Chan and colleagues treat agency in algorithmic systems as a matter of degree, raised by four characteristics: underspecification, directness of impact, goal-directedness and long-term planning; they stress that recognizing such agency “does not absolve or shift” human responsibility.

SocioLens project,

Claim LD01-SL-C10 (v1.0)

Provenance and status

Claim type: Interpretation
Publication status: Eligible for publication, with qualifiers: interpretation label
Verification state: Checked against the primary source. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: A measurement of agency in deployed systems
Limitations: Read in arXiv version 2 (12 May 2023), the FAccT 2023 paper; written before tool-using agent products were common; the harms are anticipated and the cited evidence is partial
Source (as cited): Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023
Source type: Peer-reviewed conference paper (recorded as “Peer-reviewed conference paper”)
Institutional position: Independent academic (Mila, University of Cambridge, UC Berkeley, McGill University and others)
Maturity of the evidence: Emerging evidence
Recorded date: 16 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023 (Peer-reviewed conference paper)
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Version

This is the current version, v1.0. Earlier versions stay available, and their records never change.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): INTERPRETATION (as printed: “INTERPRETATION”)
Publication status (coded): ELIGIBLE (INTERPRETATION_LABEL) (as printed: “ELIGIBLE WITH INTERPRETATION LABEL”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): PEER_REVIEWED_CONFERENCE_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD01-SL-C10	—
2	PUBLIC-FACING CLAIM	Chan and colleagues treat agency in algorithmic systems as a matter of degree, raised by four characteristics: underspecification, directness of impact, goal-directedness and long-term planning; they stress that recognizing such agency “does not absolve or shift” human responsibility.	—
3	CLAIM TYPE	INTERPRETATION	base_types: INTERPRETATION
4	RESEARCH STRAND	A — What each account says generative AI is, and what it predicts	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023	source_ids: SRC-SL-CHAN-ET-AL-AGENTIC-ARXIV-2302-10329
7	SOURCE TYPE	Peer-reviewed conference paper	classes: PEER_REVIEWED_CONFERENCE_PAPER
8	INSTITUTIONAL POSITION	Independent academic (Mila, University of Cambridge, UC Berkeley, McGill University and others)	—
9	SCOPE	Algorithmic systems in general, including language models; 2023	—
10	DESIGN	Conceptual argument with anticipated harms	—
11	SAMPLE / DATASET	Not applicable	—
12	MODEL / TOOL / VERSION	Algorithmic and machine-learning systems in general	—
13	COMPARATOR	Systems treated as passive tools	—
14	MAIN RESULT	Agency is graded; anticipated harms of more agentic systems include reward hacking, which the authors say can rise abruptly with model size or training time, citing other work	—
15	INFERENTIAL TARGET	How to describe and anticipate the harms of systems that act with growing independence	—
16	DOES NOT LICENSE	A measurement of agency in deployed systems	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Read in arXiv version 2 (12 May 2023), the FAccT 2023 paper; written before tool-using agent products were common; the harms are anticipated and the cited evidence is partial	—
19	CONTRADICTORY / SUPPORTING SOURCES	Agency as a profile on several dimensions: LD01-SL-C12; measured task length: LD01-SL-C23	—
20	GEOGRAPHY / LANGUAGE	Not applicable / English	—
21	DISTRIBUTIONAL LEDGER	Not analysed in this claim	—
22	R01 / FIELD-MAP LINKS	LD-01, T4, D6	—
23	WHAT WOULD CHANGE THIS CLAIM?	A validated measure of the four characteristics in deployed systems	—
24	PUBLICATION STATUS	ELIGIBLE WITH INTERPRETATION LABEL	state: ELIGIBLE · qualifiers: INTERPRETATION_LABEL
25	RECORDED DATE	2026-10-16	—

Field 22 references resolved against Field Map v0.2: LD-01 (LIVING_DEBATE); T4 (TENSION); D6 (DOMAIN)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023” → Chan et al. (2023), “Harms from Increasingly Agentic…” (SRC-SL-CHAN-ET-AL-AGENTIC-ARXIV-2302-10329--v1.0) — Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023; class PEER_REVIEWED_CONFERENCE_PAPER (explicit public provenance pin)

Cited by Living Debate versions

What kind of thing is generative AI, and does the answer predict anything? (v0.1) LD-01

Cite this page

SocioLens project. (2026, October 16). Chan and colleagues treat agency in algorithmic systems as a matter of degree, raised by four characteristics: underspecification, directness of impact, goal-directedness and long-term planning; they stress that recognizing such agency “does not absolve or shift” human responsibility [Claim LD01-SL-C10, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld01-sl-c10/v1.0/

@misc{sociolens_ld01_sl_c10_v1_0,
  author = {{SocioLens project}},
  title = {Chan and colleagues treat agency in algorithmic systems as a matter of degree, raised by four characteristics: underspecification, directness of impact, goal-directedness and long-term planning; they stress that recognizing such agency “does not absolve or shift” human responsibility.},
  year = {2026},
  date = {2026-10-16},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld01-sl-c10/v1.0/}},
  note = {Claim LD01-SL-C10, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 bb3ef0095557be97bdcd51b907c1d61b85e4f65e837336285291bcb4769231d3.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD01-SL-C10 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-16; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 16 October 2026 to build the LD-01 debate; a new Claim, first version, written from the project's LD-01 source notes, checked against full texts, official web pages or official abstracts. Block “ENTRY 10 — LD01-SL-C10” SHA-256 725953531c0e7162dae12fe6f1f5c09cb03ebd67f38a1e20ff1e5e07aec7e6ee; fixture fixtures/authored/claims/LD01-SL-C10--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD01-SL-C10 v1.0); the first version of a new Claim of the LD-01 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD01-SL-C10 v1.0" (Project Lead (Claude, AI), 2026-10-16); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 16 October 2026 to build the LD-01 debate; a new Claim, first version, written from the project's LD-01 source notes, checked against full texts, official web pages or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-CHAN-ET-AL-AGENTIC-ARXIV-2302-10329--v1.0 — basis: field 6 of ENTRY 10 — LD01-SL-C10 cites "Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-CHAN-ET-AL-AGENTIC-ARXIV-2302-10329--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Chan et al., “Harms from Increasingly Agentic Algorithmic Systems,” FAccT 2023".