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pith:2026:LTEXOPHKH7YMSK3BYGOSEARTDA
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Explainable AI Isn't Enough! Rethinking Algorithmic Contestability

Gunnar K\"onig, Kristof Meding, Timo Freiesleben

Standard XAI tools like counterfactuals only flag nearby errors and fall short of providing grounds to overturn algorithmic decisions.

arxiv:2605.16041 v1 · 2026-05-15 · stat.ML · cs.LG

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Claims

C1strongest claim

Standard XAI explanations such as counterfactuals, LIME, or Anchors, even when combined with human intuitions about decision continuity or monotonicity, reveal only errors in the neighborhood of the individual, but provide insufficient grounds for overturning the decision at hand.

C2weakest assumption

That the three identified types of evidence (predictive multiplicity, incorrect feature values, and neglected overruling evidence) render decisions normatively indefensible according to the decision maker's own ethical standards, as stated in the section proposing the operational definition of contestability.

C3one line summary

The paper defines algorithmic contestability as identifying evidence to overturn potentially incorrect decisions and identifies three types of such evidence that make decisions normatively indefensible under the decision maker's standards.

References

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[1] A practical guide, 1st ed., Cham: Springer International Publishing , volume= 2017
[2] Joint European conference on machine learning and knowledge discovery in databases , pages= 2019
[3] European Union , year=
[4] Philosophy of Science , volume= 2014
[5] New essays on semantic externalism and self-knowledge , pages=

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Receipt and verification
First computed 2026-05-20T00:01:50.381946Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

5cc9773cea3ff0c92b61c19d220233180f877f50f20305cf0523f73a52dbdc41

Aliases

arxiv: 2605.16041 · arxiv_version: 2605.16041v1 · doi: 10.48550/arxiv.2605.16041 · pith_short_12: LTEXOPHKH7YM · pith_short_16: LTEXOPHKH7YMSK3B · pith_short_8: LTEXOPHK
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/LTEXOPHKH7YMSK3BYGOSEARTDA \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 5cc9773cea3ff0c92b61c19d220233180f877f50f20305cf0523f73a52dbdc41
Canonical record JSON
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