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Accepted Paper:

Utilitarianism scales: The shared intellectual genealogies of the ethics of autonomous driving and data driven philanthropy  
Maya Indira Ganesh (University of Cambridge)

Paper short abstract:

This presentation articulates the epistemic connections between the Moral Machine project and My Goodness, two projects from MIT Media Lab that advanced utilitarian approaches to ethical decision-making in statistical and data-driven systems in AI applications.

Paper long abstract:

How should an autonomous vehicle be programmed to make decisions in the case of a crash that potentially jeopardises multiple human lives? Can these human lives be considered equally worthy of saving? These questions have animated a briefly popular academic and industrial field of inquiry, the ethics of autonomous driving. A similar set of questions animates a conundrum thought to be associated with philanthropic giving: which set of human lives are worth more in saving from disease, deprivation, and disaster? Both share a similar foundational concern: what is the most efficient, effective data-driven measure by which the answer –the more valuable human life - might be arrived at? They also share another connection; Moral Machine and My Goodness are two projects from MIT Media Lab’s now-disbanded Scalable Cooperation Group marrying utilitarian approaches to ethics with data-scientific approaches to autonomous driving and philanthropic giving respectively. This paper maps the shared political, epistemic, material, and discursive transformations of ethics and morality into matters for data-scientific ‘reason’; and how gamification is a key epistemic modality in resolving ethical conflict. Eventually, ‘the ethical’ as a matter of friction and complexity in interior and collective struggle is fast disappearing as AI picks up pace.

Panel P063
Philanthropy, technoscience, and transformation
  Session 1 Friday 19 July, 2024, -