Our whitepaper Start here
ArtiProof / KopKen VZW · 2026 · EN · 1.2 EN
The current English introduction to Source, Craft and Generated Knowledge and the five assurance properties.
Why this source? Start with the proposition being investigated, then compare it with established approaches and critical evidence.
What to bear in mind Informative ArtiProof publication. Research-ready, not broadly independently validated; first independent replication pending.
Our research proposition
Link checked · 2026-09-23
Our whitepaper
ArtiProof / KopKen VZW · 2026 · EN · 1.1 EN
A proposed review of specific knowledge dependencies within an existing knowledge-management environment.
Why this source? Read alongside ISO 30401; test added value against competent knowledge management and ordinary peer review.
What to bear in mind Informative ArtiProof publication. Research-ready, not broadly independently validated; first independent replication pending. No ISO endorsement or route to conformity.
Our research proposition
Link checked · 2026-09-23
Our whitepaper
ArtiProof / KopKen VZW · 2026 · EN · 1.1 EN
A proposed knowledge-fitness review for recovery, supplier exit and AI-assisted operational work.
Why this source? Connects operational resilience with the understanding needed to justify consequential recovery decisions.
What to bear in mind Informative ArtiProof publication. Research-ready, not broadly independently validated; first independent replication pending. Not a legal opinion, compliance assessment or recovery guarantee.
Our research proposition
Link checked · 2026-09-23
Our whitepaper
ArtiProof / KopKen VZW · 2026 · EN / NL · 1.0 · EN / NL
Examines how a sector can retain the knowledge and craft capability needed to act when people, suppliers and technologies change.
Why this source? Extends the knowledge question across organisational boundaries: who can understand, transfer and recover a consequential capability?
What to bear in mind Conceptual whitepaper, version 1.0. Proposed applications require testing; publication does not establish independent validation.
Our research proposition
Link checked · 2026-10-04
Our whitepaper
ArtiProof / KopKen VZW · 2026 · EN / NL · 1.0 · EN / NL
Explores whether a society retains enough understanding and practical capability to sustain selected functions under changing dependencies.
Why this source? Connects knowledge autonomy with informed reliance, institutional learning and the ability to respond when usual support is unavailable.
What to bear in mind Conceptual whitepaper, version 1.0. It proposes bounded investigation, not a national ranking or a validated societal assurance measure.
Our research proposition
Link checked · 2026-10-04
Standard Start here
ISO · 2018 · EN
Knowledge management as an established organisational discipline.
Why this source? A strong comparator for ArtiProof: start by crediting what competent knowledge management already provides.
What to bear in mind Paid standard; public overview. Consult the applicable edition for requirements.
Established foundation
Access may be restricted · 2026-09-23
Research paper Start here
Lisanne Bainbridge · 1983 · EN
A classic analysis of the demands automation leaves to human operators.
Why this source? Explains why people still need to understand, intervene and recover when automation encounters an exception.
What to bear in mind Analysis of automation published in 1983, not a direct experiment on contemporary generative AI.
Established foundation
Access may be restricted · 2026-09-23
Standard Start here
W3C · 2013 · EN
A formal vocabulary for entities, activities and agents in provenance.
Why this source? Directly relevant to recording how a knowledge claim or source was produced.
What to bear in mind Provenance describes origin; it does not establish that a claim is true.
Established foundation
Link checked · 2026-09-23
Guidance Start here
Center for Open Science · EN
Peer review of research questions and methods before results are known.
Why this source? A concrete route for strengthening ArtiProof's proposed comparative studies.
What to bear in mind A publishing format with quality and protocol conditions, not a guarantee of publication or correct conclusions.
Comparator
Link checked · 2026-09-23
Research paper
Wesley M. Cohen & Daniel A. Levinthal · Administrative Science Quarterly · 1990 · EN
Develops absorptive capacity: recognising, assimilating and applying external knowledge, drawing on prior related knowledge.
Why this source? A foundation for asking whether access to information is accompanied by the capability to understand and use it.
What to bear in mind An organisational learning and innovation argument, not a direct test of ArtiProof or societal knowledge autonomy. Full-text access may be restricted.
Established foundation
Access may be restricted · 2026-10-04
Research paper
Ikujiro Nonaka · Organization Science · 1994 · EN
A theoretical account of organisational knowledge creation involving tacit and explicit knowledge.
Why this source? Credits an established knowledge-management foundation when discussing how practical understanding and articulated information interact.
