Unite.AI

APRIL 9, 2024

As organizations strive for responsible and effective AI, Composite AI stands at the forefront, bridging the gap between complexity and clarity. The Need for Explainability The demand for Explainable AI arises from the opacity of AI systems, which creates a significant trust gap between users and these algorithms.

Composite AI 182

Composite AI Explainability Black Box AI Explainable AI 182

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.

Explainability 246

Explainability Explainable AI AI AI 246

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.

Automation 147

Automation AI AI Artificial Intelligence 147

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].

Explainability 105

Explainability Explainable AI Natural Language Processing Prompt Engineering 105

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.

Prompt Engineering 338

Prompt Engineering Prompt Engineer OpenAI Large Language Models 338

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.

Data Scientist 234

Data Scientist Metadata Explainability Responsible AI 234

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.

Metadata 227

Metadata Explainability Automation Responsible AI 227

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.

Explainability 290

Explainability AI AI Responsible AI 290

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.

AI Modeling 147

AI Modeling Automation Explainable AI AI Chatbots 147

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?

Explainable AI 52

Explainable AI Explainability Convolutional Neural Networks Neural Network 52

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.

Metadata 220

Metadata Explainability Automation Explainable AI 220

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.

Explainable AI 52

Explainable AI Explainability Deep Learning Neural Network 52

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.

Metadata 228

Metadata AI AI Explainable AI 228

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.

Responsible AI 52

Responsible AI ML Data Scientist Machine Learning 52

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)?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

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 ).

Machine Learning 119

Machine Learning Explainability Artificial Intelligence Artificial Intelligence 119

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.

AI 300

AI AI Artificial Intelligence Artificial Intelligence 300

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.

Explainable AI 93

Explainable AI Data Science Responsible AI Machine Learning 93

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?

Automation 147

Automation Explainability Responsible AI AI Automation 147

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.

Data Science 52

Data Science LLM NLP Software Engineer 52

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?

Machine Learning 52

Machine Learning Algorithm Explainability Data Quality 52

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.

Generative AI 189

Generative AI Neural Network ChatGPT OpenAI 189

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.

AI 137

AI AI Algorithm Artificial Intelligence 137

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.

Explainable AI 52

Explainable AI Data Science Responsible AI Machine Learning 52

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.

AI Researcher 87

AI Researcher AI Research Generative AI AI 87

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.

Explainability 59

Explainability Automation AI AI 59

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.

Explainability 64

Explainability AI AI Algorithm 64

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.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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.

Machine Learning 52

Machine Learning IDP AI Algorithm 52

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.

Data Science 52

Data Science Machine Learning NLP Software Engineer 52

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.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

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.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

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.

Responsible AI 338

Responsible AI Big Data AI AI 338

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.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52

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.

Data Scientist 52

Data Scientist LLM Chatbots AI 52

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.

Data Scientist 52

Data Scientist AI Chatbots AI 52

Pickl AI

DECEMBER 29, 2024

Summary: Responsible AI ensures AI systems operate ethically, transparently, and accountably, addressing bias and societal risks. Through ethical guidelines, robust governance, and interdisciplinary collaboration, organisations can harness AI’s transformative power while safeguarding fairness and inclusivity.

Responsible AI 52

Responsible AI Black Box AI Artificial Intelligence Artificial Intelligence 52