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.

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Composite AI Explainability Black Box AI Explainable AI 182

Chatbots Life

MAY 23, 2023

Responsible AI — deployment framework I asked ChatGPT and Bard to share their thoughts on what policies governments have to put in place to ensure responsible AI implementations in their countries. They should also work to raise awareness of the importance of responsible AI among businesses and organizations.

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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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Explainability Explainable AI Natural Language Processing Prompt Engineer 105

Google Research AI blog

MARCH 16, 2023

The Impact Lab team, part of Google’s Responsible AI Team , employs a range of interdisciplinary methodologies to ensure critical and rich analysis of the potential implications of technology development. We examine systemic social issues and generate useful artifacts for responsible AI development.

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AWS Machine Learning Blog

NOVEMBER 25, 2024

ISO/IEC 42001 is an international management system standard that outlines requirements and controls for organizations to promote the responsible development and use of AI systems. Responsible AI is a long-standing commitment at AWS. At Snowflake, delivering AI capabilities to our customers is a top priority.

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Artificial Intelligence Artificial Intelligence Responsible AI Explainability 115

IBM Journey to AI blog

JANUARY 15, 2024

To develop responsible AI, government leaders must carefully prepare their internal data to harness the full potential of both AI and generative AI. Setting responsible standards is a crucial government role, requiring the integration of responsibility from the start, rather than as an afterthought.

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Generative AI Responsible AI Neural Network Natural Language Processing 200

Unite.AI

DECEMBER 1, 2023

SHAP's strength lies in its consistency and ability to provide a global perspective – it not only explains individual predictions but also gives insights into the model as a whole. This method requires fewer resources at test time and has been shown to effectively explain model predictions, even in LLMs with billions of parameters.

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LLM Machine Learning Explainability Algorithm 264

Unite.AI

JULY 1, 2024

It doesn’t matter if you are an online consumer or a business using that information to make key decisions – responsible AI systems allow all of us to fully and better understand information, as you need to ensure what is coming out of Generative AI is accurate and reliable.

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Explainability Software Engineer AI Modeling Responsible AI 173

Unite.AI

MARCH 27, 2024

Likewise, ethical considerations, including bias in AI algorithms and transparency in decision-making, demand multifaceted solutions to ensure fairness and accountability. Addressing bias requires diversifying AI development teams, integrating ethics into algorithmic design, and promoting awareness of bias mitigation strategies.

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AI AI Natural Language Processing Computer Vision 278

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.

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Metadata Explainability Automation Explainable AI 220

Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It also introduces Google’s 7 AI principles.

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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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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.

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Unite.AI

NOVEMBER 4, 2024

Ex-Human was born from the desire to push the boundaries of AI even further, making it more adaptive, engaging, and capable of transforming how people interact with digital characters across various industries. Ex-human uses AI avatars to engage millions of users.

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Conversational AI Explainability Chatbots AI 246

NVIDIA

MARCH 1, 2024

Trustworthy AI initiatives recognize the real-world effects that AI can have on people and society, and aim to channel that power responsibly for positive change. What Is Trustworthy AI? Trustworthy AI is an approach to AI development that prioritizes safety and transparency for those who interact with it.

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Marktechpost

NOVEMBER 22, 2024

It helps developers identify and fix model biases, improve model accuracy, and ensure fairness. Arize helps ensure that AI models are reliable, accurate, and unbiased, promoting ethical and responsible AI development. It’s a valuable tool for building and deploying AI models that are fair and equitable.

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Automation Explainability Data Analysis Machine Learning 111

Unite.AI

APRIL 30, 2024

Ethical Considerations and Challenges Ethical considerations and challenges are significant in the development of self-reflective AI systems. Transparency and accountability are at the forefront, necessitating explainable systems that can justify their decisions.

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Chatbots Neural Network BERT OpenAI 204

IBM Journey to AI blog

JANUARY 10, 2024

But even with the myriad benefits of AI, it does have noteworthy disadvantages when compared to traditional programming methods. AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended.

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Artificial Intelligence Artificial Intelligence Neural Network Algorithm 229

Towards AI

JULY 27, 2024

Dedicated to safety and security It is a well-known fact that Anthropic prioritizes responsible AI development the most, and it is clearly seen in Claude’s design. This generative AI model is trained on a carefully curated dataset thus it minimizes biases and factual errors to a large extent.

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Marktechpost

NOVEMBER 23, 2023

This technical prowess positions Leonardo as a crucial asset for advancing AI applications across Europe​​. REAL AI’s unique opportunity- “We aim to provide Europe’s answer to responsible AI development. Together with UNINA and AI supercomputer cluster ‘Leonardo’, we can make this possible”.

