We welcome original, unpublished papers including improved versions of extended abstracts or rejected papers from AAMAS, AAAI and IJCAI 2023. The submission should describe work that has not been previously published, accepted for publication, nor is currently under review by another conference or journal. Proceedings, as a part of EUMAS 2024, will be published as part of the Lecture Notes in Computer Science (LNCS) series of Springer

Submissions are solicited on, but not limited to, the following themes / questions:

• What kinds of values and value-conflicts are (in)expressible in algorithmic form?
• Can ethical behaviour be guaranteed or verified in computational media?
• Implementation of ethical reasoning mechanisms founded on non-western ethical traditions
• Can artificial moral decision-making be decoupled from mere implementation of normative ethical theories? 
• Privacy and Trust relationships between humans and machines in the presence of hybrid actions
• Implementation of ethical reasoning in logic-based methods
• Representation of ethical principles in AI agents
• Machine-learning based approaches to ethical reasoning
• Development of machine ethics in cognitive robot programs
• Robot learning for ethical reasoning
• Integration of symbolic and neural information systems for ethical reasoning
• Development of formal frameworks for ethical decision-making
• Techniques for explaining the ethical reasoning of AI agents
• Frameworks for ethical collaboration between humans and AI agents
• Building trust in intelligent systems through ethical design and interaction

Important Dates (all deadlines – AoE)

Logistics

Paper size and format – All submissions will be peer-reviewed in a single blind fashion. Submission should be at most 15 pages long, with any number of pages for references and, if needed, a clearly marked appendix and be formatted according to Springer’s LNCS format.

Submission Link: https://easychair.org/conferences/?conf=eumas2024

Organizing Committee

Vivek Nallur, University College Dublin, Ireland

Marija Slavkovik, University of Bergen, Norway

Sarah Moth-Lund Christensen, Leeds University, UK

Programme Committee

Michael Anderson, University of Hartford

Selmer Bringsjord, Rensselaer Polytechnic Institute (RPI)

Louise Dennis, University of Manchester

Maurice Pagnucco, University of New South Wales

Yang Song, University of New South Wales

Ken Satoh, National Institute of Informatics Japan

Leon van der Torre, University of Luxembourg

Jean-Gabriel Ganascia, Sorbonne, France

John P. Sullins, Sonoma State University

Kevin Baum, University of Saarbrucken

Edmond Awad, University of Exeter

John Horty, University of Maryland

Pere Pardo, University of Luxembourg

Thomas Powers, University of Delaware

Juan Carlos Nieves, Umea University

Ryan Tonkens, Lakehead University

Paul Formosa, Macquarie University, Australia

Submit your papers at: https://easychair.org/my/conference?conf=eumas2024

Paper submission deadline: 15 May 2024 (AoE)

Here’s the blurb from the conference website:

Submissions are solicited on, but not limited to, the following themes / questions:

1. What kinds of values and value-conflicts are (in)expressible in algorithmic form?
2. Can ethical behaviour be guaranteed or verified in computational media?
3. Implementation of ethical reasoning mechanisms founded on non-western ethical traditions
4. Can artificial moral decision-making be decoupled from mere implementation of normative ethical theories?
5. Privacy and Trust relationships between humans and machines in the presence of hybrid actions
6. Implementation of ethical reasoning in logic-based methods
7. Representation of ethical principles in AI agents
8. Machine-learning based approaches to ethical reasoning
9. Development of machine ethics in cognitive robot programs
10. Robot learning for ethical reasoning
11. Integration of symbolic and neural information systems for ethical reasoning
12. Development of formal frameworks for ethical decision-making
13. Techniques for explaining the ethical reasoning of AI agents
14. Frameworks for ethical collaboration between humans and AI agents
15. Building trust in intelligent systems through ethical design and interaction

The Programme Committee consists of the following:

• Michael Anderson, University of Hartford
• Selmer Bringsjord, Rensselaer Polytechnic Institute (RPI)
• Louise Dennis, University of Manchester
• Maurice Pagnucco, University of New South Wales
• Yang Song, University of New South Wales
• Ken Satoh, National Institute of Informatics Japan
• Leon van der Torre, University of Luxembourg
• Jean-Gabriel Ganascia, Sorbonne, France
• John P. Sullins, Sonoma State University
• Kevin Baum, University of Saarbrucken
• Edmond Awad, University of Exeter
• John Horty, University of Maryland
• Pere Pardo, University of Luxembourg
• Thomas Powers, University of Delaware
• Juan Carlos Nieves, Umea University
• Ryan Tonkens, Lakehead University
• Paul Formosa, Macquarie University, Australia

Sophia Chen, writing for W.I.R.E.D magazine wrote about how the field of AI is attracting physicists to peer inside the algorithms. She also mentions me, and some of the questions that I think are really relevant to the field.

