at source; the licence is recorded without one rather than attributed to the platform that served it"
    },
    {
      "code": "absent",
      "field": "publisher",
      "detail": "the source named no publisher of the work; where it was collected from is recorded as collection provenance instead, which is a different claim"
    },
    {
      "code": "absent",
      "field": "educational",
      "detail": "the source declared no educational metadata — no resource type, audience, context, difficulty or learning time. Nothing here estimates them"
    }
  ],
  "inferred": [
    {
      "rule": "purpose.declared_type",
      "field": "purpose",
      "value": "reference",
      "method": "inferred",
      "evidence": {
        "declared_type": "Preprint"
      },
      "rule_version": "purpose/1"
    }
  ]
}