Developing Team Design Patterns for Hybrid Intelligence Systems

With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of...

Is Google making us smart? Health self-management for high performance employees and organisations

Globally, the burden of disease is rising. High performance employees and organisations need to improve their health self-management options and skills. Unfortunately, there are an overwhelming number (> 500,000) of new health publications every year. We aim to design a health AI on top of Scholar Google, to support rapid employee do-it...

A Design Pattern Language for Hybrid Intelligent Teams

The field of Hybrid Intelligence (HI) is like a vast land with many tribes that speak different languages. Our goal is to develop a lingua franca to unify the peoples of the HI land.We expect our language to facilitate documentation and communication of research results and thus collaboration among various HI fields by making use of design...

Team design patterns for moral decisions in hybrid intelligent systems: A case study of bias mitigation

Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is key. The use of Team Design Patterns (TDPs) can advance this goal by describing successful and reusable...

Evaluating XAI: A comparison of rule-based and example-based explanations

Current developments in Artificial Intelligence (AI) led to a resurgence of Explainable AI (XAI). New methods are being researched to obtain information from AI systems in order to generate explanations for their output. However, there is an overall lack of valid and reliable evaluations of the effects on users' experience of, and behavior in...

Interpretable confidence measures for decision support systems

Decision support systems (DSS) have improved significantly but are more complex due to recent advances in Artificial Intelligence. Current XAI methods generate explanations on model behaviour to facilitate a user's understanding, which incites trust in the DSS. However, little focus has been on the development of methods that establish and...

Hybrid collective intelligence in a human–AI society

Within current debates about the future impact of Artificial Intelligence (AI) on human society, roughly three different perspectives can be recognised: (1) the technology-centric perspective, claiming that AI will soon outperform humankind in all areas, and that the primary threat for humankind is superintelligence; (2) the human-centric...

Public speaking training in front of an imaginary or virtual audience: A randomized controlled trial

When preparing for a public speech, practicing with an audience is suggested to be effective in enhancing speech performance. However, it is often impractical to organize an audience to practice a presentation. Virtual reality can provide a solution, i.e., practicing with a virtual audience. This paper studied this practicing technique for...

Guided or factual computer support for kidney patients with different experience levels and medical health situations: Preferences and usage

Personalization of eHealth systems is a promising technique for improving patients’ adherence. This paper explores the possibility of personalisation based on the patients’ medical health situation and on their health literacy. The study is set within the context of a self-management support system (SMSS) for renal transplant patients. A SMSS...

Improving service matching and selection in ubiquitous computing environments: A user study