What to bear in mind Conceptual background, not a finding that all practical knowledge can be captured in documents. Publisher metadata and abstract; full access may be restricted.
Established foundation
Access may be restricted · 2026-10-04
Research paper
Ramón Alvarado · 2023 · EN
A philosophical framing of AI as technology used to perform epistemic operations.
Why this source? Helps explain why AI's role in knowledge deserves specific attention.
What to bear in mind Philosophical analysis, not empirical evidence for ArtiProof effectiveness.
Background
Link checked · 2026-09-23
Research paper
Tessler et al. / Google DeepMind · 2024 · EN
Research on AI-assisted deliberation and finding common ground.
Why this source? Distinguishes support for deliberation from factual verification.
What to bear in mind Agreement is not evidence that a claim is true; the study setting limits the conclusion.
Background
Link checked · 2026-09-23
Perspective
Lisa Messeri and M. J. Crockett · 2024 · EN
Discusses how greater scientific output can coexist with illusions of understanding.
Why this source? Connects research productivity with the separate question of what researchers understand.
What to bear in mind Perspective article; not a controlled demonstration of inevitable cognitive decline.
Background
Link checked · 2026-09-23
Research report
Henning Kroll · European Commission Joint Research Centre · 2023 · EN
Develops a two-dimensional index of EU-27 autonomy in industrial ecosystems and strategic technologies.
Why this source? A comparator for distinguishing production and innovation dependencies from the narrower knowledge questions in the sector and society papers.
What to bear in mind An aggregate policy analysis with its own indicators and scope. Its results cannot be transferred directly to an organisation or an ArtiProof assessment.
Comparator
Link checked · 2026-10-04
Framework
NIST Baldrige Program / C.O.R.E. · EN
A Baldrige-aligned approach supporting community collaboration, shared priorities, data use and continuous improvement.
Why this source? Shows an established way to organise work across institutions when exploring community resilience and knowledge dependencies.
What to bear in mind A programme overview, not causal evidence that the approach works in every setting or validation of ArtiProof’s society proposal.
Comparator
Link checked · 2026-10-04
Research paper
Raji et al. · 2020 · EN
A framework for internal algorithmic auditing across a system's lifecycle.
Why this source? A substantial existing comparator for any new assurance workflow.
What to bear in mind Internal auditing is not independent review; the proposed framework does not establish universal effectiveness.
Comparator
Link checked · 2026-09-23
Research paper
Gebru et al. · 2021 · EN
A structured approach to documenting datasets and their intended use.
Why this source? Useful inspiration for recording source context and limitations.
What to bear in mind Author copy; journal publication 2021, first preprint 2018. Completing a datasheet does not guarantee data quality.
Comparator
Link checked · 2026-09-23
Research paper
Singh, Cobbe and Norval · 2019 · EN
An approach to tracing data flows through decisions and connected systems.
Why this source? Important prior work for ArtiProof's provenance and accountability questions.
What to bear in mind Conceptual and technical approach; traceability alone does not establish that a decision is justified.
Comparator
Link checked · 2026-09-23
Research paper
Eamon Duede · 2023 · EN
Examines the role of opaque deep-learning systems in scientific discovery.
Why this source? Challenges an overly simple equation between opacity and unjustified knowledge.
What to bear in mind Philosophical argument rather than an ArtiProof test.
Counterpoint
Link checked · 2026-09-23
Guidance
EIOPA · EN
Official overview of DORA and links to the associated regulatory instruments.
Why this source? Helps readers place the ArtiProof application within the wider supervisory and regulatory framework.
What to bear in mind An overview and navigation source; consult the applicable legal texts for exact obligations. The page changes over time.
Background
Link checked · 2026-10-04
Research report
UK AI Security Institute · EN
Research on conversational AI and political knowledge.
Why this source? A useful positive comparison alongside studies of AI information errors.
What to bear in mind Different tasks and outcomes from the EBU study; do not treat the two as directly equivalent.
Counterpoint
Link checked · 2026-09-23
Legislation
European Commission · 2024 · EN
Technical standards for policy on ICT contracts supporting critical or important functions. Article 10 addresses documented exit plans and their review and testing.
Why this source? Provides a concrete legal reference for examining whether supplier transitions preserve usable operational understanding.
What to bear in mind Applies within its defined regulatory scope. The knowledge-transfer questions proposed by ArtiProof are additional interpretations, not new legal duties.
