=Paper=
{{Paper
|id=Vol-3205/paper2
|storemode=property
|title=Towards an Argument Scheme Classification for Ethical Reasoning
|pdfUrl=https://ceur-ws.org/Vol-3205/paper2.pdf
|volume=Vol-3205
|authors=Elfia Bezou-Vrakatseli,Oana Cocarascu,Sanjay Modgil
|dblpUrl=https://dblp.org/rec/conf/comma/Bezou-Vrakatseli22
}}
==Towards an Argument Scheme Classification for Ethical Reasoning==
https://ceur-ws.org/Vol-3205/paper2.pdf
Towards an Argument Scheme Classification for
Ethical Reasoning
Elfia Bezou-Vrakatseli1 , Oana Cocarascu1 and Sanjay Modgil1
1
Department of Informatics, King’s College London, UK
Abstract
This paper describes progress towards realising the long-term research goal of supporting dialogue
between humans and between humans and AI systems so as to enable transparent and rational joint
reasoning, in particular about matters of ethical significance. Key to realising this goal is this paper’s
proposed exploration and analysis of natural language moral debates, via argument schemes and critical
questions. We believe this to be an important first step in identifying schemes and scheme taxonomies,
specialised for ethical reasoning, and that can support both the natural language processing needed to
support human-AI dialogue, as well as for scaffolding human-human dialogue.
Keywords
Dialogue, argument schemes, argument mining, ethics
1. Introduction & Motivation
Recent highly publicised successes in Artificial Intelligence (AI) applications have in large part
been due to advances in machine learning (notably deep learning) [1]. However, symbolic ap-
proaches to AI will necessarily play a role in facilitating inter-agent (in particular human-AI and
human-human) communication which is inherently a symbolic activity. In particular, reasoning
in the presence of uncertainty, conflict, and disagreement typically benefits from multiple agents
engaged in information sharing and joint reasoning; that is, in dialogical exchanges normatively
governed by prescriptions encoded in logics for non-monotonic reasoning. One of the most
promising paradigms for facilitating such dialogues is through argumentation-based charac-
terisations of non-monotonic (nm) inference relations in terms of the exchange of arguments
constructed from a given static belief base. These ‘monological’ characterisations can then be
generalised to dialogical models in which agents exchange locutions (not limited to arguments),
such that evaluation of a dialogical exchange in favour of a claim equates with that claim being
a non-monotonic inference from the information shared during the course of the dialogue [2].
As dialogues consist of informational exchanges, they enable the understanding of the parties
involved, not only as a direct result of the information each utterance conveys, but also as a
means of exploring the reasoning of the interlocutors. As a result, dialogues also facilitate joint
reasoning. Overall, the communication and joint reasoning of AI systems and humans leverages
the strengths of AI along with those of human reasoning.
CMNA ’22: Workshop on Computational Models of Natural Argument
Envelope-Open elfia.bezou_vrakatseli@kcl.ac.uk (E. Bezou-Vrakatseli); oana.cocarascu@kcl.ac.uk (O. Cocarascu);
sanjay.modgil@kcl.ac.uk (S. Modgil)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
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Elfia Bezou-Vrakatseli et al. CEUR Workshop Proceedings 1–5
Our long-term research goal is guiding humans and AI systems alike in building and chal-
lenging arguments related to ethical issues as ethical reasoning is of crucial importance for
decision-making systems that can impact human lives [3]. Moreover, enabling joint human
and AI reasoning can help solve the value alignment problem [2] and help ensure the ethical
behaviour, in accordance with human values, of agents as shown in [4]. In order to support
dialogue between humans and between humans and AI systems that can enable transparent and
rational joint reasoning, we need to draw from recent advances in natural language processing
(NLP), and in particular argument mining [5], an area of research which focuses on extracting
arguments and their relations from text (e.g. relations between premises and conclusions).
To this end, we begin by analysing natural language (NL) texts using argument schemes and
critical questions. In particular, we focus on annotating moral debates using two argument
scheme classifications: Walton [6] and Wagemans [7]. As the existing vast variety of taxonomies
and argument schemes is one of the biggest problems in the literature, we purport to reconcile
the two most used classifications and develop a theoretically well-founded, as well as practically
useful, hybrid classification that can be applied to ethical debates. Said reconciliation leverages
the strengths of both, while identifying the schemes particular to ethical reasoning. The novelty
of our research can be found in the attempt to go beyond standard argument mining techniques
(to determine the relation between premise and conclusion and identify support/attack relations
between arguments) by making use of informal logic. In particular, we make use of argument
schemes and critical questions that offer a semantically richer approach to argument classifica-
tion, as premises support a conclusion by virtue of instantiating a scheme and support/attack
relations are instigated in response to critical questions.
