The Department of Computing Science at Umeå University is seeking candidates for a PhD student position in Computer Science with focus on socially intelligent systems for human-agent collaboration. Deadline for application is March 31, 2021.
The Department of Computing Science is a dynamic environment with around 150 employees representing more than 20 countries worldwide. We conduct education and research on a broad range of topics in Computing Science. The department’s research on Artificial Intelligence has a strong international position, in particular on the topics of collaborative and responsible AI. In these areas, the focus is on human-AI interaction and on the ethical and societal impact of AI. Our researchers collaborate with several national and international research groups, and have active links with industry and policy organisations. Visit https://www.umu.se/en/research/groups/interactive-and-intelligent-systems/ and https://www.umu.se/en/research/groups/responsible-artificial-intelligence/ for more information.
Wallenberg Foundations and WASP-HS
The project is financed by the Wallenberg Foundations. The student will be affiliated to WASP-HS, the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program – Humanities and Society. The WASP-HS graduate school provide foundations, perspectives, and state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. It thus provides added value on top of the existing PhD programs at the hosting university, providing unique opportunities for students who are dedicated to achieving international research excellence in a research and other activities conducted within WASP-HS please visit https://wasp-hs.org/.
Human-centred Artificial Intelligence (AI) is a novel field of research that is striving towards designing systems for best serving humans, beyond “hard optimization” of classic performance criteria such as efficiency or profit, which may end up costing to users and society e.g. by impersonal and impractical systems. Yet, little research offers theories, models, and practical solutions for designing AI systems that are capable of reducing the anxiety experienced by its users – one of the largest tolls to human health, economy, personal and social development. Worse, classic AI systems generally cause greater anxiety to their users: the over-optimized strategies it generates leave little room for error and unexpected situations and thus high stress on the involved humans.
Think for instance of an itinerary planner for finding the shortest route from A to B. Such a planner will disregard risks and their consequences, such as an unexpected delay of a bus that might cause cascading missed connections and thus missing a plane in the end. Such a plan exposes users to anxiety, at least until they get out of the “risky bus” in time. What if the system would propose another route, say 10% longer, but with a very high certainty of no delay? How much anxiety would such alternatives avoid?
Another example is how to manage a situation where anxiety is at stake, such as the COVID-19 crisis. Decisions in reaction to the crisis can cause anxiety-inducing situations for the individual, potentially leading to an increase of anxiety disorders (e.g. depressions). What is the net cost in terms of anxiety incurred by these decisions, both in the short run (e.g. the relief of immediate reaction) and in the long run (e.g. uncertainty of economic and social actors)? How can we generate pragmatic decisions and plans that account for classic performance criteria augmented with the anxiety experienced by users, both immediately and in the long run?
This PhD project strives to build intelligent systems capable of answering such questions.
In this research, the PhD student will contribute to the study of how to design AI systems capable of accounting for the anxiety a situation is causing to various actors and how decisions can be adjusted for balancing the achievement of system goals with the anxiety provoked by the decisions.
This research involves the following general tasks:
1) understand the dynamics of anxiety from a human-science perspective (psychology, cognitive science, behavioural science, philosophy);
2) build computational models of anxiety and include such models within goal-oriented systems;
3) develop software based on these models;
4) apply these models for validation in user experiments
The research is based on articles such as:
Miceli, M., & Castelfranchi, C. (2005). Anxiety as an “epistemic” emotion: An uncertainty theory of anxiety. Anxiety, Stress, and Coping, 18(4), 291–319.
The PhD student will have the opportunity to develop a high interdisciplinary profile and expertise on making computational models of human cognitive components that can be included in state-of-the-art AI problem-solving techniques.
About the position
The successful applicant will be employed by Umeå University and receive salary for a period equivalent of four years of full time PhD studies. PhD students are typically offered the opportunity to gain teaching experience on suitable undergraduate courses. If so, the employment period is extended to cover the time spent on teaching (at most 20 %). Expected starting date is 1st of June 2021 or as otherwise agreed.
The applicant is required to have completed a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from overseas, or equivalent qualifications. To fulfil the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed courses at second-cycle level degree equivalent to 90 ECTS credits in computing science, or in a subject considered to be directly relevant for the specialisation in question, preferably cognitive science or psychology. A solid ability and interest in computing sciences is assumed.
Since research is conducted in an international research environment, the ability to collaborate and contribute to teamwork, and a very good command of the English language, both written and spoken, are key requirements.
It is a strong merit if you can demonstrate knowledge about / experience with
- former experience with making mental models for agents (e.g. virtual agents with emotions).
- working with human subjects.
- partial or complete Courses in cognitive sciences or psychology
- reading and writing formal/mathematical text
- empirical research (from theory to implementation and experimentation),
- Markov Decision Processes
- building mid-scale programmes (e.g. a small game),
A complete application should contain the following documents:
- A cover letter including a description of your research interests, your reasons to apply for the position, and your contact information
- A curriculum vitae
- If applicable, copy of completed BSc and/or MSc thesis and other original research publications
- Certified copies of degree certificates, including documentation of completed academic courses and obtained grades
- Contact information for two persons willing to act as references
- If applicable, description / documentation of a similar project you have developed earlier
- Up to 2 pages describing how you envision to contribute to the project
The application and attached documents must be written or translated to English or Swedish. Documents must be in Word or pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than March 31, 2021. Reference number: AN 2.2.1-1780-20.
The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed. The recruitment aims at a balanced gender distribution, and in particular women are encouraged to apply.
For additional information, please contact Assoc. Prof. Loïs Vanhee email@example.com or Prof. Virginia Dignum firstname.lastname@example.org.
We look forward to receiving your application!
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