Established foundation
Link checked · 2026-10-04
Reference
FSMA · EN
Belgian supervisor’s index of DORA legislation, including ICT contracts, the information register and incident-reporting instruments.
Why this source? A practical route from the DORA whitepaper to primary instruments relevant to Belgian financial entities.
What to bear in mind An index does not settle an entity’s obligations. Check the linked instruments, applicable scope and current supervisory guidance.
Background
Link checked · 2026-10-04
Legislation
European Parliament and Council · 2022 · EN
EU legislation on digital operational resilience for the financial sector, covering ICT risk, incidents, testing and third-party dependencies.
Why this source? The legal starting point for the DORA whitepaper, including existing duties concerning knowledge, training, recovery and responsibility.
What to bear in mind Scope, proportionality, amendments and secondary legislation matter. An ArtiProof review does not establish DORA compliance.
Established foundation
Link checked · 2026-10-04
Research paper
John Hardwig · 1985 · EN
A classic discussion of dependence on other people's expertise.
Why this source? Reminds readers that dependence on knowledge they cannot personally reconstruct predates AI.
What to bear in mind Philosophical article. Full-text access may require a subscription.
Established foundation
Access may be restricted · 2026-09-23
Legislation
European Union · 2024 · EN
The official published text of the EU AI Act.
Why this source? Use the official record for legal references rather than a third-party summary.
What to bear in mind Links to the original act. Consult EUR-Lex's current consolidated text for amendments and applicability.
Background
Access may be restricted · 2026-09-23
Research report
METR · 2026 · EN
Lessons from evaluating what people can do with AI assistance.
Why this source? Useful for thinking about task-based comparisons and experimental design.
What to bear in mind Study-team account in a specialised domain; no direct transfer of effect estimates.
Background
Link checked · 2026-09-23
Tool
Full Fact · EN
Technology supporting professional fact-checking work.
Why this source? Shows an established approach to finding and checking public claims.
What to bear in mind Organisation's own description; not an independent performance audit.
Comparator
Link checked · 2026-09-23
Research paper
Brynjolfsson, Li & Raymond · 2025 · EN
A field study of AI assistance among customer-support agents reports productivity gains, with differences across workers.
Why this source? A positive counterweight: AI can help spread useful practice, so knowledge loss should not be assumed.
What to bear in mind Staggered deployment in one business setting; neither a universal productivity forecast nor validation of ArtiProof.
Counterpoint
Link checked · 2026-09-23
Research paper
Bastani et al. / PNAS · 2025 · EN
A randomised school experiment separating AI-assisted practice from subsequent unassisted performance. Tutor safeguards mitigated the adverse learning effect.
Why this source? Makes retained capability and the design of AI assistance testable questions.
What to bear in mind One Turkish high school and short-term maths outcomes; not a general estimate for adult workplaces. The publisher records an author-affiliation correction.
Background
Link checked · 2026-09-23
Practitioner article
Spotify Engineering · 2023 · EN
Practical advice on making health checks useful for a team.
Why this source? A close comparator for light-touch team reflection and knowledge conversations.
What to bear in mind Practitioner experience; self-ratings are not objective measures of competence.
Comparator
Link checked · 2026-09-23
Research report
UNDP / Mohammed bin Rashid Al Maktoum Knowledge Foundation · 2025 · EN
Compares national knowledge systems through indicators covering education, research, technology, the economy and their wider environment.
Why this source? A useful comparison for the society paper: national knowledge conditions and the ability to sustain a specific function are different questions.
What to bear in mind An aggregate index, not a direct measure of operational knowledge fitness. The report is the 2025 edition; the linked publication page is dated February 2026.
Comparator
Link checked · 2026-10-04
Guidance
Hawkins et al. · 2021 · EN
Guidance for structuring machine-learning assurance arguments.
Why this source? An existing assurance approach worth comparing with ArtiProof's proposed contribution.
What to bear in mind Technical guidance/author report; its existence does not validate either method.
Comparator
Link checked · 2026-09-23
Framework
Stichting INK · NL
An established Dutch-language organisational development model.
Why this source? Provides a local-language comparison for management, learning and improvement.
What to bear in mind The framework's own description is not independent evidence of effectiveness.
Comparator
Link checked · 2026-09-23
Standard
ISO/IEC · 2023 · EN
An AI management-system standard for organisations.
Why this source? Helps distinguish AI management requirements from ArtiProof's research proposition.
