Unite.AI

AUGUST 25, 2023

One of the most significant issues highlighted is how the definition of responsible AI is always shifting, as societal values often do not remain consistent over time. Can focusing on Explainable AI (XAI) ever address this? For someone who is being falsely accused, explainability has a whole different meaning and urgency.

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Unite.AI

DECEMBER 19, 2024

By leveraging multimodal AI, financial institutions can anticipate customer needs, proactively address issues, and deliver tailored financial advice, thereby strengthening customer relationships and gaining a competitive edge in the market. The OECD reports over 700 regulatory initiatives in development across more than 60 countries.

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Towards AI

OCTOBER 19, 2024

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. What is Explainability AI (XAI)? It’s particularly useful in natural language processing [3].

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IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly.

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AI News

MARCH 7, 2024

Stability AI, in previewing Stable Diffusion 3, noted that the company believed in safe, responsible AI practices. OpenAI is adopting a similar approach with Sora ; in January, the company announced an initiative to promote responsible AI usage among families and educators.

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IBM Journey to AI blog

MAY 9, 2023

Success in delivering scalable enterprise AI necessitates the use of tools and processes that are specifically made for building, deploying, monitoring and retraining AI models. Responsible AI use is critical, especially as more and more organizations share concerns about potential damage to their brand when implementing AI.

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Unite.AI

DECEMBER 13, 2023

AI transforms cybersecurity by boosting defense and offense. However, challenges include the rise of AI-driven attacks and privacy issues. Responsible AI use is crucial. The future involves human-AI collaboration to tackle evolving trends and threats in 2024.

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Unite.AI

MARCH 18, 2025

By observing ethical data collection, we succeed business-wise while contributing to the establishment of a transparent and responsible AI ecosystem. Another notable trend is the reliance on synthetic data used for data augmentation, wherein AI generates data that supplements datasets gathered from real-world scenarios.

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TransOrg Analytics

FEBRUARY 11, 2025

These are just a few ways Artificial Intelligence (AI) silently influences our daily lives. As AI continues integrating into every aspect of society, the need for Explainable AI (XAI) becomes increasingly important. What is Explainable AI? Why is Explainable AI Important?

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IBM Journey to AI blog

OCTOBER 16, 2023

Foundation models are widely used for ML tasks like classification and entity extraction, as well as generative AI tasks such as translation, summarization and creating realistic content. The development and use of these models explain the enormous amount of recent AI breakthroughs. Increase trust in AI outcomes.

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Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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IBM Journey to AI blog

DECEMBER 4, 2023

In addition, the CPO AI Ethics Project Office supports all of these initiatives, serving as a liaison between governance roles, supporting implementation of technology ethics priorities, helping establish AI Ethics Board agendas and ensuring the board is kept up to date on industry trends and company strategy.

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ODSC - Open Data Science

OCTOBER 21, 2024

As AI systems become increasingly embedded in critical decision-making processes and in domains that are governed by a web of complex regulatory requirements, the need for responsible AI practices has never been more urgent. But let’s first take a look at some of the tools for ML evaluation that are popular for responsible AI.

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Pickl AI

OCTOBER 8, 2024

Summary: This blog discusses Explainable Artificial Intelligence (XAI) and its critical role in fostering trust in AI systems. One of the most effective ways to build this trust is through Explainable Artificial Intelligence (XAI). What is Explainable AI (XAI)? What is Explainable AI (XAI)?

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NYU Center for Data Science

JUNE 16, 2023

Motivated by applications in healthcare and criminal justice, Umang studies how to create algorithmic decision-making systems endowed with the ability to explain their behavior and adapt to a stakeholder’s expertise to improve human-machine team performance. His work has been covered in press (e.g., UK Parliament POSTnote , NIST ).

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IBM Journey to AI blog

MARCH 4, 2024

The scale and impact of next-generation AI emphasize the importance of governance and risk controls. An AI+ enterprise mitigates potential harm by implementing robust measures to secure, monitor and explain AI models, as well as monitoring governance, risk and compliance controls across the hybrid cloud environment.

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ODSC - Open Data Science

JUNE 7, 2023

Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive.

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Unite.AI

OCTOBER 25, 2024

In the Expand phase, AI initiatives scale through LLMOps, AI COE Setup, and Responsible AI Implementation, embedding AI into the enterprise to drive innovative outcomes. Can you explain how SLK’s AI-powered solutions, like TrackShieldAI and PeakPerform, drive efficiency and productivity in manufacturing?

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ODSC - Open Data Science

MARCH 20, 2025

Tuesday is also the first day of the AI Expo and Demo Hall , where you can connect with our conference partners and check out the latest developments and research from leading tech companies. At night, well have our Welcome Networking Reception to kick off the firstday.

