Deep Ethics Integration in Technology Research and Development: Bridging the Principles-to-Practice Gap in AI Ethics – and Elsewhere

Abstract In this paper I investigate how integrating ethics deeply into technology research and development can help developers overcome a major obstacle in the ethical alignment of innovation processes, namely, the “principles-to-practice gap”. By reference to a specific ethics intervention made by Berlin Ethics Lab featuring an AI system under development, I show that the gap is not about a failure to operationalize principles for research and development practice, but rather that it originates in divergent styles of thinking: ethical reflection and design thinking. Based on these insights, I elucidate how ethical reflection can be integrated on a foundational level into research and development processes. An essential starting point is the creation of a space for reflection to explore potential designs, a space dedicated to contextualizing and re-conceptualizing technology. This enables an ethical reframing of the design problem, systematic ethical analysis, and an assessment of potential implications. I conclude by presenting the ways in which this approach of deep ethics integration challenges other approaches to integrating ethics at an early stage (such as embedded ethics, STIR, VCIO, ethics by design, and value sensitive design) and demonstrating what additional benefits it has to offer.

Authors

Institutions

Publication Details

Journal
Philosophy & Technology
Published
2026-08-31
DOI
https://doi.org/10.1007/s13347-026-01134-0
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep Ethics Integration in Technology Research and Development: Bridging the Principles-to-Practice Gap in AI Ethics – and Elsewhere

Sabine Ammon
Philosophy & Technology
Ethics and Social Impacts of AI
article

Deep Ethics Integration in Technology Research and Development: Bridging the Principles-to-Practice Gap in AI Ethics – and Elsewhere

Sabine Ammon
article en

Abstract

Abstract In this paper I investigate how integrating ethics deeply into technology research and development can help developers overcome a major obstacle in the ethical alignment of innovation processes, namely, the “principles-to-practice gap”. By reference to a specific ethics intervention made by Berlin Ethics Lab featuring an AI system under development, I show that the gap is not about a failure to operationalize principles for research and development practice, but rather that it originates in divergent styles of thinking: ethical reflection and design thinking. Based on these insights, I elucidate how ethical reflection can be integrated on a foundational level into research and development processes. An essential starting point is the creation of a space for reflection to explore potential designs, a space dedicated to contextualizing and re-conceptualizing technology. This enables an ethical reframing of the design problem, systematic ethical analysis, and an assessment of potential implications. I conclude by presenting the ways in which this approach of deep ethics integration challenges other approaches to integrating ethics at an early stage (such as embedded ethics, STIR, VCIO, ethics by design, and value sensitive design) and demonstrating what additional benefits it has to offer.

Philosophy & TechnologyVol. 39(3)
Technische Universität Berlin (DE), University of Tübingen (DE)
Technische Universität Berlin
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
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.