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Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI

T0 review · 2 major / 5 minor · reviewed 2026-08-01 · deepseek-v4-flash

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Pith's one-line read The paper argues that selective disclosure of a person's Chronicle should be formalized as minimum-necessary subgraph compilation: given a relationship, purpose, and query, release the smallest authorized evidence subgraph that is sufficien

desk verdict A honest position paper that frames minimum-necessary disclosure as subgraph compilation, with a central caveat the authors themselves flag: the guarantee is only as good as the request planner. read the letter →

arxiv 2607.22953 v1 pith:XNI7Z6MN submitted 2026-07-24 cs.AI cs.CRcs.CYcs.SI

Sourena Khanzadeh , Daniel Platnick , Marjan Alirezaie , Hossein Rahnama This is my paper · ORCID
classification cs.AIcs.CRcs.CYcs.SI
keywords minimum-necessarydisclosureselectiveChronicleknowledgegraphfederatednetworkspurpose-basedaccesscontrolrelationship-baseddatasovereignty
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper proposes that selective disclosure of a person's Chronicle—a temporal knowledge graph of their lived situations—should be treated as a constrained minimization problem: given who asks, why they ask, and what they ask, release the smallest authorized evidence subgraph sufficient for the request. The authors formalize this as a minimization objective over the holder's consolidated Chronicle, subject to every node and edge passing an authorization function based on requester relationship and stated purpose, and subject to a structural sufficiency predicate. They provide a validator that checks path coverage, predicate-type completeness, connectivity, and provenance, plus an optional distributional refinement for LLM consumers. The two-phase protocol releases provenance-linked text first and raw artifacts only after explicit per-artifact holder approval, which the authors argue reduces disclosure blast radius. This is a protocol-design proposal rather than an implemented system, and the paper explicitly flags the minimization target and the request-planner completeness assumption as open questions.

What carries the argument

The central object is the authorized evidence subgraph S*, defined as the solution to a minimization problem over the holder's consolidated Chronicle: minimize |S| subject to S being drawn from the holder's graph, every node and edge passing the authorization function A(relationship, purpose, element), and the sufficiency predicate holding. Sufficiency is enforced by a validator that checks four structural conditions—path coverage of each information-need template (with ontology subsumption), predicate-type completeness, connectivity of the evidence paths, and provenance completeness—plus an optional distributional check comparing the consuming LLM's answer distribution over S* versus the fu

What would settle it

Find a query and a Chronicle where Algorithm 1 accepts a subgraph as structurally sufficient—path coverage, predicate-type completeness, connectivity, provenance—yet a competent human consumer or an LLM demonstrably cannot answer the query from that subgraph without additional context, as in the paper's own AFib example. A direct test of the completeness assumption: take a set of purpose-annotated queries, have domain experts enumerate the information needs, and check whether the planner's I(Q) matches; any dropped genuine need falsifies the guarantee.

Watch

Extended reading notes

Core claim

The central claim is that a Chronicle holder can—and should—answer a requester's query by compiling a compact authorized evidence subgraph S*, rather than by returning all data the requester is allowed to see. The subgraph is defined as the minimum-size subgraph drawn from the holder's consolidated Chronicle that passes the authorization function A for every node and edge and satisfies a structural sufficiency check: every information need is covered by a connected predicate-typed path with predicate-type completeness and full provenance. The authors argue that existing federated storage, policy engines, and blockchain systems provide pieces—sovereign storage, allow/deny policies, tamper-evi

Load-bearing premise

The load-bearing premise is that the request planner can reliably decompose a natural-language query into a complete set of schema-level information needs; if the planner drops a genuine need, the released subgraph is compact but under-informative, and the 'smallest sufficient' guarantee collapses.

