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The Human-Technology Interaction Group (HTI) of the School of Innovation Sciences, in collaboration with the Eindhoven Artificial Intelligence Systems Institute (EAISI), is looking for a PhD-student on effective human-AI collaboration via explanations and interactive AI.
Are you interested in improving the way in which humans interact with AI-systems in the domains of health and education? Are you interested in studying how explanations and interactive AI, tailored to the user and its context, could result in optimal human-AI collaboration and thereby improving human functioning in the workplace?
Artificial Intelligence has an increasing impact on the ways in which humans work, live, and learn. In this project we focus on AI systems providing recommendations or suggestions to improve human functioning in the domains of education and health. For example, systems that can help surgeons to identify malignant cells from pathology slides or automatic feedback systems that aid students in their learning. However, the full potential of these systems is often not obtained due to the fact that these systems are not always fully understood or because they are not fully adapted to the user and the (complex) context.
To reach the full potential of these AI systems, it is especially important to have an optimal human-AI collaboration. For this, the AI needs to go beyond merely showing the recommendation. Therefore, this project aims to determine how effective explanations of AI and interactive machine learning can be used to improve human-AI collaboration. The use of explanations and interactivity of AI in health and education tailored to the user's needs and context, has been very limited, with some rare exceptions. Here, we argue that effective explanations of AI are not necessarily synonymous to explaining the underlying logic of the model. Neither might providing full interactivity effectively aid the user. Carefully considering the users' needs in combination with the capabilities of the AI system lies at the heart of this project.
In this project, the human-AI collaboration will be evaluated within two different domains: health and education. By applying this project in two different contexts (health and education), we aim to determine which aspects of explanations and interactive machine learning are more domain-specific and which aspects generalize to other domains as well.
The research groups
The Department of Industrial Engineering & Innovation Sciences (IE&IS) is a leading school in the area of industrial engineering and management science as well as innovation sciences. IE&IS has several BSc and MSc programs housed in two separate schools: Innovation Sciences (IS) and Industrial Engineering (IE). The School of Innovation Sciences focuses on the realization and impact of technological innovations at the individual, organizational, and societal level. The Human-Technology Interaction (HTI) group is part of the school of IS. It concentrates expertise in social sciences - particularly psychology - and engineering, studying technology in the service of human wellbeing within the broader context of a socially and ecologically sustainable society.
The Eindhoven AI Systems Institute (EAISI) combines all TU/e Artificial Intelligence activities. Top researchers from various research groups work together to create new and exciting AI methodologies and applications with a direct impact on the real world. TU/e has been active in the field of AI for many years, which gives the new institute an excellent starting position to build upon.
Eindhoven University of Technology (TU/e)
- Recently completed (or be close to the completion of) a Master's degree in Human-Computer Interaction, Cognitive Psychology, Artificial Intelligence, or a related field that shows an interest in both intelligent systems as well as their applications (preferably in the domains of heath or education).
- Demonstrable experience in conducting empirical and/or experimental research, including knowledge of and demonstrable experience with applying (state of the art) statistical techniques.
- Excellent mastering of the English language and good communication skills. Note that there is no Dutch language requirement.
We expect you to:
- further develop the project proposal based on academic literature, and in collaboration with organizations in the educational and healthcare domain
- design empirical (field) studies
- design lab/online experiments
- statistically analyze data obtained from field studies and experiments and report on results
- communicate practical implications of your research to specific stakeholders/the general public
- present the findings of your research at (inter)national scientific conferences
- publish papers in internationally renowned academic journals
Conditions of employment
- A meaningful job in a dynamic and ambitious university.
- A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
- To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
- To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
- A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
- Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
- Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
- A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.