Ethical and Societal Challenges of Machine Learning

An ICTP Virtual Meeting From helping farmers adapt to climate change to predicting disease outbreaks, scientists in developing countries have begun turning to ML for more effective solutions. With this potential, however, comes the possibility for abuse, misuse, and unintended consequences. Embedding Ethics Education in Machine Learning: case studies from various parts of the world that demonstrate the need for a wider perspective on ML ethical challenges. Big data, privacy and democracy: ethical questions linked with big data exploitation, privacy and the dangers for democracy. Machine Learning, bias and fairness: problems of ML amplified bias, and some of the possible solutions.