A Unified Framework of Five Principles for AI in Society — TEI-tagged view

Luciano Floridi, Josh Cowls · 2019 · social-sciences · doi:10.1162/99608f92.8cd550d1 · TEI xml · tagged edition · index · concepts · authors
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Other fields define these differently the same word, defined another way in another discipline
accountability 4 fields · artificial intelligence 4 fields
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principle proliferation explicability2 intelligibility3 accountability8 beneficence3 non-maleficence4 bioethics5 digital ethics artificial intelligence10 thinking2 meta-autonomy2 conceptual-analysis217
Method, as described: a comparative reading of six sets chosen by three stated criteria - recent, relevant to AI and society as a whole, and published by authoritative multi-stakeholder bodies with at least national scope - mapped onto the four bioethics principles

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenona field generating ethical declarations faster than it can reconcile them, with 'similar terms often used to mean different things' and a risk the authors name as a 'market for principles'— “Unfortunately, the sheer volume of proposed principles threatens to become overwhelming and confusing, posing two potential problems.1 Either the various sets of ethical principles for AI are similar, leading to unnecessary repetition and redundancy, or, if they differ significantly, confusion and ambiguity will result instead. The worst…
claim-typemethod— “Taken together, these five principles capture every one of the 47 principles contained in the six high-profile, expert-driven documents we analysed. Moreover, each principle is included in almost every statement of principles we analyzed”
method — evidence— “For this comparative analysis, we identified six high-profile initiatives established in the interest of socially beneficial AI: 1. The Asilomar AI Principles, developed under the auspices of the Future of Life Institute”
object of study — evidence— “Each set of principles meets three basic criteria: they are recent, published within the last three years; directly relevant to AI and its impact on society as a whole (thus excluding documents specific to a particular domain, industry, or sector); and highly reputable, published by authoritative, multi-stakeholder organizations with at least…
research question — evidence— “Unfortunately, the sheer volume of proposed principles threatens to become overwhelming and confusing, posing two potential problems.1 Either the various sets of ethical principles for AI are similar, leading to unnecessary repetition and redundancy, or, if they differ significantly, confusion and ambiguity will result instead. The worst…
contribution — evidence— “Taken together, these five principles capture every one of the 47 principles contained in the six high-profile, expert-driven documents we analysed. Moreover, each principle is included in almost every statement of principles we analyzed”
mechanismthe convergence is explained by a structural resemblance between the fields, and the explanation is offered rather than tested: `Of all areas of applied ethics, bioethics is the one that most closely resembles digital ethics in dealing ecologically with new forms of agents, patients, and environments`— “This convergence can most clearly be shown by comparing the sets of principles with the four core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice (Beauchamp & Childress, 2012). The comparison should not be surprising. Of all areas of applied ethics, bioethics is the one that most closely…mechanisms[0]
mechanismand the fifth principle is argued for FUNCTIONALLY - explicability is needed because the other four cannot be checked without it: you cannot tell whether AI is beneficent without understanding what it does, nor hold anyone to account without knowing why an outcome arose— “The addition of the principle of ‘explicability,’ incorporating both the epistemological sense of ‘intelligibility’ (as an answer to the question ‘how does it work?’) and in the ethical sense of ‘accountability’ (as an answer to the question ‘who is responsible for the way it works?’), is the crucial missing piece of…mechanisms[1]
extends Beauchamp & Childress's four principles of bioethics, carried into AI ethics with a fifth added and the imperfection of the translation stated
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claim_relations[0]
supports the 1955 Dartmouth proposal's counterfactual formulation of the AI problem, kept as the working definition sixty-four years later
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claim_relations[1]
contradicts the claim that ethics is 'Europe's silver bullet' in a 'global AI battle' - answered with two words, 'We disagree', and then with the reason
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claim_relations[2]
sense`principle proliferation` - THE CONDITION THIS PAPER NAMES AND TREATS. Either the sets are similar, `leading to unnecessary repetition and redundancy`, or they differ, and `confusion and ambiguity will result instead`. The worst case is named too: a `market for principles` in which stakeholders `SHOP` for the most appealing
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senses[0]
senseTHE DIAGNOSIS, WHICH IS THIS PROJECT'S OWN THESIS IN ONE CLAUSE: `the underlying meaning of each of the principles is contested, with similar terms often used to mean different things`. A shared word list is not a shared vocabulary
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senses[1]
senseexplicability - FIVE NAMES FOR ONE PRINCIPLE, LISTED WITH THEIR SOURCES: `TRANSPARENCY` in Asilomar and EGE, `transparency` AND `ACCOUNTABILITY` in IEEE, `INTELLIGIBILITY` in AIUK, `understandable and interpretable` in the Partnership. The new term is coined to cover a thing four documents already had
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senses[2]
senseexplicability, as defined - TWO SENSES DELIBERATELY BOUND TOGETHER: the EPISTEMOLOGICAL sense of intelligibility (`how does it work?`) and the ETHICAL sense of accountability (`who is responsible for the way it works?`). One term carrying two questions on purpose
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senses[3]
senseAI - `A Research Area in Search of a Definition` in the paper's own heading. It keeps the 1955 Dartmouth formulation, reads it as A COUNTERFACTUAL (`WERE a human to behave in that way, that behaviour WOULD be called intelligent`), and then substitutes its own working phrase - `a reservoir of smart agency on tap` - justified by fitness for the corpus it is about to analyse
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senses[4]
sensebeneficence and non-maleficence - `THOUGH DO ONLY GOOD AND DO NO HARM MAY SEEM LOGICALLY EQUIVALENT, THEY ARE NOT, AND REPRESENT DISTINCT PRINCIPLES`. A near-synonymy refused explicitly, which is exactly the move most papers leave implicit
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senses[5]
sensemeta-autonomy - a coined term for `a DECIDE-TO-DELEGATE model`: humans keep the power to decide WHICH decisions to take, and any delegation must remain `overridable in principle (i.e., deciding to decide again)`
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senses[6]
controlthe six documents were selected by three declared criteria - recent, relevant to AI and society as a whole rather than to one sector, and published by authoritative multi-stakeholder bodies of at least national scope — held
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— rules out ad-hoc selection as the explanation of the convergence; the criteria are stated before the result and exclude domain-specific documents
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controls[0]
controlwhether the convergence is an artefact of where the documents come from — failed
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— rules out nothing, and the authors say so: all six came from global-scope initiatives or 'from within western liberal democracies', and the framework would benefit from perspectives 'presently un- or under-represented in our sample'
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controls[1]
controlwhether the framework's later adoption is independent evidence for it — failed
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— rules out nothing - AI4People and the EC High-Level Expert Group are counted as uptake, and the disclosure states the authors chaired, rapporteured and sat on them. THE DISCLOSURE IS COMPLETE AND THE CIRCULARITY IS STILL THERE
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controls[2]
controlwhether 'beneficence' and 'non-maleficence' are one principle wearing two names — held
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— rules out the collapse, explicitly: they 'may seem logically equivalent, they are not, and represent distinct principles', and the six documents treat them separately
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controls[3]
weightBeauchamp & Childress's four principles of bioethics, carried into AI ethics with a fifth added and the imperfection of the translation stated — 0.9
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claim_relations[0]
weightthe 1955 Dartmouth proposal's counterfactual formulation of the AI problem, kept as the working definition sixty-four years later — 0.7
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[1]
weightthe claim that ethics is 'Europe's silver bullet' in a 'global AI battle' - answered with two words, 'We disagree', and then with the reason — 0.8
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claim_relations[2]
edgebeneficence —distinct-from→ non-maleficence
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concept_edges[0]
auditdigital ethics —distinct-from→ bioethics — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the span compares AI principles with bioethics principles; distinct-from is loose.
