The Meaning of Safe Haven
Responding to the Ukrainian refugee crisis, outsmarting artificial intelligence, and more
March 24, 2022
In this week’s issue of Public Seminar . . .
Seeking Shelter
“Every fresh refugee crisis is an opportunity to reform the international system—and the current crisis in Ukraine is no exception.” T. Alexander Aleinikoff discusses what we can learn from previous humanitarian disasters. (March 23, 2022)
Andreas Kossert examines what it means to be displaced. “Although the reasons and circumstances that drive people to flee can be very different, the concrete experiences of refugees, displaced people and exiles are similar. All must decide: what do I take with me? How much can I carry when on foot? Should I pack valuables, photos, jewelry and documents or better food for the days to come?” (March 22, 2022)
As more than 3.5 million civilians leave Ukraine, Simon Garnett surveys the European landscape. “Public opinion counts. In Poland especially, neighborliness is everywhere to be seen, despite all the historical baggage between the two countries.” (March 23, 2022)
Freedom and Democracy
“To radically remake the world requires openness to radical alterity, the possibility of the radically new. This is why divine creation signifies the essence of freedom, the power to be free from the past, to create entirely new futures, by first taking responsibility for the other.” Lucas Fain returns to Emmanuel Lévinas in order to understand Putin’s “New Iron Curtain.” (March 22, 2022)
Don’t Trust the Algorithm
“Throughout our history, we’ve seen a very systemic and very deliberate policing strategy that’s meant to break down and destroy already marginalized communities, especially Black and Brown communities. So we’re going to see those same data points being reflected in systems that are used to train AI and algorithms. And if we’re not thinking critically about it, we’re just going to see those same cycles repeated over and over again.” Patrick K. Lin chats with Miko Yoshida about his new book, Machine See, Machine Do. (March 23, 2022)
In this excerpt from Machine See, Machine Do, Patrick K. Lin unpacks how facial recognition software is used—and mis-used—in law enforcement. “The diversity of faces used to train an algorithm can influence the kinds of photos and faces that an algorithm is most adept at examining. If the set of face images is skewed towards a certain race, the algorithm may be better at identifying members of that group as compared to individuals of other groups.”