Editorial extensions

If this is right

  • If a holder releases only S*, denied predicate categories (e.g., billing, psychiatric notes) never cross the holder boundary, making the access-control guarantee enforceable at hold time rather than by post-hoc redaction.
  • Because sufficiency is checked structurally against path templates and re-run on the assembled cross-holder subgraph, the protocol can guarantee that every information need is covered by connected, provenance-traceable paths even when fragments come from multiple federated holders.
  • The two-phase text-first/artifact-after-approval flow means high-fidelity raw data never rides along with a text response, limiting the blast radius of a disclosure even if the requester's agent is compromised after receipt.
  • Purpose limitation and relationship-based access become first-class inputs to a formal minimization objective, turning 'minimum necessary' regulatory requirements into a concrete per-request optimization target.
  • The AFib example shows a direct corollary: a structurally sufficient S* can still omit context a competent consumer needs, so structural sufficiency lower-bounds task sufficiency without implying it.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A natural extension would be to make the information-need set I(Q) a negotiated object rather than a one-shot planner output, letting the requester clarify or expand the need set before minimization runs.
  • The structural validator is consumer-agnostic, so a similar compile-time minimization layer could be applied to any predicate-typed graph retrieval system that must respect purpose and relationship constraints, not only PAi Chronicles.
  • Making the distributional sufficiency tier computable would turn the protocol from a compile-time guarantee into an empirical one, but it conflicts with the federated no-central-materialization stance; a per-holder local divergence check aggregated by the coordinator is a plausible middle path.
  • The AFib case suggests a testable variant of the minimization objective: instead of pure size, require inclusion of diagnosis-indication edges whenever a linked prescription is released, and measure whether task outcomes improve.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The paper proposes Provenance Preserving Chronicles (PPC), a federated protocol for minimum-necessary disclosure of personal context represented as temporal knowledge graphs (Chronicles). The central idea is to compile, per request, a compact authorized evidence subgraph that is both minimal under a stated objective and sufficient according to an explicit structural check. The paper formalizes this as a constrained minimization problem (Eq. 1), defines an authorization function over relationship and purpose, presents a two-phase interaction model (provenance-linked text first, raw artifacts only after explicit holder approval), and instantiates the design in medical and litigation scenarios. It also provides an explicit threat model and honestly states that it is a position/protocol-design paper without an implementation or empirical evaluation.

Significance. If the framework were realized, it would provide a principled compilation layer over existing federated storage and policy substrates, giving operational meaning to concepts such as purpose limitation and minimum-necessary disclosure in structured personal data. The paper's strengths include a clear separation between a sufficiency validator (Algorithm 1) and a compiler that searches for S*, an explicit two-phase release protocol that reduces disclosure blast radius, and a fair positioning against existing systems (Solid + VC + policy engine) rather than an overstated break from them. The paper also deserves credit for explicitly surfacing its own load-bearing assumptions—notably the completeness of request planning—and for labeling the distributional sufficiency tier as aspirational rather than shipped. The worked AFib example is particularly valuable for exposing the tension between structural minimization and clinical utility.

