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[Víctor Pérez <victor.perez AT software.imdea.org>]

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CALL FOR PAPERS

MEandE-LP 2022

2nd Workshop on Machine Ethics and Explainability-The Role of Logic 
Programming

https://sites.google.com/view/meande-lp2022/

July 31, 2022 (ICLP Workshop)

Affiliated with 38th International Conference on Logic Programming (ICLP),

July 31–August 8, 2022, Haifa, Israel

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AIMS AND SCOPE

Machine Ethics, Explainability are two recent topics that have been 
attracting a lot of attention and concern in the last years. This global 
concern has manifested in many initiatives at different levels. There is an 
intrinsic relation between these two topics. It is not enough for an 
autonomous agent to behave ethically, it should also be able to explain its 
behavior, i.e. there is a need for both ethical component and explanation 
component. Furthermore, an explainable behavior is obviously not acceptable 
if it is not ethical (i.e., does not follow the ethical norms of the society).

In many application domains especially when human lives are involved (and 
ethical decisions must be made), users need to understand well the system 
recommendations, so as to be able to explain the reasons for their decisions 
to other people.One of the most important ultimate goals of explainable AI 
systems is the efficient mapping between explainability and causality. 
Explainability is the system ability to explain itself in natural language to 
average user by being able to say, "I generated this output because x,y,z". 
In other words, the ability of the system to state the causes behind its 
decision is central for explainability.

However, when critical systems (ethical decisions) are concerned, is it 
enough to explain system's decisions to the human user? Do we need to go 
beyond the boundaries of the predictive model to be able to observe a cause 
and effect within the system?

There exists a big corpus of research work on explainability, trying to 
explain the output of some blackbox model following different approaches. 
Some of them try to generate logical rules as explanations. However, It is 
worth noting that most methods for generating post-hoc explanations are 
themselves based on statistical tools, that are subject to uncertainty or 
errors. Many of the post-hoc explainability techniques try to approximate 
deep-learning black-box models with simpler interpretable models that can be 
inspected to explain the black-box models. However, these approximate models 
are not provably loyal with respect to the original model, as there are 
always trade-offs between explainability and fidelity.

On the other side, a good corpus of researchers have used inherently 
interpretable approaches to design and implement their ethical autonomous 
agents. Most of them are based on logic programming, from deontic logics to 
non-monotonic logics and other formalisms.

Logic Programming has a great potential in these two emerging areas of 
research, as logic rules are easily comprehensible by humans, and favors 
causality which is crucial for ethical decision making .

Anyway, in spite of the significant amount of interest that machine ethics 
has received over the last decade mainly from ethicists and artificial 
intelligence experts, the question "are artificial moral agents possible?" is 
still roaming around.There have been several attempts for implementing 
ethical decision making into intelligent autonomous agents using different 
approaches. But, so far, no fully descriptive and widely acceptable model of 
moral judgment and decision making exists. None of the developed solutions 
seem to be fully convincing to provide a trusted moral behavior. The same 
goes for explainability, in spite of the global concern about the 
explainability of the autonomous agents' behaviour, existing approaches do 
not seem to be satisfactory enough. There are many questions that remain open 
in these two exciting, expanding fields.

This workshop aims to bring together researchers working in all aspects of 
machine ethics and explainability, including theoretical work, system 
implementations, and applications. The co-location of this workshop with ICLP 
is intended also to encourage more collaboration with researchers from 
different fields of logic programming.This workshop provides a forum to 
facilitate discussions regarding these topics and a productive exchange of 
ideas.

Topics of interest include (but not limited to):

        • New approaches to programming machine ethics;
        • New approaches to explainability of blackbox models;
        • Evaluation and comparison of existing approaches;
        • Approaches to verification of ethical behavior;
        • Logic programming applications in machine ethics;
        • Integrating logic programing with methods for machine ethics;
        • Integrating logic programing with methods for explainability.
SUBMISSIONS

The workshop invites two types of submissions:

        • original papers describing original research.
        • non-original paper already published on formal proceedings or 
journals.
Original papers must be formatted using the Springer LNCS style available 
here:

        • regular papers must not exceed 14 pages (including references)
        • extended abstract must not exceed 4 pages (excluding references)
Authors are requested to clearly specify whether their submission is original 
or not with a footnote on the first page. Authors are invited to submit their 
manuscripts in PDF via the EasyChair system at the link:

IMPORTANT DATES

Paper submission deadline: 10 May 2022

Author Notification: 15 June 2022

Camera-ready articles due: TBA

Workshop: TBA

PROCEEDINGS

Authors of all accepted original contributions can opt for to publish their 
work on formal proceedings. Accepted non-original contributions will be given 
visibility on the workshop web site including a link to the original 
publication, if already published.

Accepted original papers will be published (detailes will be added soon).

LOCATION

Fully Virtual.

WORKSHOP ORGANIZERS

Abeer Dyoub, DISIM, University of L'Aquila.
Fabio Aurelio D’Asaro, University of Verona.