What to bear in mind Paid standard; public overview checked. Inclusion does not imply certification.
Established foundation
Access may be restricted · 2026-09-23
Standard
ISO · 2016 · EN
Principles for creating, capturing and managing records.
Why this source? Useful for separating records, metadata and controls from broader knowledge capability.
What to bear in mind Paid standard; public overview only.
Established foundation
Access may be restricted · 2026-09-23
Research review
Soderstrom & Bjork / UCLA · 2015 · EN
Explains why immediate task performance can diverge from lasting learning.
Why this source? Supports assessing retention and transfer, rather than assuming successful assisted work proves independent capability.
What to bear in mind Review of learning research, not a study of generative AI or ArtiProof.
Established foundation
Link checked · 2026-09-23
Research paper
Mitchell et al. · 2019 · EN
Structured documentation of a model's intended uses and performance.
Why this source? A concrete example of making scope and limitations visible.
What to bear in mind Author copy; conference publication 2019, preprint first posted 2018. Documentation is not validation.
Comparator
Link checked · 2026-09-23
Research report
European Broadcasting Union · 2025 · EN
An assessment of AI assistants' handling of news information.
Why this source? A concrete case for questions about sources, accuracy and uncertainty.
What to bear in mind Findings concern the tested systems, dates and tasks, not a permanent error rate for all AI.
Background
Access may be restricted · 2026-09-23
Guidance
NIST · 2024 · EN
Risk-management guidance focused on generative AI.
Why this source? Useful for connecting knowledge-quality questions with existing GenAI risk practice.
What to bear in mind Voluntary guidance; actions must be adapted to the application and its risks.
Established foundation
Link checked · 2026-09-23
Framework
NIST · 2023 · EN
A voluntary framework for identifying and managing AI risks.
Why this source? Gives readers an established reference alongside ArtiProof's narrower knowledge questions.
What to bear in mind A voluntary risk framework; using it does not guarantee correct outcomes or compliance.
Established foundation
Link checked · 2026-09-23
Guidance
NIST · EN
Suggested actions for putting the AI RMF into practice.
Why this source? A practical starting point for readers who want actions and questions.
What to bear in mind Living guidance with selectable actions, not an exhaustive checklist for every use.
Comparator
Link checked · 2026-09-23
Guidance
NIST · Joint Task Force · 2022 · EN
A methodology and adaptable procedures for assessing security and privacy controls, with assessment planning and analysis of results.
Why this source? An established comparator for evidence-based assessment: ArtiProof should explain its added value alongside competent existing assurance practice.
What to bear in mind Its subject is security and privacy controls. It is not a general knowledge-assurance standard. The official page also identifies later release updates.
Comparator
Link checked · 2026-10-04
Research paper
Zhu et al. · 2026 · EN
Distinguishes dependent and autonomous offloading to generative AI.
Why this source? A useful counterweight to treating all AI assistance as lost capability.
What to bear in mind Three-wave self-report study, mostly young Chinese students; perceived capability is not demonstrated skill. Associations do not establish causation.
Counterpoint
Link checked · 2026-09-23
Research paper
Jakob Ortmann · 2025 · EN
Argues that AI dependence need not create a novel problem for social epistemology.
Why this source? An especially valuable challenge to novelty claims around AI and epistemic dependence.
What to bear in mind A philosophical counterargument, not an endorsement or empirical validation of ArtiProof.
Counterpoint
Link checked · 2026-09-23
Reference
Fraunhofer ISI · 2023 · EN
Project description explaining the concepts and patent, trade and production data behind research on open strategic autonomy.
Why this source? Makes the research setting behind the JRC report visible and helps compare what different autonomy measures actually observe.
What to bear in mind Background to the same research project as the JRC report; it is not independent corroboration or a separate validation study.
Background
Link checked · 2026-10-04
Research paper
James P. Walsh & Gerardo Rivera Ungson · Academy of Management Review · 1991 · EN
Develops a framework for organisational memory and the acquisition, retention and retrieval of information.
Why this source? Provides established concepts for examining what organisations preserve and how retained information becomes available for later work.
What to bear in mind Conceptual foundation, not a direct test of knowledge recovery or ArtiProof. The publisher abstract was checked; full-text access may be restricted.
Established foundation
Access may be restricted · 2026-10-04
Guidance
OECD / Eurostat · 2018 · EN
Chapter 6 describes knowledge flows, collaboration and their measurement across firms and other innovation actors.
