---
OA_place: repository
OA_type: green
_id: '22103'
abstract:
- lang: eng
  text: "Modern AI systems increasingly rely on opaque, highly complex models whose
    inner workings remain inaccessible even to experts. This opacity creates challenges
    for trust, accountability, and compliance with\r\nemerging regulatory expectations
    such as the “right to an explanation”. While traditional explainability methods—feature
    attributions, counterfactuals, surrogate models—and interpretable model classes
    provide valuable insights for engineers, they often fall short of delivering the
    contextual, conversational explanations that\r\nreal users expect. Large Language
    Models (LLMs) offer a promising new avenue for explanation due to their\r\nability
    to engage interactively, adapt to user needs, and translate technical outputs
    into more accessible reasoning. However, their tendencies toward hallucination,
    conflict avoidance, and oversimplification introduce\r\nserious risks when used
    as explanatory agents. This paper analyzes these opportunities and limitations,
    examines verification strategies for ensuring explanation fidelity, and situates
    LLM-generated explanations within\r\nbroader concerns about public trust. The
    paper concludes by outlining best practices and future research directions for
    building robust, verifiable, and human-aligned explanation systems."
acknowledgement: "This work has been supported by the European Research Council under
  Grant No.: ERC-2020-AdG\r\n101020093. LLM–based tools have been used as\r\nwriting
  assistance to help improve presentation.\r\n"
article_processing_charge: No
author:
- first_name: Filip
  full_name: Cano Cordoba, Filip
  id: 708cad98-e86a-11ef-8098-bdae2d7c6af1
  last_name: Cano Cordoba
  orcid: 0000-0002-0783-904X
citation:
  ama: 'Cano Cordoba F. Explaining decisions one conversation at a time: Opportunities
    and risks of LLMs as explainability assistants. In: <i>Proceedings of the 18th
    International Conference on Agents and Artificial Intelligence</i>. Vol 5. Science
    and Technology Publications; 2026:4689-4696. doi:<a href="https://doi.org/10.5220/0014483200004052">10.5220/0014483200004052</a>'
  apa: 'Cano Cordoba, F. (2026). Explaining decisions one conversation at a time:
    Opportunities and risks of LLMs as explainability assistants. In <i>Proceedings
    of the 18th International Conference on Agents and Artificial Intelligence</i>
    (Vol. 5, pp. 4689–4696). Marbella, Spain: Science and Technology Publications.
    <a href="https://doi.org/10.5220/0014483200004052">https://doi.org/10.5220/0014483200004052</a>'
  chicago: 'Cano Cordoba, Filip. “Explaining Decisions One Conversation at a Time:
    Opportunities and Risks of LLMs as Explainability Assistants.” In <i>Proceedings
    of the 18th International Conference on Agents and Artificial Intelligence</i>,
    5:4689–96. Science and Technology Publications, 2026. <a href="https://doi.org/10.5220/0014483200004052">https://doi.org/10.5220/0014483200004052</a>.'
  ieee: 'F. Cano Cordoba, “Explaining decisions one conversation at a time: Opportunities
    and risks of LLMs as explainability assistants,” in <i>Proceedings of the 18th
    International Conference on Agents and Artificial Intelligence</i>, Marbella,
    Spain, 2026, vol. 5, pp. 4689–4696.'
  ista: 'Cano Cordoba F. 2026. Explaining decisions one conversation at a time: Opportunities
    and risks of LLMs as explainability assistants. Proceedings of the 18th International
    Conference on Agents and Artificial Intelligence. ICAART: International Conference
    on Agents and Artificial Intelligence vol. 5, 4689–4696.'
  mla: 'Cano Cordoba, Filip. “Explaining Decisions One Conversation at a Time: Opportunities
    and Risks of LLMs as Explainability Assistants.” <i>Proceedings of the 18th International
    Conference on Agents and Artificial Intelligence</i>, vol. 5, Science and Technology
    Publications, 2026, pp. 4689–96, doi:<a href="https://doi.org/10.5220/0014483200004052">10.5220/0014483200004052</a>.'
  short: F. Cano Cordoba, in:, Proceedings of the 18th International Conference on
    Agents and Artificial Intelligence, Science and Technology Publications, 2026,
    pp. 4689–4696.
conference:
  end_date: 2026-03-08
  location: Marbella, Spain
  name: 'ICAART: International Conference on Agents and Artificial Intelligence'
  start_date: 2026-03-05
corr_author: '1'
das_tickbox: '0'
date_created: 2026-06-21T22:03:00Z
date_published: 2026-04-01T00:00:00Z
date_updated: 2026-06-24T08:37:00Z
day: '01'
department:
- _id: ToHe
doi: 10.5220/0014483200004052
ec_funded: 1
intvolume: '         5'
keyword:
- Explainable AI
- Large Language Models
- Trust in AI
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://filipcano.org/files/icaart26llm.pdf
month: '04'
oa: 1
oa_version: Accepted Version
page: 4689-4696
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: Proceedings of the 18th International Conference on Agents and Artificial
  Intelligence
publication_identifier:
  eissn:
  - 2184-433X
  isbn:
  - '9789897587962'
  issn:
  - 2184-3589
publication_status: published
publisher: Science and Technology Publications
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: 'Explaining decisions one conversation at a time: Opportunities and risks of
  LLMs as explainability assistants'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 5
year: '2026'
...