The Ethics Institute的动态

FREE COURSES ON AI/ETHICS/PHILOSOPHY/CRITICAL THINKING 1. Ethics of AI (University of Helsinki) 2. AI-Ethics: Global Perspectives (aiethicscourse.org) 3. Bias and Discrimination in AI (Université de Montréal) 4. Data Science Ethics (University of Michigan) 5. Intro to AI Ethics (Kaggle) 6. Ethics in AI and Data Science (LFS112x) 7. Practical Data Ethics (Fast AI) 8. Data Ethics, AI and Responsible Innovation (The University of Edinburgh) 9. Identify guiding principles for responsible AI (Microsoft) 10. Human-Computer Interaction III: Ethics, Needfinding & Prototyping (Georgia Tech) 11. Ethics in Action 12. Foundations of Ethical Decision-Making (Georgetown University) 13. Philosophy and Critical Thinking 14. IEEE Awareness Module on AI Ethics (IEEE) Enjoy Learning #AI #ethics #philosophy #education

Are you interested in the ethics of AI and digital technology? would it be useful for you to interrogate and question the academic work of one of the world’s leading Professors on the ethics of digital technology? Yale Professor Luciano Floridi is one of the world’s leading academics on the ethics of digital technology has built a generative AI chatbot based on his academic work called LuFlot. Press release Yale: https://lnkd.in/e95ShPkT Access to chatbot: https://lnkd.in/eBjM6PXk The chatbot was developed by two students Nicolas Gertler research assistant at Yale Digital Ethics Centre and Rithvik “Ricky” Sabnekar, a high school junior from Texas and answers questions on Professor Floridi’s academic work completely free. This is a highly significant development in many respects: - 1) Professor Floridi’s work is open access from a specialised academic domain. 2) Discovery and understanding academic papers can be extremely difficult and highly useful academic thinking can be missed and not used, the LuFlot chatbot simplifies discovery. 3) Using the Chatbot is a learning process, think of the top 5 questions you have on Ethical and Moral implications of AI and ask LuFlot. 4) Highly disruptive to how diffusion of academic knowledge occurs the implications of the potential disruption go far beyond the boundaries of academia 5) Gives an insight into how domain specific knowledge bases will be used. Are we entering a world where every Professor, Academic and Knowledge expert will have their own chatbot? ??#AI #Chatbot #Ethics

We are delighted to publish the second in our series of blogs on AI Ethics by Dr Hossein Dabbagh, Assistant Professor in Applied Ethics at Northeastern University London. Dr Dabbagh takes a dive into the principles of ethics in AI and discusses how they can be integrated into everyday lessons in maths, data, ethics/philosophy and more. As he explains: "AI ethics education isn't merely about imparting knowledge of technology; it's about fostering a nuanced understanding of how AI technologies operate within and affect societal structures, personal privacy, and ethical boundaries." Thank you to Dr Brian Ball, Associate Professor of Philosophy at Northeastern University London for facilitating this introduction. #AI #ethics #education

I participated in this pedagogical toolkit complements the competency framework entitled “AI Ethics Training in Higher Education: Competency Framework", which we produced thanks to the "P?le montréalais d'enseignement supérieur en intelligence artificielle" (PIA). In this pedagogical toolkit, we provide concrete ways of carrying out training activities that will help develop the various aspects of AI ethics competency. For each activity, you will find a short explanation of the link between the proposed activity and the elements of the competency framework. This pedagogical toolkit should be seen as a working document that can be used creatively by the teachers who use it. https://lnkd.in/eTQ4c-QY

I remember teaching AI ethics to 14-15 year olds in a high school between 2018-2021. I loved those classes, because it was a part of the course where we got to dream up scenarios for a future world and apply ethical frameworks. As we enter that world now, I'm struck by how prescient those discussions were. The ethical dilemmas we once imagined are becoming reality faster than we anticipated. It's both exciting and sobering to see the rapid advancement of AI and its integration into our daily lives. Those students are navigating a world where AI ethics isn't just a theoretical exercise but a practical necessity. I wonder how those early conversations have shaped their perspectives and decision-making in this new landscape. I hope we can continue fostering these crucial discussions. The ethical considerations surrounding AI are more important than ever and we need diverse voices and perspectives to guide its development responsibly.

An AI Ethics Training pedagogical toolkit useful for Cegep level competencies. https://lnkd.in/epMdh3M2

Now that the semester is over, I’d like to share the top five lessons I’ve learned in the trenches of teaching Artificial Intelligence (AI) ethics in health @ Memorial University! 1 - ENGAGE MORE - It’s been a privilege to learn from students. They have often grown up with AI and digital health and have an intuitive sense around AI. We need to create opportunities to learn from emerging students, such as clinicians, bioethicists, data engineers and policy-makers. 2 - EXPLORE AI USE CASES - When we go beyond theory and ethical principles we can go further and find meaning for ethical AI. Students are inspired by applied learning opportunities.? 3 - ETHICS CAN BE YOUR COMPASS - You might think that ethicists-in-training would rally against AI, but students can easily see the greater good and benefits that can come from AI. They wish to maximize these benefits, while minimizing harm. Embedding ethics generally, and ethicists in particular, into the AI pipeline can mean better technology, improved clinical outcomes and overall buy-in & support.? 4 - INTERNATIONAL DIFFERENCES - To understand the ethics of AI we need to understand context. There are harms and considerations in developing countries that need to be explored. Specific cultural and societal considerations need to be addressed, including the potential for disproportionate harms.? 5 - WE ARE ONLY GETTING STARTED - Students are the first to recognize that we do not know what we do not know. AI opportunities in health are ever-growing, changing and evolving and so too are the potential harms. Laws and policy may never catch up so we need to advance ethics opportunities to learn, research and grow here in Canada and globally.? Plant a seed and let it grow… #AI #Ethics #Bioethics #AIEthics #ResponsibleAI #Privacy #DataEthics **(NOTE: Based on learnings from co-teaching MED 6908 AI Ethics in Health grad course and year two of incorporating AI Ethics into the medical school curriculum in the Faculty of Medicine at Memorial University of Newfoundland). (photo credit: MUN Medicine)

? How could AI technologies be used in educational contexts while keeping students at the centre? 10 Practicing AI Ethics Literacy scenarios are proposed by Anna Keune, ?iva Sim?i?, Noha Lea Halim, Camila Hidalgo, Verena Kappes, Urs Gasser, Matthias Grabmair and, Sezen Per?in to answer this question. The scenarios aim to demonstrate how AI can be used ethically in an educational setting, fostering crucial conversations around ethics. ?? Educators get the chance to share your feedback: https://lnkd.in/drjAesRt This research is part of the “Co-designing a Risk-Assessment Dashboard for AI Ethics Literacy in EdTech” project at the Institute for Ethics in Artificial Intelligence - TUM.? ?? Learn more about it here: https://lnkd.in/e63wU9fh #AIinEducation #EthicalAI #AIEthics #AIEd #AILiteracy Image credit: Htc Erl (https://lnkd.in/dhN6U8Nd) from Pixabay

Excellent application of engaged learning on ethics and AI.

Embedding AI Ethics into K-12 Classrooms: A Framework for Success