2. Background & Related Work
Argument schemes represent stereotypical patterns of reasoning and consist of a set of premises
and a conclusion. Walton proposed over 60 argument schemes with corresponding sets of critical
questions which are used to evaluate the strength of an argument [6] . For example, Walton’s
representation of the argument from positive consequences scheme is defined by a Premise: “If 𝐴
is brought about, good consequences will (plausibly) occur” and Conclusion: “Therefore, 𝐴 should
be brought about”, with the following critical questions (CQs): CQ1: “How strong is the likelihood
that the cited consequences will (may, must) occur?”; CQ2: “What evidence supports the claim that
the cited consequences will occur and is it sufficient to support the strength of the claim adequetly?”;
“CQ3: Are there opposite consequences (bad as opposed to good) that should be taken into account?”.
Wagemans proposed the Periodic Table of Arguments (PTA) [7] (see Figure 1 for the first
iteration of the table), which is based on an a priori constrained set of possible combinations
between different characterisations of argument: subject vs predicate arguments, first vs second
order arguments, and argument substance. Subject arguments are arguments whose premise
and conclusion have the same predicate but different subject (e.g. “Abortion should be illegal,
because murder is illegal.”), whereas Predicate arguments are arguments whose premise and
conclusion share the same subject but have different predicates (e.g. “The death penalty should
be abolished, because the death penalty carries the risk of ruining innocent people lives.”). First-
order arguments contain simple statements which cannot be split further while Second-order
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Figure 1: The first Periodic Table of Arguments with different characterisations of arguments: subject
vs predicate, 1st vs 2nd order, and combinations of three types of propositions: F(act), V(alue), P(olicy) [7].
arguments are epistemological in nature and, containing at least one complex statement whose
subject can be broken down, they can embed first order arguments (e.g., “We should wear masks
in public because WHO suggests it.”). Finally, the argument’s statements are categorised as
propositions of policy (if they express that an act should be performed), of value (if they contain
an evaluative judgment based on a definition or assessment criteria, such as ethical judgements),
or of fact (if their veracity can be verified empirically). We note that the two taxonomies are not
incompatible and the PTA can incorporate existing schemes, for example Walton’s argument
from sign corresponds to 1-pre-FF in the PTA, as can be seen in Figure 1.
Several works have focused on classifying arguments based on the argument scheme they
instantiate using features extracted from text [8, 9]. [10] proposed guidelines for annotating
argument schemes using a taxonomic hierarchy of schemes and the semantic properties of
premises/claims, while [11] advocated for the creation of argument scheme templates represent-
ing clusters of schemes. Visser et al. [12] annotated election debates using Walton’s schemes
and Wagemans’s PTA and provided an overview of the correspondence between the results
obtained with the two taxonomies. In contrast, our aim is to reconcile the two approaches of
classifying schemes, leveraging the strengths of both in order to develop a hybrid classification
that can be applied to ethical debates so as to provide transparent and rational reasoning.
3. From Argument Classification to Reconciling Taxonomies
We make first steps towards reconciling the two taxonomies by classifying NL arguments
using Walton and Wagemans, following the method of Visser et al. [12] to manually annotate
arguments, but we focus on ethical debates (e.g. “Pro-life vs Pro-choice: Should abortion be
legal?”, “Should an Artificial General Intelligence be created?”, “Should all humans be vegans?”).
The most common schemes identified are: argument from consequences, argument from values,
argument from analogy, argument from example, practical reasoning, while the majority of
arguments we identify using Wagemans’ classification are first-order, predicate arguments.
Classifying an argument from the debate Pro-life vs Pro-choice. Consider argument 𝐴:
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Elfia Bezou-Vrakatseli et al. CEUR Workshop Proceedings 1–5
Access to legal abortion improves the health and safety of pregnant people. In our analysis, we
first determine that argument 𝐴 is an enthymeme and assume the complete argument to be
𝐴′ : Access to legal abortion improves the health and safety of pregnant people, so pregnant people
should have the right to choose abortion.
To annotate with Walton’s taxonomy, we use the Argument Scheme Key (ASK), a series of
disjunctive choices based on the distinctive features of argument schemes which also groups
scheme types that share particular characteristics [12]. The ASK path used to classify argument
𝐴′ is as follows, with the answer in brackets: Argument relies on a source’s opinion or character
(No); Conclusion is about a course of action (Yes); Argument focuses on the outcome of the action
(Yes); Conclusion promotes a positive outcome (Yes); Course of action assists someone else (No);
Course of action promotes a goal (Yes), resulting in an argument from positive consequences.
To annotate with Wagemans’ taxonomy, we consider the three characterisations of argument.
In particular, we determine that 𝐴′ is a first-order, predicate argument as the premise and the
conclusion share the same subject (i.e. “access to legal abortion”). Note that 𝐴′ needs to be
rephrased slightly in order to match the definition of a predicate argument. Lastly, we observe
that the conclusion of 𝐴′ is a proposition of policy (“pregnant people should have the right …”),
while the premise is a fact (“legal access improves the health and safety of pregnant people”),
thus the argument is of type 1-pre-PF, equivalent to a pragmatic argument.
This example offers insights into our approach towards a hybrid taxonomy: firstly, observing
the co-occurrences of argument schemes in both classification systems allows us to detect
correspondences between the two in order to reconcile them. For example, Walton’s argument
from positive consequences is often classified as 1-pre-PF using Wagemans’ PTA, which was
also observed in [12]. Secondly, comparing and contrasting the annotation guidelines of each
taxonomy helps us reflect on them and their usefulness. For instance, deciding if an argument
is first or second order is a criterion in both taxonomies, which indicates that this distinction is
necessary and should be included in the criteria of classification in our hybrid taxonomy.
We also take inspiration from [13] that developed the hybrid scheme argument from action,
which (partly) incorporates the schemes argument from positive/negative consequences, argument
from positive/negative values, and practical reasoning. Grouping schemes in this manner can be
a helpful tool in decreasing the number of argument schemes considered and a step towards
developing our hybrid classification. Thus, we also consider argument 𝐴′ as an argument from
action, although the scheme is not part of the two taxonomies analysed.
Linking arguments using critical questions. Consider argument 𝐴: A vegan society would
cause the least harm to wildlife, so all humans should go vegan and argument 𝐵: The risk of death of
wildlife increases during the transport of food, especially when the vegan food travels for thousands
of miles. Argument 𝐴 is an argument from action which has 16 critical questions [13], one of
them being CQ: “Assuming the circumstances, does the action have the stated consequences?”. We
observe that argument 𝐵 can serve as an answer to the CQ of argument 𝐴 and can be seen as a
counter-argument to it. In addition, argument 𝐵 is as an argument from danger.
An important step in reconciling Walton’s argument schemes and Wagemans’ PTA is to
identify the strengths of the two taxomies. The former is more comprehensive, while the latter
is more practically useful and can be seen as an intermediate between the semantic detail of
Walton and the relation between premise-conclusion used in argument mining approaches.
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Critical questions represent a key aspect of argument schemes, as they can be pointers to
counter-arguments or supporting arguments, since the argument answering a critical question
attacks/supports the original argument by virtue of the critical question; we aim to include
them in our hybrid classification and apply them to ethical debates. Part of our reconciliation
process is also to decrease the number of argument schemes. Indeed, the next step of our study
will focus on exploring whether other schemes can be grouped together, similarly to argument
from action [13]. The clustering nature of the ASK algorithm along with the criteria of the PTA
can be used to create a reduced, but still broad, number of argument types.
4. Conclusion
This paper describes an initial step towards realising the long-term research goal of supporting
dialogue between humans and between humans and AI systems. We focus on argument
annotation using Walton’s argument schemes and critical questions as well as Wagemans’
Periodic Table of Argument, in order to develop a new, evolved framework, specialised in
ethical reasoning. We believe this is an important first step in identifying schemes and scheme
taxonomies specialised for ethical reasoning and that can support dialogical scaffolding of
both human and artificial agent reasoning. Our approach goes beyond standard annotation
approaches for argument mining and proposes a semantically richer approach to argument
classification through tools of argumentation.
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