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Pickl AI

FEBRUARY 17, 2025

Transparency and Explainability As Machine Learning models become increasingly complex, ensuring transparency and explainability remains a significant challenge. Approximately 44% of organisations express concerns about transparency in AI adoption. Why Is Explainability Important in Machine Learning?

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Unite.AI

JANUARY 12, 2024

Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development. The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones.

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NVIDIA

MARCH 1, 2024

Transparency: Making AI Explainable To create a trustworthy AI model, the algorithm can’t be a black box — its creators, users and stakeholders must be able to understand how the AI works to trust its results. NVIDIA is also part of the National Institute of Standards and Technology’s U.S.

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ODSC - Open Data Science

FEBRUARY 27, 2024

Interactive Explainable AI Meg Kurdziolek, PhD | Staff UX Researcher | Intrinsic.ai Although current explainable AI techniques have made significant progress toward enabling end-users to understand the why behind a prediction, to effectively build trust with an AI system we need to take the next step and make XAI tools interactive.

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Marktechpost

DECEMBER 11, 2024

Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 models adhered to LG AI Research s Responsible AI Development Framework, prioritizing data governance, ethical considerations, and risk management. model scored 70.2.

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ODSC - Open Data Science

FEBRUARY 18, 2025

Prompt Engineers: Also known as AI Interaction Specialists, these experts craft and refine the prompts used to interact with and guide AI models, ensuring they generate high-quality, contextually relevant content and responses. Explainable AI (XAI) techniques are crucial for building trust and ensuring accountability.

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Towards AI

OCTOBER 7, 2023

Last Updated on October 9, 2023 by Editorial Team Author(s): Lye Jia Jun Originally published on Towards AI. Balancing Ethics and Innovation: An Introduction to the Guiding Principles of Responsible AI Sarah, a seasoned AI developer, found herself at a moral crossroads. The other safeguards personal data but lacks speed.

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The MLOps Blog

JUNE 27, 2023

This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking. Truera offers capabilities such as model debugging, explainability, and fairness assessment to gain insights into model behavior and identify potential issues or biases. Learn more from the documentation.

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Pickl AI

SEPTEMBER 17, 2024

AI in Security Automation and Incident Response AI is revolutionising security automation and incident response by enabling faster, more efficient, and more accurate responses to cyber threats.

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ODSC - Open Data Science

JUNE 8, 2023

Keynotes Both in-person and virtually, we had some amazing keynote speakers that told the audience about their research, expertise, use cases, or state-of-the-art developments.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Advanced ML Algorithms & EnsembleMethods Hyperparameter Tuning & Model Optimization AutoML & Real-Time MLSystems Explainable AI & EthicalAI Time Series Forecasting & NLP Techniques Who Should Attend: ML Engineers, Data Scientists, and Technical Practitioners working on production-level ML solutions.

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Pickl AI

JULY 14, 2023

Robotics also witnessed advancements, with AI-powered robots becoming more capable in navigation, manipulation, and interaction with the physical world. Explainable AI and Ethical Considerations (2010s-present): As AI systems became more complex and influential, concerns about transparency, fairness, and accountability arose.

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AI News

APRIL 25, 2024

The current incarnation of Pryon has aimed to confront AI’s ethical quandaries through responsible design focused on critical infrastructure and high-stakes use cases. “[We We wanted to] create something purposely hardened for more critical infrastructure, essential workers, and more serious pursuits,” Jablokov explained.

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Pickl AI

AUGUST 1, 2024

Techniques such as explainable AI (XAI) aim to provide insights into model behaviour, allowing users to gain confidence in AI-driven decisions, especially in critical fields like healthcare and finance.

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Snorkel AI

MARCH 19, 2024

Vertex AI, Google’s comprehensive AI platform, plays a pivotal role in ensuring a safe, reliable, secure, and responsible AI environment for production-level applications. Vertex AI provides a suite of tools and services that cater to the entire AI lifecycle, from data preparation to model deployment and monitoring.

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Snorkel AI

MARCH 19, 2024

Vertex AI, Google’s comprehensive AI platform, plays a pivotal role in ensuring a safe, reliable, secure, and responsible AI environment for production-level applications. Vertex AI provides a suite of tools and services that cater to the entire AI lifecycle, from data preparation to model deployment and monitoring.

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Unite.AI

JANUARY 20, 2025

Transparency = Good Business AI systems operate using vast datasets, intricate models, and algorithms that often lack visibility into their inner workings. This opacity can lead to outcomes that are difficult to explain, defend, or challengeraising concerns around bias, fairness, and accountability.

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Unite.AI

NOVEMBER 29, 2023

For example, Algorithmic Fact-Checking Solutions, including Explainable AI (XAI) , assume a central role by providing a comprehensive overview of AI-driven techniques. The Bottom Line In conclusion, AI watchdogs are indispensable in safeguarding elections and adapting to evolving disinformation tactics.

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