Mele’s Digital Zygote: Developer Responsibility for Neural Networks

Should developers be held responsible for the predictions of their neural networks-and if not, does that introduce a responsibility gap? The claim that neural networks introduce a responsibility gap has seen significant pushback, with philosophers arguing that the gap can be bridged, or did not exist in the first place. We show how the responsibility gap turns on whether we can distinguish between foreseeable and unforeseeable neural network predictions. Empirical facts about neural networks tell us we cannot, which seems to force developers to either assume full responsibility or no responsibility at all, introducing a responsibility gap-unless, of course, the same empirical facts hold true of humans, in which case there is no gap, but the trouble is simply with the classical notion of responsibility. We revisit and revise Mele's Zygote, as well as the famous Palsgraf case, and argue that in fact, what complicates responsibility assignment for neural networks also complicates responsibility assignment for humans, and humans seem to confront us with the same all-or-nothing dilemma. Thus, we agree there is no technology-induced responsibility gap (there was no gap in the first place), but for slightly different reasons than our predecessors.

Authors

Institutions

Publication Details

Journal
Science and Engineering Ethics
Published
2025-11-26
DOI
https://doi.org/10.1007/s11948-025-00566-9
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mele’s Digital Zygote: Developer Responsibility for Neural Networks

Anders Søgaard, Filippos Stamatiou
Science and Engineering Ethics
Ethics and Social Impacts of AI
article

Mele’s Digital Zygote: Developer Responsibility for Neural Networks

Anders Søgaard, Filippos Stamatiou
article en

Abstract

Should developers be held responsible for the predictions of their neural networks-and if not, does that introduce a responsibility gap? The claim that neural networks introduce a responsibility gap has seen significant pushback, with philosophers arguing that the gap can be bridged, or did not exist in the first place. We show how the responsibility gap turns on whether we can distinguish between foreseeable and unforeseeable neural network predictions. Empirical facts about neural networks tell us we cannot, which seems to force developers to either assume full responsibility or no responsibility at all, introducing a responsibility gap-unless, of course, the same empirical facts hold true of humans, in which case there is no gap, but the trouble is simply with the classical notion of responsibility. We revisit and revise Mele's Zygote, as well as the famous Palsgraf case, and argue that in fact, what complicates responsibility assignment for neural networks also complicates responsibility assignment for humans, and humans seem to confront us with the same all-or-nothing dilemma. Thus, we agree there is no technology-induced responsibility gap (there was no gap in the first place), but for slightly different reasons than our predecessors.

Science and Engineering EthicsVol. 31(6)
University of Copenhagen (DK), Stellenbosch University (ZA)
Openalex Percentile: Top 63%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Mele’s Digital Zygote: Developer Responsibility for Neural Networks — Anders Søgaard, Filippos Stamatiou · Science and Engineering Ethics (2025) | TGRS Research Map | TGRS