major comments (2)
  1. [§4.3 and §5.1] The central guarantee of Eq. (1)—that S* is both minimal and sufficient—is defined relative to I(Q), the planner's decomposition of Q into schema-level information needs. The paper explicitly acknowledges (§4.3) that a planner dropping a genuine need yields an S* that is compact but under-informative, and the AFib example (§5.1) concretely shows the resulting clinically insufficient release. However, the abstract and conclusion state that the system releases a subgraph 'sufficient for the request' without this qualification. Since this caveat is load-bearing for the paper's main claim, the abstract, Eq. (1), and the conclusion should consistently phrase the guarantee as 'sufficient relative to the request decomposition I(Q)' and clearly flag that the protocol does not, in its current form, provide an absolute minimum-necessary guarantee. The paper should also consolidate the planning-com
  2. [§5.1 and Table 2] The AFib example itself is used to illustrate the 'minimality can fight utility' tension, but the paper stops at stating the problem and does not propose even a heuristic mitigation. Since the example directly undermines the ordinary-language reading of 'share no more than the request requires' (the released S* omits context a cardiologist would reasonably need), the paper should discuss potential directions—e.g., expanding I(Q) with indications for retrieved medications, or allowing the requester to challenge/refine the decomposition in a second round—even if only as future work. As written, the paper's own worked example shows that the protocol can satisfy its formal definitions while failing the clinical purpose it is meant to serve, and the reader is left without any guidance on how to close this gap.
minor comments (5)
  1. [Abstract and Conclusion] The phrase 'sufficient for the request' appears without the caveat 'relative to the request decomposition I(Q)'. Adding this qualifier would make the paper's claims more precise and prevent overstatement of the protocol's guarantees.
  2. [Eq. (1)] The notation 'S ⊆ G_Cu' is slightly ambiguous because S is defined as a pair (V_S, E_S). It would be clearer to write 'V_S ⊆ V_Cu and E_S ⊆ E_Cu' explicitly, as done elsewhere in the text.
  3. [Algorithm 1] The distributional check in lines 22–24 is vague: what is the sample space over which P_M is defined, and what does 'semantic equivalence classes of answer strings' mean operationally? A brief clarification would help, especially because the paper labels this tier as aspirational.
  4. [Table 1] PPC's row shows '✓' for all capabilities, but since the system is not implemented, these checkmarks represent design intent rather than demonstrated functionality. Adding a footnote to distinguish 'designed' from 'implemented' would be more precise.
  5. [§6, step (3c)] The paper mentions Prize-Collecting Steiner Tree as an example solver but does not note that the underlying minimization is NP-hard or discuss approximation guarantees. Since the protocol explicitly does not certify minimality, a one-sentence acknowledgement would prevent readers from assuming that the solver produces the exact optimum of Eq. (1).

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the core formalization is conditional on an explicitly acknowledged planner-completeness assumption, and self-citations are background rather than load-bearing.

full rationale

The paper's central contribution is a formal optimization objective (Eq. 1) plus a structural sufficiency validator (Algorithm 1). Eq. (1) is an optimization problem, not a prediction derived from fitted data: it minimizes size subject to authorization and sufficiency constraints. Sufficiency is defined explicitly in §4.3 via PathCov, PredComplete, connectivity, and ProvComplete, and Algorithm 1 checks exactly those conditions. There is no fitted parameter relabeled as a prediction, and no equation reduces to its own input by construction. The paper's acknowledged dependence on the request planner—'Framework soundness is conditional on this step: sufficiency, minimization, and authorization are all defined relative to I(Q)'—is a genuine completeness limitation, and the AFib example in §5.1 is an honest illustration of that limitation. But this is a conditional-soundness caveat, not circularity: I(Q) is derived from the query Q, not from the released subgraph S*, and the formal system is transparent about what it does and does not guarantee. Self-citations to PAi background ([2], [31], [32]) establish the Chronicle model and deployed applications, but the PPC formalization (authorization function, subgraph minimization, two-phase protocol) is defined in the present paper and is not derived from those references in a load-bearing way. No uniqueness theorem is imported from the authors' prior work, and no alternative is excluded by self-citation. The paper makes no external benchmark claims; its worked examples are explicitly hypothetical and are used to expose the planner-completeness tension rather than to certify it. Accordingly, no circular step is present, and the appropriate finding is no significant circularity.

Assumptions & free parameters 2 free parameters · 6 assumptions · 0 invented entities

The contribution rests on the self-cited PAi Chronicle model, on the unproven completeness of request planning, on an assumed privacy-preserving record linkage primitive, and on several threat-model scoping choices. None of these are demonstrated in this paper; they are stated assumptions or open problems. No new physical or metaphysical entities are introduced; the new components (PPC, access controller, two-phase flow) are architectural protocol constructs, not postulated mechanisms.