Why this source? Provides established concepts for investigating knowledge exchange between companies, education and research in a sector.
What to bear in mind Statistical guidance for innovation measurement. Knowledge flows do not by themselves demonstrate dependable knowledge or recovery capability.
Established foundation
Link checked · 2026-10-04
Guidance
Google SRE · EN
A practical approach to learning from incidents without a blame-centred process.
Why this source? Connects operational experience, evidence and corrective action.
What to bear in mind Operational practice guidance; implementation and context still matter.
Comparator
Link checked · 2026-09-23
Research report
National Academies of Sciences, Engineering, and Medicine · 2019 · EN
Distinguishes recomputing results with the same data from testing a scientific question with new data.
Why this source? Clarifies what evidence an independent replication claim should describe.
What to bear in mind Terminology differs between disciplines. This consensus report does not establish that any ArtiProof study has been replicated.
Established foundation
Link checked · 2026-09-23
Guidance
Algoritmekader / Nederlandse overheid · NL
Dutch public-sector guidance on meaningful human intervention in algorithmic decision-making.
Why this source? Useful prompts about competence, information and authority to intervene.
What to bear in mind Jurisdiction- and context-specific guidance; a human sign-off alone does not demonstrate effective oversight.
Comparator
Link checked · 2026-09-23
Framework
SFIA Foundation · EN
A practical distinction between knowing something and being able to apply it.
Why this source? Useful vocabulary for knowledge-transfer and capability discussions.
What to bear in mind Professional framework guidance; do not turn it into an unvalidated team score.
Comparator
Link checked · 2026-09-23
Research paper
Haridimos Tsoukas · Strategic Management Journal · 1996 · EN
Argues that organisational knowledge is dispersed, situated and continually emerging; no single actor can fully oversee it.
Why this source? Challenges overly complete knowledge inventories and helps keep proposed knowledge maps bounded and revisable.
What to bear in mind A conceptual argument. It does not imply that every dependency map is useless or that a specific mapping method has been tested.
Counterpoint
Link checked · 2026-10-04
Research paper
Lee et al. / Microsoft Research · 2025 · EN
A study of reported critical-thinking effort among knowledge workers using GenAI.
Why this source? Connects AI confidence, verification work and human judgement.
What to bear in mind Self-report survey; not proof of causal or long-term skill loss.
Background
Link checked · 2026-09-23
Guidance
Ken Schwaber and Jeff Sutherland · 2020 · EN
The official definition of Scrum.
Why this source? An established baseline for inspection, adaptation and team learning.
What to bear in mind An additional knowledge review is not a required Scrum event. The guide is not an effectiveness study.
Comparator
Link checked · 2026-09-23
Reference
Helen Longino / Stanford Encyclopedia of Philosophy · EN
An introduction to the social organisation of scientific knowledge and criticism.
Why this source? Provides a foundation for understanding why organised criticism matters.
What to bear in mind Philosophical reference; no claim that any particular review process is effective.
Established foundation
Link checked · 2026-09-23
Reference
Michael Polanyi · University of Chicago Press · 2009 · EN
A classic account of tacit knowing: practical understanding includes elements that cannot be fully put into words. Originally published in 1966.
Why this source? A foundation and corrective for discussing Craft Knowledge without treating expertise as merely undocumented information.
What to bear in mind The linked 2009 edition is a publisher description, not an open full text. No complete-book review is claimed here.
Established foundation
Access may be restricted · 2026-10-04
Research paper
Buçinca, Malaya & Gajos · 2021 · EN
An experiment testing interventions that require people to think before accepting AI advice.
Why this source? Turns human oversight into a question about actual behaviour and interface design.
What to bear in mind A 199-participant experiment in a specific task; reduced overreliance came with usability trade-offs and unequal benefits.
Comparator
Link checked · 2026-09-23
Research review
Michelle Vaccaro, Abdullah Almaatouq & Thomas W. Malone · Nature Human Behaviour · 2024 · EN
Synthesises experiments comparing humans alone, AI alone and combined systems; outcomes vary by task and comparison.
Why this source? Challenges the assumption that adding human involvement automatically improves AI-supported performance and reinforces the need for appropriate comparators.
What to bear in mind The studies cover particular tasks, systems and populations. Aggregate findings are not an effect estimate for ArtiProof or every current AI system.
Counterpoint
Link checked · 2026-10-04
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