Value Engineering in AI (VALE Track)

With the development and spread of AI techniques, ensuring the adherence of AI's behaviour to legal and ethical principles has become a major subject. General fear of the unintended effects of AI systems, by its actions and its use of personal data, has led to a strong demand for trustworthy AI. This is a central concern that has become prominent both in public opinion and policy maker's agenda. The EU High-Level Expert Group on AI, convened by the European Commission in 2018, published a report on "Ethics Guidelines for Trustworthy AI" stating that AI systems should be: 

• lawful, complying with all applicable laws and regulations 

• ethical, ensuring adherence to ethical principles and values 

The VALE track of the VECOMP 2024 workshop focuses on the second issue: ensuring AI respects human values. To achieve this, there is a need to develop software systems that reason about human values and norms, implement these values through norms, and ensure the alignment of behaviour with those values and norms. We argue that just as values guide our own morality, values can guide the morality of software agents and systems, bringing machine morality closer to reality. The result would be value-aware systems that take value-aligned decisions, interpret human behaviour in terms of values and enrich human reasoning by enhancing the human's value-awareness. 

Today there is a growing wealth of work in the field of AI on accounting for human values and working towards value-aligned behaviour. The VALE Track intends to bring in research on value engineering together and foster in-depth discussions on the topic.

We note that the VALE Track of VECOMP 2024 is a continuation of the past and successful VALE workshop at ECAI 2023.

Topic Areas: 

The relevant topics include, but are not limited to: 

• Value and norm representation 

• Value and norm learning 

• Value and norm agreement 

• Value and norm conflict resolution 

• Value-driven argumentation and negotiation 

• Value-driven decision making 

• Value-driven system design 

• Value-alignment 

• Value-driven explainability 

• Legal questions in value and norm enforcement