Applying Responsible AI with Open-Source Tools
Learn practical techniques for building safe, fair AI models using open-source tools. Tackle challenges in robustness, labeling errors, bias, and data leakage with hands-on examples for machine learning and NLP projects.
How to Make Smart Architecture Decisions when Building Generative AI Apps
Explore architectural decisions for building reliable, performant generative AI apps. Learn to make smart choices, enhance safety and accuracy, and apply best practices through real-life use cases.
Responsible AI and Ethics in AI Engineering
Explore ethical AI engineering practices and their societal impact. Learn to adapt to the changing landscape and consider human factors when building AI-powered systems and products.
Be More Responsible Around AI - Less Bias, More Ethics
Explore ethical AI development, focusing on reducing bias and enhancing responsible practices in artificial intelligence systems.
AI One Can Trust
Explore trustworthy AI principles and applications with Dr. Biplav Srivastava, focusing on ethical considerations and reliable AI systems development.
The Role of Openness in Responsible AI
Explore the crucial role of openness in developing responsible AI systems with insights from industry experts on ethical considerations and best practices.
Responsible AI in Practice: Real-World Examples and Challenges
Explore real-world examples and challenges of implementing responsible AI, gaining insights into ethical considerations and practical strategies for developing AI systems with integrity.
Ethics in the Cloud - Safeguarding Responsible AI Development in Asia
Explore ethical AI development in Asia, focusing on data privacy, cybersecurity, and regulatory compliance. Learn strategies to champion responsible practices in the region's diverse tech landscape.
AI Show - Ignite Recap: Arc-Enabled ML, Language Services, and OpenAI
Recap of Microsoft Ignite announcements, featuring Arc-enabled ML, Language services, and OpenAI capabilities on Azure. Includes demos, Q&A sessions, and discussions on responsible AI use.
Responsible AI in Industry - Lessons Learned in Practice
Explore practical lessons on implementing responsible AI in industry, covering explainability, fairness, and challenges faced by major tech companies.
The What, Why & How of Responsible AI
Explore practical strategies for implementing ethical AI systems, addressing bias, and promoting fairness in algorithmic decision-making across various sectors of society.
Developing Policies for the Responsible Use of AI Technologies
Explore AI governance with experts discussing responsible adoption, risk management, and building trust in AI technologies across industry, academia, government, and law enforcement.
Generative AI Meets Responsible AI - Practical Challenges and Opportunities
Explore practical challenges and opportunities at the intersection of generative AI and responsible AI, focusing on ethical considerations and real-world applications.
Theories of Change in Responsible AI
Explore theories of change in responsible AI, examining approaches to ethical development and implementation of artificial intelligence technologies.
The Myth of Neutrality - How AI is Widening Social Divides
Explores how AI systems perpetuate and amplify societal biases, examining real-world examples of algorithmic discrimination and discussing potential solutions for building more equitable AI technologies.
Responsible AI for Business Leaders
Explore responsible AI practices, challenges, and Google's principles for ethical AI implementation in business. Learn strategies to mitigate risks and ensure positive outcomes in AI development.
Responsible AI for Engineers
Explore responsible AI practices, challenges, and solutions in this talk by Google's Technical Director. Learn about bias, unintended consequences, and techniques for aligning machine learning with ethical values.
LinkedIn's Insights on AI Fairness in Hiring
Explore LinkedIn's approach to AI fairness in hiring, focusing on mitigating bias in algorithmic and product design, and data processing for more equitable recruitment practices.
Responsible AI: Importance, Challenges, and Future Directions
Explore responsible AI with IBM's Dr. Stacy Hobson, discussing its importance, examples of irresponsible AI, and future developments in inclusive technology research.
Universal Hyper Intelligence - Shaping Human Evolution
Explore Universal Hyper Intelligence's impact on human-machine interaction, societal influence, and ethical implications. Discover opportunities and challenges in AI-driven evolution and the importance of responsible development.
Responsible AI: Challenges and Emerging Practices - Keynote
Explore challenges and emerging practices in responsible AI, including unintended consequences, model interpretability, fairness, and engineering objectives.