Usama Fayyad – By making AI and ML algorithms work in practice, solving real problems with real constraints and challenges, we advance both the science and education of AI. Our AI Solutions Factory at the Institute for Experiential AI gives learners and apprenticeship-intensive experience and tools that teach the art of practicing AI and Data Science.
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Christo Wilson – In this study, we partnered with Pymetrics, a startup that offers candidate screening services for employers, to conduct an algorithm audit of their machine learning pipeline.
Much of the recent focus in machine learning has been on the pattern-recognition side of the field. I will focus instead on the decision-making side, where many fundamental challenges remain.
As companies tap into AI for next-generation offerings with huge real-world impacts, mistakes go beyond mere inconvenience. For AI to reach its full potential, human intervention is needed.
The growing ubiquity of the Internet and the information overload created a new economy at the end of the twentieth century: the economy of attention.
Ethical Complexities of Search Engine Rankings - Search engines play a crucial role in our access to information. We need a more rigorous public debate that goes beyond principles and engages with necessary value trade-offs.
The recent incidents involving Dr. Timnit Gebru, Dr. Margaret Mitchell, and Google have triggered an important discussion emblematic of issues arising from the practice of AI Ethics research. We offer this paper and its bibliography as a resource to the global community of AI Ethics Researchers.
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence
Inequalities, Biases, Fairness, Nudge, and Feedback Loops — an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence