The role and challenges of education for responsible AI

Artificial intelligence (AI) is impacting education in many different ways. From virtual assistants for personalized education, to student or teacher tracking systems, the potential benefits of AI for education often come with a discussion of its impact on privacy and well-being. At the same time, the social transformation brought about by AI requires reform of traditional education systems. This article discusses what a responsible, trustworthy vision for AI is and how this relates to and affects education

Open agent systems???

E-institutions are envisioned as facilities on the Internet for heterogeneous software agents to perform their interactions and thus forming truly open agent systems. We investigate how these heterogeneous agents can determine whether an institution is one in which they can participate. We propose a layered approach which is supported through a (traditional) middle agent that is part of the environment. Starting with a basic compatibility of message types, each extra layer ensures a higher degree of compatibility, but requires also extra sophistication in both the information required and the matching algorithms. In this paper, we describe reasoning about how an agent should take on a specific role, message matching, and protocol compatibility. We explore the issues in the context of an actual accommodation agent built in JACK, and a travel agency institution built in ISLANDER

A Conversational Agent for Social Support: Validation of Supportive Dialogue Sequences

Recently, we proposed a dialogue model for social support. To validate this model, we analyzed 23 real world chat conversations. After some adjustments, the dialogue sequence patterns specified in the model cover 87.4% of the data. Based on this result, we conclude that the dialogue model accurately describes comforting conversations. Next, the model will be incorporated into a comforting ECA

Evaluating organizational configurations

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Service Performance Assessment: A PI Toolset Methodology for VEs

Part 2: Knowledge-Based ServicesInternational audienceNowadays service sector is becoming more and more relevant in building successful collaborative economies. In this environment Virtual Enterprises (VEs) are forcing a change in the way traditional manufacturing systems are managed. Therefore measuring service performances plays an important role in turning company strategic goals into reality. Performance Indicators (PIs) consist in a supporting tool to assess service efficiency and effectiveness. Consequently, determining the most significant activities which need to be controlled and measured through proper PIs becomes essential. Within this paper, a PI Toolset is going to be presented and tested through industrial use case. The PI Toolset has been developed to support VEs in selecting significant activities, to manage governance processes and to support the design and implementation of specific PIs related to the precise use case objectives. Finally, a lesson learnt approach has been adopted so to stress strengths and weaknesses of both proposed methodology and tools

OperA/ALIVE/OperettA

Comprehensive models for organizations must, on the one hand, be able to specify global goals and requirements but, on the other hand, cannot assume that particular actors will always act according to the needs and expectations of the system design. Concepts as organizational rules (Zambonelli 2002), norms and institutions (Dignum and Dignum 2001; Esteva et al. 2002), and social structures (Parunak and Odell 2002) arise from the idea that the effective engineering of organizations needs high-level, actor-independent concepts and abstractions that explicitly define the organization in which agents live (Zambonelli 2002).Peer ReviewedPostprint (author's final draft