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concept_edges[1]
outcomecontrol — held
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controls[0]
outcomecontrol — failed
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Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[1]
outcomecontrol — failed
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[2]
outcomecontrol — held
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Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[3]
limitationTHE SAMPLE IS SIX DOCUMENTS AND THE PAPER SAYS WHERE THEY COME FROM: each `emerged either from initiatives with global scope, or from within western liberal democracies`, and the framework `would undoubtedly benefit from the perspectives of regions and cultures presently un- or under-represented`
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limitations[0]
limitationthe coverage claim and the distribution claim are DIFFERENT CLAIMS AND ONLY THE FIRST IS ABSOLUTE: the five principles `capture every one of the 47`, but each principle appears in `almost every statement` - and the paper's own Table 1 shows IEEE missing autonomy and justice, and the Partnership missing autonomy
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limitations[1]
limitationTHE ADOPTION EVIDENCE INCLUDES BODIES THE AUTHORS SIT ON. AI4People and the EC High-Level Expert Group are counted as uptake, and the disclosure states that FLORIDI CHAIRED AI4PEOPLE, COWLS WAS ITS RAPPORTEUR, AND FLORIDI IS A MEMBER OF THE HLEG. Declared in full, and it is still the authors' framework being adopted by the authors' committees
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limitations[2]
limitationthe funding sits on the subject: the work was supported by an EPSRC hub AND BY FACEBOOK AND GOOGLE - two of the companies whose AI the framework is written to govern. Declared
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limitations[3]
limitationthe paper leaves its central ambiguity open and says so twice: `it is not entirely clear whether it is the people developing AI, or the technology itself, which should be encouraged not to do harm - in other words, whether it is Frankenstein or his monster against whose maleficence we should be guarding`
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limitations[4]
limitationand `justice` is left carrying more than one meaning inside the framework that is supposed to fix it: `Elsewhere ‘justice’ has still other meanings (especially in the sense of _fairness)`. The unification does not reach inside the principles
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limitations[5]
Content tags
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finding
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finding
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finding
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finding
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finding
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finding
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quantityprinciples across the six documents, claimed to be captured entirely by the five
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quantityhigh-profile initiatives analysed - Asilomar, Montreal, IEEE, EGE, AIUK, the Partnership on AI
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content_tags.quantities[1]
quantitycore principles in the resulting framework - four borrowed, one coined
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definitionexplicability
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content_tags.definitions[0]
definitionartificial intelligence
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definitionmeta-autonomy
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content_tags.definitions[2]
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptprinciple proliferation — not defined in this paper's own words; the condition of a field producing more ethical declarations than it can reconcile
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concepts[0]
conceptexplicability — not defined in this paper's own words; the fifth principle, coined here to cover intelligibility and accountability together
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concepts[1]
conceptintelligibility — not defined in this paper's own words; the epistemological half of explicability - an answer to 'how does it work?'
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concepts[2]
conceptaccountability — not defined in this paper's own words; the ethical half of explicability - an answer to 'who is responsible for the way it works?'
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concepts[3]
conceptbeneficence — not defined in this paper's own words; 'do only good' - one of the four principles imported from bioethics
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concepts[4]
conceptnon-maleficence — not defined in this paper's own words; 'do no harm' - argued to be NOT logically equivalent to beneficence
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concepts[5]
conceptbioethics — not defined in this paper's own words; the field the four core principles are imported from, chosen because it 'most closely resembles digital ethics'
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concepts[6]
conceptdigital ethics — not defined in this paper's own words; the importing field - and the import is stated to be imperfect
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concepts[7]
conceptartificial intelligence — not defined in this paper's own words; kept at the 1955 Dartmouth formulation, read as a counterfactual about BEHAVIOUR and explicitly not about thinking
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concepts[8]
conceptthinking — not defined in this paper's own words; the mental predicate the Dartmouth counterfactual explicitly does NOT license - 'It does not mean that the machine _is_ intelligent, or even _thinking'
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concepts[9]
conceptmeta-autonomy — not defined in this paper's own words; a decide-to-delegate model in which delegation stays overridable in principle
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concepts[10]

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