free parameters (2)
  • Divergence threshold ε
    Algorithm 1 uses ε to decide whether an LLM consumer's answer distribution over S* is close enough to the distribution over the full authorized view C_a. No value or calibration is given; it is a hand-chosen, unvalidated threshold used only in the optional distributional tier.
  • Authorization-weighted penalty weights in minimization
    Step 3(c) of the protocol says the subgraph optimizer uses 'authorization-weighted penalties' (Prize-Collecting Steiner Tree). The actual penalty values are not specified, so the practical objective is under-determined.
assumptions (6)
  • domain assumption A user's personal context can be faithfully represented as a temporal knowledge graph of predicate-labeled Situation Graphs (a Chronicle).
    Borrowed from the authors' prior PAi work (ref [2]). All PPC reasoning operates over this representation; if the Chronicle model is not a faithful encoding of personal context, the protocol's outputs are built on the wrong substrate. Invoked throughout §2 and §4.
  • ad hoc to paper Request planning can decompose a natural-language query Q into a complete set of information needs I(Q) with correct path templates.
    The paper states in §4.3 that framework soundness is conditional on this step; a planner that drops a need yields an under-informative S*. This is not standard math and not an external discipline constraint; it is a self-imposed requirement the paper does not satisfy.
  • domain assumption Ontology subsumption (⊑) between predicate types is a valid basis for path matching and completeness.
    Algorithm 1 uses subsumption to allow a cardiacDiagnosis edge to satisfy a diagnosis template. This requires the domain ontology's hierarchy to be semantically correct for the regulative domain, which is a domain-expert assumption.
  • domain assumption Privacy-preserving cross-holder record linkage can be performed without revealing unmatched identifiers.
    Protocol step 4 depends on this for assembling S* across holders, and the paper explicitly calls it 'an open problem' (ref §6, step 4). If such linkage is not available or leaks metadata, the federated assembly step is not implementable as described.
  • domain assumption The verifiable-presentation/DID layer is sound, and the holder's local system is trusted, while the coordinator is honest-but-curious.
    These are explicit scoping choices in §6.1. If credentials are forgeable or the local system is compromised, the authorization guarantees do not hold. These are reasonable for a threat model but are not proven or implemented.
  • ad hoc to paper Cardinality of the subgraph (|V|+|E|) is the right objective for 'minimum-necessary' disclosure.
    The paper defines S* as the minimum-size subgraph, but later admits in §5.1 that aggressive structural minimization can omit clinically load-bearing context (the AFib indication) and that the minimization target itself is an open question. This is a design choice, not an externally justified metric.

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Cite this review

Pith. "Pith review of Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI." pith.science (2026). https://pith.science/paper/XNI7Z6MN

@misc{pith2026260722953,
  author       = {Pith},
  title        = {Pith review of: Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XNI7Z6MN}},
  note         = {Machine review of arXiv:2607.22953}
}
read the original abstract

Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data. Users require a sovereign system to securely own, govern, and disclose their context while remaining compliant across regulated domains with strict provenance, interpretability, and policy adherence. Perspective-aware AI approaches this by transforming a user's aggregated personal data into a structured identity model called a \emph{Chronicle}: a temporal knowledge graph that represents and grows with the user. Chronicles support the secure disclosure of context across federated networks. A Chronicle holder may expose a queryable, authorized view that a third-party agent may consult without centralizing anyone's data. This paper explores the problem of minimum-necessary disclosure across domain boundaries: when a requester's agent queries a Chronicle, how can the system constrain its response to release only what the requester's relationship, stated purpose, and specific task require? We propose \textbf{Provenance Preserving Chronicles} (PPC), a federated protocol that compiles each holder's Chronicle into a compact \emph{authorized evidence subgraph} governed by one rule: \emph{share no more than the request requires}. Holders keep local sovereignty; an access controller projects relationship-aware views over domain-expert ontologies; and a two-phase flow returns provenance-linked text first, releasing raw artifacts only after explicit holder approval. We frame the problem, map gaps in blockchain, P2P, and holder-sovereign designs, define the core constructs, and sketch the protocol with an explicit threat model.

Figures

Figures reproduced from arXiv: 2607.22953 by the authors.

Figure 1
Figure 1. A Chronicle stacks Situation Graph snapshots in [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Federated Chronicle disclosure architecture. A requester sends batched requests over a secure channel to an access [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗

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