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Large Language Models LLM AI AI 126

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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Snorkel AI

FEBRUARY 22, 2023

At Snorkel AI’s 2022 Future of Data-Centric AI virtual conference, Eisenberg gave a short presentation on the way he and his colleagues are working to operationalize the assessment of responsible AI systems using a Credo AI tool called Lens. My name is Ian Eisenberg, and I head the data science team at Credo AI.

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Snorkel AI

FEBRUARY 22, 2023

At Snorkel AI’s 2022 Future of Data-Centric AI virtual conference, Eisenberg gave a short presentation on the way he and his colleagues are working to operationalize the assessment of responsible AI systems using a Credo AI tool called Lens. My name is Ian Eisenberg, and I head the data science team at Credo AI.

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Marktechpost

NOVEMBER 28, 2024

The platform has enabled groundbreaking solutions that showcase AI’s transformative potential. Pfizer has accelerated critical medicine research and delivery timelines, while Intuit explains complex tax calculations for millions of users.

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Marktechpost

DECEMBER 6, 2023

It can understand, explain, and generate high-quality code in multiple programming languages, a feature that positions it as one of the leading foundation models for coding. This capability is expected to facilitate breakthroughs in various fields, including science and finance. Check out the Technical Report and Google Release Post.

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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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IBM Journey to AI blog

AUGUST 16, 2023

” We’ll come back to this story in a minute and explain how it relates to ChatGPT and trustworthy AI. As the world of artificial intelligence (AI) evolves, new tools like OpenAI’s ChatGPT have gained attention for their conversational capabilities.

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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.

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Artificial Corner

AUGUST 3, 2023

Twitter’s CEO, Sarah Jackson, explained that the rebranding is part of a strategic effort to expand the platform’s offerings beyond its traditional microblogging format. The formation of the industry body “Frontier Model Forum” further solidifies their dedication to ensuring responsible AI development.

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NYU Center for Data Science

JANUARY 3, 2024

We wanted to develop a framework for understanding the toxicity of language that would take into account more than just what’s shown explicitly in the text,” Gabriel explains. This focus on the implicit meanings and the social context of language in AI models is crucial in an era where digital communication is omnipresent.

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NYU Center for Data Science

DECEMBER 12, 2023

The Center for Responsible AI (NYU R/AI) is leading this charge by embedding ethical considerations into the fabric of artificial intelligence research and development. The Center for Responsible AI is a testament to NYU’s commitment to pioneering research that upholds and advances these ideals.

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Unite.AI

AUGUST 14, 2024

Anand Kannappan is Co-Founder and CEO of Patronus AI , the industry-first automated AI evaluation and security platform to help enterprises catch LLM mistakes at scale. Previously, Anand led ML explainability and advanced experimentation efforts at Meta Reality Labs. What initially attracted you to computer science?

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LLM AI AI Large Language Models 130

Becoming Human

APRIL 19, 2024

Transparency and Explainability Transparency in AI systems is crucial for building trust among users and stakeholders. This lack of explainability raises concerns about accountability and the potential for unintended consequences. AI consultants must prioritize transparency by adopting models and techniques for interpretability.

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AI AI Responsible AI Artificial Intelligence 102

AWS Machine Learning Blog

MAY 9, 2024

Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI. To provide ethical integrity , an AI/ML CoE helps integrate robust guidelines and safeguards across the AI/ML lifecycle in collaboration with stakeholders.

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NYU Center for Data Science

NOVEMBER 26, 2024

CDS Faculty Fellow Umang Bhatt l eading a practical workshop on Responsible AI at Deep Learning Indaba 2023 in Accra In Uganda’s banking sector, AI models used for credit scoring systematically disadvantage citizens by relying on traditional Western financial metrics that don’t reflect local economic realities.

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Deep Learning Responsible AI Robotics Machine Learning 50

Towards AI

FEBRUARY 14, 2023

Another important trend to watch in the future of generative AI is the growing focus on ethical and responsible AI development. With the potential of AI to impact society in profound ways, it is crucial that we take a responsible approach to its development and use.

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Pickl AI

DECEMBER 16, 2024

With the global AI market exceeding $184 billion in 2024a $50 billion leap from 2023its clear that AI adoption is accelerating. This blog aims to help you navigate this growth by addressing key enablers of AI development. Key Takeaways Reliable, diverse, and preprocessed data is critical for accurate AI model training.

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