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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AI News

JULY 31, 2024

As the EU’s AI Act prepares to come into force tomorrow, industry experts are weighing in on its potential impact, highlighting its role in building trust and encouraging responsible AI adoption. “The greatest problem facing AI developers is not regulation, but a lack of trust in AI,” Wilson stated.

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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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AI News

OCTOBER 22, 2024

The legislation establishes a first-of-its-kind regulatory framework for AI systems, employing a risk-based approach that categorises AI applications based on their potential impact on safety, human rights, and societal wellbeing.

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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

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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ODSC - Open Data Science

JULY 17, 2024

This discussion will explore the key pillars of strong AI governance and how responsible AI practices can differentiate products and brands, demystify legal frameworks, and explain why data and AI governance are crucial for organizational success.

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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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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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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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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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Allen AI

JULY 27, 2023

The AI2 ImpACT License Project: Open, Responsible AI Licenses for the Common Good A new way to think about AI licensing By Jen Dumas, Crystal Nam, Will Smith, David Atkinson, and Nicole DeCario AI Is Everywhere; What Are the Risks? We welcome your feedback on this initiative: please reach us at ai2impact@allenai.org.

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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.

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Pickl AI

APRIL 26, 2024

This can lead to discriminatory outcomes, for example, an AI-powered hiring tool trained on historical data might perpetuate existing biases against certain demographics. Ensuring fairness and mitigating bias in AI development is crucial. To reap the benefits and mitigate the risks, we must approach AI development responsibly.

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Viso.ai

SEPTEMBER 12, 2024

It provides that model developers can download the source code and redistribute copies provided they attribute the owner of the content, but no modification in the source file can be developed nor any commercial use. Data-Centric Licenses Data is the backbone of AI, and licensing data sets is a significant aspect of AI development.

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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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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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Dlabs.ai

SEPTEMBER 24, 2024

Instead of applying uniform regulations, it categorizes AI systems based on their potential risk to society and applies rules accordingly. This tiered approach encourages responsible AI development while ensuring appropriate safeguards are in place. Also, be transparent about the data these systems use.

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TensorFlow

MAY 10, 2023

This year at Google I/O, we highlighted how we are helping developers like you build with generative AI, use machine learning in spreadsheets and applications, create ML models from the ground up, and scale them up to serve millions of users. While AI technology is advancing rapidly, we must continue to ensure it is used responsibly.

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Topbots

JULY 29, 2024

Introduction to Generative AI by Google Cloud Level: Beginner Duration: Specialization with 4 courses (approximately 4 hours total) Cost: Free Instructor: Google Cloud Training Team Audience: This course is ideal for individuals looking to deepen their understanding of generative AI and large language models.

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