Explore tweets tagged as #Explainability
Thrilled to announce that my survey paper has been accepted at #EMNLP2025 Main! 🎉. To our knowledge, this is the first comprehensive survey dedicated to multilingual explainability. 📄 Preprint: With @annalkorhonen @IAugenstein. #NLP #ExplainableAI
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Regularly auditing AI models for bias and fairness to ensure they remain fair and unbiased over time.@FractionAI_xyz Fairness An open-source toolkit developed by IBM that provides a comprehensive set of fairness metrics, bias mitigation algorithms, and explainability techniques.
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A Replication of “Explaining Why the Computer Says.No: Algorithmic Transparency Affects the Perceived.Trustworthiness of Automated Decision-Making” by Xuemei Fang, Huayu Zhou, & Song Chen confirms that explainability increases public trust.
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Statistical/Machine Learning explainability using Kernel Ridge Regression surrogates #Techtonique #DataScience #Python #rstats #MachineLearning
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💡 AI agents in healthcare: augmentation, not replacement. @Capgemini Research Institute’s 2025 recent report on agentic AI highlights four adoption keys:. 🧑⚕️👩💻 Human-in-the-loop by design. 🔍 Explainability & auditability for every action. 🔗 Workflow fit — agents live where
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🚀 The future of QA in AI:.✅ Test automation.✅ Bias & fairness checks.✅ Continuous monitoring.✅ Explainability. AI testing isn’t like traditional software—it’s dynamic, data-driven & evolving. 🔗 #GoodFirms #AI #QATesting #TechTrends
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⚠️ Everyone talks about building AI. But no one talks about the mess behind the curtain:. • Wrangling data.• Tech that breaks on Friday night.• Dependability (good luck with that).• Trust, explainability. in a black box.• Clear objectives .• Ethics, but only when it hits
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Automation is making real risk decisions now. But would you trust it?. To believe a system’s call, most people need:. 🧠 Explainability.📊 A solid track record.👀 Human oversight.🤷 Or… nothing would help. What builds your trust?. #AI #Automation #GRC #TrustInTech #6clicks.
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Latest papers: Francisco Cruz & André Mata investigate lay perceptions of explainability of psychological phenomena through two studies
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In a panel in June at the @SSSIHMSWFD initiated "Global Medical Conference", I discussed that AI governance and explainability are not exclusive to developed countries and highly resourced settings but are necessary wherever AI is implemented in healthcare service delivery.
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의료인분들은 Explainability를 중요하게 여기시는군 🥰.
오늘 아침에 회의 갔다가 잠깐 나왔던 디스커션.- 의료 데이터로 ML 예측모델 만들어서 feature importance를 분석하면 어떤 feature가 예측에 얼마나 기여하는지 알 수 있고, 대개 병인에도 관련되어있는 것이 나옴.- NLP를 이용해 free text로 뭔가 예측/분류를 하는 것이 가능한데 비슷하게 되나?.
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🔧 “Leveraging Semantics for Transparency in Industrial Systems (SENTIS)” Workshop at #SemanticsConf. Explore how semantic modeling & reasoning boost transparency and explainability in complex IT/OT, ML & AI-driven ecosystems. #SEMANTiCS2025
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Uncertainty is more important to AI than explainability [2018]
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Black boxes are out. With OpenLedger you get transparency, explainability, and on-chain proofs for every AI step. In @OpenledgerHQ Trust is a feature, not a vibe.
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Everyone loves to talk about #AI “accelerating” enterprise testing, but speed means nothing if you can’t explain the decisions it makes. 👀⚖️. In this episode of #TestTalks, @Stav_Grinshpon breaks down why real success starts with explainability, visibility, and governance, not
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A perfect prediction means little if you don’t know why. In drug discovery, explainability isn’t a nice-to-have - it’s a must. See how XAI builds trust in your models - from lab to regulator. 👉 Read more: #XAI #ExplainableAI #MachineLearning
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@Infinit_Labs.On Chain Explainability: “Why did my agent do that?”. Ever wondered why an AI agent made a particular trade or move on chain? Transparency is key. On chain explainability means every decision your agent makes is traceable and easy to understand. By publishing an
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The future of AI & blockchain is being built in the open—exactly why @OpenledgerHQ matters. By pushing for transparency, explainability & community-driven governance, they’re ensuring AI doesn’t become a black box controlled by a few, but a shared tool that empowers everyone.
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