Tristram McPherson

Development of socially sustainable traffic-control principles for self-driving vehicles: the ethics of anthropocentric design

Converging effect of communication, sensing, and in-vehicle computing technology has ensured potential to develop large-scale deployment of self-driving vehicles. Considering the potential impact of this technology, the approach for development cannot overlook needs regarding sustainability and social considerations. This paper argues that control technology for self-driving vehicles has both direct and indirect effect on fundamental human rights, and that the anthropocentric design perspective is a necessary ethical approach. Furthermore, we present current perspectives on operational principles, and relevant theoretical and empirical social implications. We conclude that there is potential for development of traffic-control principles for self-driving vehicles on the basis of mutually-advantageous cooperative production. Finally, we present several important areas for further investigation.

A Case for Ethical Veganism

This paper argues for ethical veganism: the thesis that it is typically wrong to consume animal products. The paper first sets out an intuitive case for this thesis that begins with the intuitive claim that it is wrong to set fire to a cat. I then raise a methodological challenge: this is an intuitive argument for a revisionary conclusion. Even if we grant that we cannot both believe that it is permissible to drink milk, and that it is wrong to set fire to cats, this leaves open the question of which of these judgments we should abandon. I consider and reject three strategies for addressing this question: more methodologically naive moral theorizing, appeal to systematic normative theory, and attacking non-moral presuppositions. I argue that philosophically satisfying the resolution of the conflict requires debunking our grounds for belief in one of the conflicting claims. Finally, I argue that ethical veganism is supported by consideration of the most salient debunking arguments available.