Explainability is the core of finance! Dimitri Bianco, Founder of Fancy Quant, explains why without explainable models, trading is just gambling and how deviations like LTCM highlight the risks. Faisal Mohammad from Zerodha discusses AI regulation and how firms need to prepare

By combining autonomy, transparency, explainability, compliance checks, identity safeguards, and early risk detection, AI agents create a secure digital fabric that enhances trust and strengthens the integrity of interactions across organizations. Microblog by @antgrasso

How an #LLM Actually “Thinks”: Explainability Is About Constraints #structuralcoherence #aisafety https://t.co/NPW7u9F57j

Infor CIO: Enterprise AI Needs Explainability, Not Just Automation @techshotsapp #AI #Enterprise #Automation https://t.co/GzrS2MhP3Z

AI-Aided Decision-Making in Education: Uncertainty, Explainability, and Human Responsibility https://t.co/a50NpEHP8i

7 Foundational Principles: 1. Trust as the foundation 2. People-first approach (human-centricity) 3. Fairness and equity to prevent bias and promote inclusion 4. Accountability based on risk and role 5. Understandability by design ensuring transparency and explainability

Explainability in #AI: The Missing Link in Digital Onboarding - https://t.co/5KYu0r4IPv | #technews #technology #futuretech

#MachineLearning and #AI Model Explainability and Interpretability https://t.co/oCypZZWTaw v/ @AnalyticsVidhya #AIEthics Cc @KirkDBorne @SpirosMargaris @Fabriziobustama @HaroldSinnott @dinisguarda @gvalan

Explainability in #AI: The Missing Link in Digital Onboarding - https://t.co/5KYu0r4IPv | #technews #technology #futuretech

Excited to be at #EMNLP2025 in Suzhou 🇨🇳! I’ll present three papers, and I'm happy to chat about any of these works! 🏅 "Multi-Domain Explainability of Preferences" - Oral, Interpretability 2, Nov 5, 17:30 (A104-105) w/ @roireichart Liat Ein-Dor 🧠 "Dementia Through Different

Trying to learn something new - ML explainability with SHAP #pybay2025

"What eGain saw with AI Agents in CX beyond Garbage In, Garbage Out.” At #eGainSolve25 Chicago Varsha Thalange, VP of Product Management, shared how eGain’s AI Agent 2 is redefining the future of AI in CX, powered by trusted knowledge, context, and explainability. #eGain

Web2 hides how models make decisions — and who profits from the data 🤖💡 @OpenLedgerHQ sees a path forward: Web3 can bring explainability and data attribution to AI systems. When models become transparent and contributors are rewarded, the entire ecosystem changes 🤯

AIが導いた“最適な提案”── けれど、その判断の根拠を説明できなければ、 私たちは患者さんに説明することもできません💬 「なぜこの薬？」「他の候補との違いは？」 患者さんからの問いに、 “AIがそう言ったから”では通用しない時代です。 AIの**Explainability（説明可能性）**とは、

Having humans report to machines challenges our notions of agency, dignity, and fairness. How does accountability work when an algorithm makes a critical decision? Organizations will need to invest in #AI literacy, explainability, and ethics frameworks https://t.co/H3BUhpGYPR

3 Doctoral Fellows are needed as part of the GREET (Generative Explainee-aware Explainability & Transparency in Proactive Cyber-Physical Eco- Environments) Doctoral Network, in Edinburgh Napier University. More information and how to apply: https://t.co/SLG8MoY4Lo Pls, Repost.

Explainability Techniques for LLMs & AI Agents: Methods, Tools & Best Practices Learn the best explainability (XAI) techniques for LLMs and AI agents. Explore methods, tools, and best practices for interpretable and transparent AI. 🔗 https://t.co/79qMHUZTLN 💬 Share your

Explainability is operational: tie model explanations to ticketing, incident response, and SLAs so transparency supports governance and audits. Join the session at #ISACAKEGRC2025 GRC360 Africa Conference Isaca Kenya Chapter @isaca_kenya.