=Paper=
{{Paper
|id=Vol-3256/paper7
|storemode=property
|title=EA-Ontology: Ethical Assessment Ontology
|pdfUrl=https://ceur-ws.org/Vol-3256/paper7.pdf
|volume=Vol-3256
|authors=Karen Leticia Vázquez-Flores,Elena Montiel-Ponsoda,María Poveda-Villalón
}}
==EA-Ontology: Ethical Assessment Ontology==
https://ceur-ws.org/Vol-3256/paper7.pdf
EA-Ontology: Ethical Assessment Ontology⋆
Karen Leticia Vázquez-Flores1 , Elena Montiel-Ponsoda1 and María Poveda-Villalón1
1
Ontology Engineering Group, Universidad Politécnica de Madrid, Spain
Abstract
Technological advancements have brought the need to analyse and evaluate the potentially negative
impact that technologies might have on individuals, society and the environment. More and more
voices are being raised in favour of carefully examining technologies from an ethical perspective at
different stages of their development, especially at the early stages. Several methodological approaches
have been proposed to ease the analysis and guide involved actors in the assessment process. In this
preliminary work, we propose the Ethical Assessment Ontology (EA-Ontology). This ontology models
the ethics assessment of emerging technologies according to two relevant approaches in the ethics
and technology area, namely, Anticipatory Ethics for Emerging Technologies (ATE) and Assessing
Expectations Methodology. Additionally, we propose some specific classes to model a complete ontology
with general information about the emerging technology. The EA-Ontology has been developed according
to the Linked Open Term methodology and published with WIDOCO. The final aim of this work is to
use the proposed model for the annotation of the ethical assessments manually produced by experts
in the context of the PROTECT EU project, and others that might be available (such as the use cases
produced by the SIENNA project).
Keywords
Ethics Assessment Ontology, Emerging Technologies, Anticipatory Ethics for Emerging Technology,
Assessing Expectations, Ethical Issue
1. Introduction
Emerging technologies are technologies in which five attributes are identifiable: (1) they have
to be radically novel, and (2) relatively fast growing; (3) they have to be characterised by a
certain degree of coherence, and (4) with the potential to exert a considerable impact on the
socio-economic domain; and, finally, (5) they have to be in a phase that is still somewhat
uncertain and ambiguous [1]. Emerging technologies are commonly analysed at the Research
and Development stage (RD). Precisely at this stage, such technologies should also be evaluated
as for the ethical issues that could arise from their employment, so that users could better
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∗
Corresponding author.
†
These authors contributed equally.
Envelope-Open kvazquez@delicias.dia.fi.upm.es (K. L. Vázquez-Flores); emontiel@fi.upm.es (E. Montiel-Ponsoda);
m.poveda@upm.es (M. Poveda-Villalón)
GLOBE https://oeg.fi.upm.es/ (K. L. Vázquez-Flores); https://oeg.fi.upm.es/ (E. Montiel-Ponsoda); https://oeg.fi.upm.es/
(M. Poveda-Villalón)
Orcid 0000-1111-2222-3333 (K. L. Vázquez-Flores); 0000-0003-3263-3403 (E. Montiel-Ponsoda); 0000-0003-3587-0367
(M. Poveda-Villalón)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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prepare for the future, and ethical undesirable consequences could be minimised. [2].
In recent years, the research about ethics in emerging technologies has taken important steps
which have led experts in the area to propose several approaches to guide the ethical analysis
of emerging technologies.
In the framework of the PROTECT International Training Network 1 , our aim is to evaluate
and refine methodologies and tools to support privacy and ethics assessment of advanced
personalisation technologies. Specifically, our work is focused on providing semantically
enhanced tools to support the ethics assessment of emerging personalisation technologies. For
that purpose, we have analysed two theoretical approaches to ethical assessment, namely, Philip
Brey’s Anticipatory Technology Ethics [3] and Lucivero et al. [4] Assessing Expectations, and
have merged them in an ontological model, the Ethics Assessment Ontology (EA-Ontology).
The Anticipatory Ethics for Emerging Technologies (ATE) methodology was formulated by
Philip Brey and is explained in [2]. ATE includes ethical principles, issues, objects of analysis,
levels of analysis, and research aims. Moreover, the approach created by Brey is particularly
intended to predict the use and the social consequences of future technology, i.e., to technology
forecasting. Assessing Expectations is proposed by Federica Lucivero et. al. in [5]. Assessing
Expectation is exactly about assessing the plausibility of promises and expectations in a tech-
nology. The aim of this approach is to study the feasibility, usability and desirability of the
expectations.
In the context of the PROTECT project, these two complementary approaches have been
used with the purpose of identifying the potential ethical issues of emerging technologies and
performing a forecast analysis of expectations. The internal documents resulting from this work
(Personalisation case studies) have been taken as the starting point for the ontology engineering
work presented in this paper. Additionally, we have also considered the deliverables resulting
from the SIENNA project, specifically D4.4 [6].