Here’s hoping that we can all meet face-to-face!!

We are hoping to make it a continuing event and have applied to AAAI for acceptance as a regular symposium. There is a mailing list for those interested in continuing discussions or notices of collaboration opportunities. Please click here to sign up. The mailing list is hosted by HEANet, Ireland. You can see a “Subscribe or Unsubscribe” link in the menu on the right hand side, in a box called “Options”. Please do consider joining.

A nudge is an overt or covert suggestion or manipulation designed to influence the emotions or behaviour of a user.  Depending on your perspective, this might seem ominous or useful. All human beings are susceptible to behavioural nudges, i.e., manipulation of content, colours, choices, even the order of choices, etc., which encourage / discourage us from a particular behaviour.  Starting from behavioural economics, where Tversky and Kahneman showed that human beings (quite consistently) behave in irrational ways¹, there has been considerable research in trying to explain how individuals evaluate choices. This is in contrast to standard economic theory that used to assume that individuals were completely rational, and always self-interested agents. Perhaps the most popular explanation of such behaviour is Dan Ariely’s book – Predictably Irrational. Governments, organizations and companies have been trying to use these insights to influence how populations, societies and consumers behave. This has given rise to the study of the nudge – subtly and adaptively influencing someone’s choice without limiting their actual choices.

Combined with Big Data and Machine Learning, the use of nudges can be used by systems to influence user behaviour. A common example is the use of pre-checked boxes. If the text next to a checkbox is boring/not clearly understood/legalese, a user is tempted to leave it as they found it. That is, if a checkbox is asking for consent to bombard you with marketing material, you are tempted to leave the checkbox checked if you don’t really understand what is being asked, or the language used is such that it insinuates a loss if you uncheck it. This is a nudge because you are quite capable of un-checking the box, but you have chosen to not do it.  Given the power of Big Data, an algorithm could identify which kind of nudges work on you personally, and then ensure that only those nudges are shown to you.  These sort of nudges can clearly be used for all kinds of purposes. For example, ensuring that users make good choices (say, encouraging them to save for retirement) or making choices where the organization benefits (say, accepting tracking cookies).

The IEEE committee’s focus is on how human beings (or design teams and organizations) should ensure that their nudges are ethical. There is clearly no standard system of ethics that everyone subscribes to. So the committee is focussed on specifying a design process which will at least ensure that every company/organization that creates intelligent systems that uses nudges, will explicitly confront the ethical choices it is making.

His abstract, from his phd application, is as follows:

Artificial Intelligence (AI) techniques such as reinforcement learning and deep learning have enjoyed some success in accomplishing tasks at human-level capability in the recent past. It is expected that several human jobs will be replaced by intelligent and autonomous systems in the near future. When domains that have direct links/involvement with the community, such as health-care, social data mining and advertising, personal assistants and autonomous vehicles, use artificial intelligence, the importance of values and the morality of an AI system comes into the picture. These systems could easily encounter situations that contain a moral dilemma which will affect a community or an individual’s life. Therefore, in order to decide which actions must be taken in such situations, we need to introduce a sense of values into these AI agents. One way to infer a sense of values onto intelligent systems is by embedding ethics into them. As a result, there are many attempts being made to provide AI systems with a sense of ethics. However, there is no general consensus on what type of ethics (i.e. utilitarian ethics, deontological ethics, virtue ethics, the principle of
double effect) can/should be embedded into an AI or what Approach (i.e.  Evolutionary computing, Multi-agent systems, Machine learning, Deep learning, Reinforcement Learning)  would be most suitable for implementing these types of ethics. The need to find philosophical theories and technological methods that can be used to build an artificial agent – and which can be entrusted to act as an ethical agent – is of vital importance in the future of intelligent agents. My research will concern itself with techniques in computer science that can be used to implement ethical behaviour

Let’s come back to this in four years time to see where he’s got

To facilitate more discussion on the topic, a mailing list was set up on HEANet’s listserv service. It is meant for everyone who is interested in the inter-disciplinary aspects of how, why, and what ethics should be implemented in machines. Clicking on the link above will take you to the HEANET website. You can see a subscribe and unsubscribe button in the menu on the right hand side called options. Please do consider joining if you are interested in society, AI, philosophy, technology, law and how they intersect.