Skip to main navigation
Skip to search
Skip to main content
TU Delft Research Portal Home
Help & FAQ
Home
Research units
Researchers
Research output
Datasets
Projects
Equipment
Press/Media
Prizes
Activities
Search by expertise, name or affiliation
Machine learning and power relations
Jonne Maas
*
*
Corresponding author for this work
Ethics & Philosophy of Technology
Research output
:
Contribution to journal
›
Article
›
Scientific
›
peer-review
4
Citations (Scopus)
107
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Machine learning and power relations'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Social Sciences
Learning
100%
Machines
100%
Consumers
100%
Artificial Intelligence
60%
Literature
40%
Asymmetry
40%
Responsibility
40%
Auditing
20%
Design
20%
Morality
20%
Legitimacy
20%
Project
20%
Forecasting
20%
Analysis
20%
Approach
20%
Risk
20%
Conceptual Framework
20%
Conceptualization
20%
Power-Dependence
20%
Attention
20%
Computer Science
Machine Learning
100%
User
100%
Power Relation
100%
Artificial Intelligence
60%
Dynamic Power
40%
Conceptual Clarity
20%
Design
20%
External Auditing
20%
Conceptualisation
20%
Dependence Relation
20%
System Developer
20%
Engineering
Artificial Intelligence
100%
End-Users
100%
Guidelines
33%
Conceptualization
33%
Risk Prediction
33%
Mechanisms
33%
Learning Systems
33%
Reflected Power
33%
Design
33%
Illustrates
33%
INIS
power
100%
machine learning
100%
dynamics
25%
accountability
25%
shape
25%
asymmetry
25%
developers
25%
prediction
12%
design
12%
drawing
12%
risks
12%
values
12%
ethics
12%
guidelines
12%
solutions
12%
Keyphrases
External Auditing
50%
Normative Grounding
50%
AI Guidelines
50%
Moral Wrong
50%