Ethics of technology involves sustained reflection on the ways that various technosocial arrangements imply new and different forms of social and political life. Machine learning plays an increasingly prominent role in mediating institutional decisions in everything from corporate hiring practices to criminal sentencing. This ongoing AI spring has invigorated discussions of the ethical dimensions of these techno-social arrangements. In particular, there is a growing awareness that algorithmic decision-making can lead to discriminatory outcomes. How can we take measures to avoid such harms? What steps can we take to democratize the design and deployment of algorithmic decion-making systems? Should we trust this technology at all? Moreover, training these systems depends on massive data collection efforts, which makes their deployment deeply entangled with mass digital surveilance. What does the normalization of digital surveilance mean for human agency? How can we freely pursue our own distinct visions of the good in the face of mass digital surveilance and large-scale technocratic bureaucracy?