
TRAIF 2026—Communicating AI Ethics: In Research And Practice
Keywords
Summary
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Critical Evaluation
Value of the Information & Strength of the Argument
VALUE OF INFORMATION: The presentations offer useful but not groundbreaking perspectives. Andrea Martin provides a clear, industry-oriented overview of AI governance, emphasizing practical implementation within a large corporation. The NIST framework example and the mainframe discussion add concrete elements. Boris Abramovic presents a thoughtful argument for using arts to improve public participation, supporting it with references to literature and examples from his lab. Loreta Tauginienė’s segment is more generic, likely describing procedural aspects without deep analysis. The arguments are logically structured, but the depth is limited due to the short format and multiple speakers. No conflicting viewpoints are presented, and all align with mainstream AI ethics discourse.
Scientific Rigor, Source Quality, Title Accuracy
SCIENTIFIC RIGOR AND SOURCE QUALITY: The speakers reference authoritative sources like NIST AI Risk Management Framework, OECD frameworks, EU AI Act, and GDPR, which are credible but not detailed. The description provides links to alignAI, IEAI, and the forum website, which are relevant institutional sources. However, no direct citations to specific studies are given in the transcript. The title matches the content. The session is part of a funded EU project (alignAI), which adds some credibility. Comment analysis: no comments are provided, so no public trends can be assessed.
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Title / Content Match
The title accurately reflects the content: a forum session on communicating AI ethics in research and practice, covering governance frameworks, art-based public engagement, and ethical review processes.
Quality & Reliability
7/10
The talks are delivered by experienced professionals and academics (IBM, University of Vienna, Kaunas University of Technology). They reference established frameworks (NIST, OECD, EU AI Act) and academic literature, but no empirical data or detailed citations are provided in the transcript. The technical depth varies, with some parts are more conceptual than hands-on.
Key Moments
Markers derived by PSI from the transcript: the creator did not define chapters.
- Andrea Martin begins presenting on AI ethics as an enterprise value at IBM, discussing the shift from trustworthiness to AI governance.
- She explains the three IBM principles (augmented intelligence, data ownership, transparency) and five pillars of responsible AI.
- Discussion on the IBM mainframe as an example of embedded AI governance features, including synthetic data and drift detection.
- Boris Abramovic starts his talk on art-based approaches for public participation in AI ethics, referencing critiques of conventional participation.
- He presents examples from the Experimental Game Cultures lab, like facial recognition games and ChatGPT role-play, emphasizing emotional and future-oriented engagement.
- Loreta Tauginienė begins her presentation on ethical oversight by research ethics committees and the communication of approval processes.
Cited Sources
- alignAI — EU Horizon project funding and information mentioned in description.
- Institute for Ethics in Artificial Intelligence (IEAI) — Organizer of the forum, referenced in description.
- IEAI Newsletter — Subscription link for updates, provided in description.
- Responsible AI Forum — Official website of the forum, linked in description.
- Amerikahaus — Venue provider, credited in description.
- IEAI Events — Page for other IEAI events, linked in description.
Concurring Sources
- NIST AI Risk Management Framework — Used by IBM and consistent with best practices in AI governance.
- EU AI Act — Mentioned as a compliance driver, aligning with the sector's regulatory direction.
Dissenting Sources
- Anthropic's claim on mainframe COBOL translation — Andrea Martin disputes the idea that mainframes are obsolete and easy to replace, suggesting that such claims overlook business integration complexities.
Contribution & Novelties
This session provides a concrete example of how an industry leader (IBM) operationalizes AI ethics through governance frameworks, and how artistic methods can enhance public understanding and engagement. The mainframe example is a novel angle rarely discussed. The combination of industry, arts, and academic perspectives in one forum highlights the multifaceted nature of communicating AI ethics.
Pour aller plus loin :
- NIST AI Risk Management Framework — Central to Andrea Martin’s talk, this is a key reference for AI governance.
- EU Artificial Intelligence Act — The legal framework mentioned across presentations, critical for understanding compliance.
- Deliberative mini-publics — A concept critiqued by Boris Abramovic, relevant to public participation in science communication.
- IBM’s AI Ethics principles — Official IBM page that elaborates on the principles Andrea Martin described.
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Radar Profile
The radar profile shows moderate scores across all dimensions, with quality and reliability slightly higher than quantity and technical depth, reflecting a balanced but not outstanding session. The low view count limits public impact, but the content is solid for an academic forum.