IAS/SIR Town Hall: How Artificial Intelligence Became a Western Language
We hope to tackle questions about how western bias manifests in machine learning, how this bias affects real-world applications of artificial intelligence, and how we can combat/prevent it. We are seeing instances of algorithmic bias altering voting outcomes, social media participation, hate speech, decision-making in politics and many more important tools of communication. Given the ever-increasing reliance on artificial intelligence, we believe it is crucial to address inadequacies before they propagate even further.
Anupam Basu, Washington University in St. Louis
Anupam Basu works at the intersection of literature and big data, drawing on emerging computational techniques like natural language processing and machine-learning to make vast digital archives of early modern print more tractable for computational analysis.
Kevin Scannell, St. Louis University
Kevin Scannell's current research uses machine learning to develop computational resources that support speakers of indigenous and minority languages around the world, particularly Irish and the other Celtic languages.
Amar Ashar, Harvard University
Amar Ashar's current research areas include issues of the ethics and governance of Artificial Intelligence with a focus on global governance, inclusion, and media/information quality.