Predictive Protection or Profiling? A Legal-Ethical Framework for Algorithmic Risk Tools in Child Welfare Systems in Spain

Predictive Protection or Profiling? 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A Legal-Ethical Framework for Algorithmic Risk Tools in Child Welfare Systems in Spain Elemegious Mugamba This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7388305/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The increasing integration of algorithmic risk assessment tools in child welfare systems across Europe—intended to enhance predictive protection and resource allocation—poses profound legal, ethical, and socio-technical challenges. This article interrogates Spain’s fragmented experimentation with predictive analytics in the child protection domain, situating it within broader European developments and the evolving corpus of fundamental rights jurisprudence. Drawing on original fieldwork conducted across three autonomous communities, and supported by 48 semi-structured interviews with frontline professionals, data engineers, and policymakers, the article combines doctrinal legal analysis with empirical inquiry and computational audit techniques to assess the regulatory sufficiency and normative coherence of algorithmic interventions in the Spanish child welfare sector. The study reveals significant divergence in algorithmic governance across regional jurisdictions—such as Catalonia’s Sistema de Valoración de Riesgos Sociales (SVRS) and Madrid’s binary risk scoring prototype—characterised by legal ambiguity, epistemic opacity, and minimal procedural safeguards. Despite Spain’s constitutional guarantees (Articles 18 and 39 CE) and obligations under the General Data Protection Regulation (GDPR) and the European Convention on Human Rights (ECHR), field evidence shows widespread non-compliance with Article 22 GDPR, the principle of legality under Article 9(3) CE, and the jurisprudence of the European Court of Human Rights (ECtHR) and the Court of Justice of the European Union (CJEU), notably in cases such as NJCM v Netherlands and López Ribalda v Spain. This article makes three principal contributions. First, it offers a granular comparative analysis of algorithmic decision-making architectures and scoring logics through the creation of original evaluative indices—SALI (Systemic Algorithmic Legality Index) and MAGI (Minimum Algorithmic Governance Index). Second, it provides a rights-based critique of Spain’s current administrative practices, arguing that algorithmic opacity, statistical bias, and inadequate contestability mechanisms risk transforming predictive tools into instruments of structural surveillance and automated marginalisation. Third, the article proposes a legal–ethical governance framework for high-risk artificial intelligence (AI) in social protection domains, aligning with the risk-tiered obligations under the proposed EU Artificial Intelligence Act (AIA) and value-sensitive design principles. By foregrounding the constitutional asymmetries, regulatory lacunae, and institutional inertia embedded in Spain’s decentralised welfare state, the article underscores the urgent need for harmonised legal standards, ex ante algorithmic impact assessments, independent audits, and participatory oversight mechanisms. The findings hold broader implications for European digital welfare governance, offering a replicable analytical methodology and normative blueprint for jurisdictions seeking to reconcile algorithmic innovation with human dignity, legal certainty, and child-centred care. Health Law Criminal Law Civil Rights Law International and Comparative Law Artificial Intelligence and Machine Learning Algorithmic child protection predictive analytics digital welfare GDPR AI governance fundamental rights Spain legal certainty data justice SALI MAGI Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7388305","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501304664,"identity":"cadbb521-50f0-49f0-994a-286b439fb77c","order_by":0,"name":"Elemegious Mugamba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYLACxgYGBn4GBjYStUg2kKzF4ACxWnRnpF/8dHOHnZzxjeRnDz5UMMjzix3Ar8XsRk6xdO6ZZGOzG2nmhjPOMBjOnJ1AUEuCdG4bc+K2Gwlm0rxtDAkGtwlrSf6d21Zfv3lG+jditaQfA9pyOMFAIodYW868YbPOPXMc6I03ZZIzzkgQ4Zfj6Y9v5+6oludvT98m8aHCRp5fmoAWBgYeAwgtAFYpQUg5CLA/gND8B4hRPQpGwSgYBSMRAADzzUYbFo97agAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0002-0262-4098","institution":"Autonomous University of Barcelona","correspondingAuthor":true,"prefix":"","firstName":"Elemegious","middleName":"","lastName":"Mugamba","suffix":""}],"badges":[],"createdAt":"2025-08-16 15:13:01","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7388305/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7388305/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89336509,"identity":"1a603d5e-3c1d-4d80-80f8-5eb9af0766e4","added_by":"auto","created_at":"2025-08-19 02:18:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1042439,"visible":true,"origin":"","legend":"","description":"","filename":"MugambaE.2025.PredictiveProtectionorProfiling.ALegalEthicalFrameworkforAlgorithmicRiskToolsinChildWelfareSystems.