Another work we have considered is the AI Risk Ontology (AIRO) [7]. AIRO aims at repre-
senting in an interoperable manner risks of harm related to AI systems, in agreement with the
requirements of the EU AI Act [8]. However, it does not seem to rely on any methodological
approaches to ethical assessment, nor relate ethical issues directly to expectations.
The rest of the paper is structured as follows: Section 2 presents the Ontology Design,
describing the Methodology and Ontology Overview. Section 4 concludes our work.
2. Ontology Design
2.1. Methodology
Linked Open Terms (LOT) [9] is the methodology used for the development of the EA-Ontology.
LOT defines a basic workflow with four steps:
• Ontological requirements specification: The two methodological approaches presented
at the Introduction of this paper define the goal of our ontology and are taken as the
basis for its development. Additionally, we consider several case studies produced in the
context of European projects, since no real assessments seem to be available.
1
https://protect-network.eu
Finally, we specified the technical requirements of the ontology (e.g., the use of Chowlk2
and Widoco3 ).
• Ontology implementation: To develop the ontology, we identify the core concepts, re-
lations and properties that describe the domain. In the work at hand, we have used the
notation proposed in the Chowlk tool [10].
• Ontology publication: We use WIDOCO [11], a tool for generating HTML documentation
of ontologies. The ontology is evaluated by modeling example use cases from PROTECT
and Deliverable 4.4 of the SIENNA project. EA-Ontology is provided in:
https://protect.oeg.fi.upm.es/eaontology/eaontology_widoco/index-en.html with
its documentation.
• Ontology maintenance: In the case of changes of requirements, the ontology will have to
be revised as a new version with appropriate documentation of changes.
2.2. Ontology Overview
The main classes and relations in the Ethical Assessment Ontology (EA-Ontology), are illustrated
in Figure 1. Only a reduced version has been included here for the sake of readability. For
the whole version of the ontology, please see https://protect.oeg.fi.upm.es/eaontology/eaontol-
ogy_widoco/index-en.html. The green shaded classes are the classes that describe an emerging
technology. The orange shaded ones represent the information about ethical issues, and the
purple ones represent the information about expectations.
The main classes about Emerging Technology are: (1) Technology, (2) Artifact, (3) Application,
with respect to which an emerging technology is ethically evaluated; the (4) ”Feature(s)” of
the emerging technology, (5) the ”Function(s)”, (6)User, who is divided into (7)Main User and
(8)Secondary User, and (9) the specific ”Context Of Use” in which the emerging technology is
supposed to be employed.
On the other hand, the core classes in the Ethical Issues part are: (10) Ethical issue, followed
by (11) the Likelihood of affectation, (12) Severity of affectation and (13) Overall affectation of
the ethical issue; Ethical issues are classified according to a taxonomy that contains 79 ethical
issues classified into four categories. The ethical issues taxonomy has been revised in the
context of PROTECT according to the ethical principles traditionally recognized in Ethics and
in documents such as the Universal Declaration of Human Rights. Even though the four main
categories are not illustrated in the figure, they are: Harm and Risk, Right, Well-being and
Common Good.
Finally, the classes that describe the Expectations are: (14) Expectation and three subtypes: (15)
claims about the characteristics and functioning of the technology, i.e., Technological Feasibility,
(16) Social Usability, which includes claims about how the technology will be adopted by the
intended users and (17) claims about how the technology will address a social problem or need,
that is, Desirability.
Any expectation or claim is based on evidences, understood as the information or data that
supports an assertion. The class (18) Evidence has been previously defined in a highly similar
2
https://chowlk.linkeddata.es
3
https://dgarijo.github.io/Widoco/doc/tutorial/
Figure 1: Overview of EA-Ontology’s main classes and relations
way in the EBOCA Evidence Ontology 4 [12], and, therefore, we decided to import it here. This
class allows us to refer to the textual information (paragraphs) in which those expectations are
supported, and account for the provenance and authors of the information.
3. Conclusions and Future Work
The ontology described in this paper is a first attempt to model the main aspects involved in the
ethical analysis of an emerging technology. EA-Ontology identifies the two key points in that
assessment: Expectations and Ethical Issues. Furthermore, the EA-Ontology accounts for the
evidence that allowed the ethical expert to make those claims about expectations and ethical
issues. In this paper, we illustrate the usefulness of the EA-Ontology with a real use case made
by and expert in Ethics.
Our objective is to use this ontology as the groundings to implement a wizard that will assist
ethicists and technology developers in assessing emerging technologies. This will also allow to
annotate the result of such an assessment and capture data in a queryable semantic format.
4
https://drugs4covid.github.io/EBOCA-Evidences-Ontology/index.htmlhttp://purl.org/dc/dcmitype/Software
Acknowledgments
This work has received funding from the EU’s Horizon 2020 Research and Innovation programme
through the contracts Marie Sklodowska-Curie PROTECT (grant agreement No. 813497).
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