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7388305/v1_covered_55bcd2cc-c199-42fc-b8a9-bc771abcb8d9.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003ePredictive Protection or Profiling? A Legal-Ethical Framework for Algorithmic Risk Tools in Child Welfare Systems in Spain\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Autonomous University of Barcelona","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":" Algorithmic child protection, predictive analytics, digital welfare, GDPR, AI governance, fundamental rights, Spain, legal certainty, data justice, SALI, MAGI","lastPublishedDoi":"10.21203/rs.3.rs-7388305/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7388305/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe increasing integration of algorithmic risk assessment tools in child welfare systems across Europe—intended to enhance predictive protection and resource \u0026nbsp;allocation—poses profound legal, ethical, and socio-technical challenges. This article interrogates Spain’s fragmented experimentation with predictive analytics in the \u0026nbsp;child protection domain, situating it within broader European developments and the evolving corpus of fundamental rights jurisprudence. Drawing on original fieldwork \u0026nbsp;conducted across three autonomous communities, and supported by 48 semi-structured interviews with frontline professionals, data engineers, and policymakers, the \u0026nbsp;article combines doctrinal legal analysis with empirical inquiry and computational audit techniques to assess the regulatory sufficiency and normative coherence of \u0026nbsp;algorithmic interventions in the Spanish child welfare sector.\u003c/p\u003e\n\u003cp\u003eThe study reveals significant divergence in algorithmic governance across regional jurisdictions—such as Catalonia’s Sistema de Valoración de Riesgos Sociales \u0026nbsp;(SVRS) and Madrid’s binary risk scoring prototype—characterised by legal ambiguity, epistemic opacity, and minimal procedural safeguards. Despite Spain’s \u0026nbsp;constitutional guarantees (Articles 18 and 39 CE) and obligations under the General Data Protection Regulation (GDPR) and the European Convention on Human \u0026nbsp;Rights (ECHR), field evidence shows widespread non-compliance with Article 22 GDPR, the principle of legality under Article 9(3) CE, and the jurisprudence of the \u0026nbsp;European Court of Human Rights (ECtHR) and the Court of Justice of the European Union (CJEU), notably in cases such as NJCM v Netherlands and López Ribalda v \u0026nbsp;Spain.\u003c/p\u003e\n\u003cp\u003eThis article makes three principal contributions. First, it offers a granular comparative analysis of algorithmic decision-making architectures and scoring logics through \u0026nbsp;the creation of original evaluative indices—SALI (Systemic Algorithmic Legality Index) and MAGI (Minimum Algorithmic Governance Index). Second, it provides a \u0026nbsp;rights-based critique of Spain’s current administrative practices, arguing that algorithmic opacity, statistical bias, and inadequate contestability mechanisms risk \u0026nbsp;transforming predictive tools into instruments of structural surveillance and automated marginalisation. Third, the article proposes a legal–ethical governance \u0026nbsp;framework for high-risk artificial intelligence (AI) in social protection domains, aligning with the risk-tiered obligations under the proposed EU Artificial Intelligence \u0026nbsp;Act (AIA) and value-sensitive design principles.\u003c/p\u003e\n\u003cp\u003eBy foregrounding the constitutional asymmetries, regulatory lacunae, and institutional inertia embedded in Spain’s decentralised welfare state, the article underscores \u0026nbsp;the urgent need for harmonised legal standards, ex ante algorithmic impact assessments, independent audits, and participatory oversight mechanisms. The findings hold \u0026nbsp;broader implications for European digital welfare governance, offering a replicable analytical methodology and normative blueprint for jurisdictions seeking to \u0026nbsp;reconcile algorithmic innovation with human dignity, legal certainty, and child-centred care.\u003c/p\u003e","manuscriptTitle":"Predictive Protection or Profiling? 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