Dr Simone Stumpf
- Reader in Responsible & Interactive Artificial Intelligence (School of Computing Science)
Dr. Simone Stumpf is a Reader in Responsible and Interactive AI at University of Glasgow, UK. I have a long-standing research focus on user interactions with machine learning systems. My current research includes self-management systems for people living with long-term conditions, developing teachable object recognisers for people who are blind or low vision, and investigating AI fairness. My work has contributed to shaping the field of Explainable AI (XAI) through the Explanatory Debugging approach for interactive machine learning, providing design principles for enabling better human-computer interaction and investigating the effects of greater transparency. The prime aim of my work is to empower all users to use intelligent systems effectively.
I am interested in the design and development of user interfaces that help end-users to interact with AI systems more successfully. Of particular interest to me is to help these users to better better understand and to appropriately trust the system, and I have conducted research in Explainable AI to do that. An underpinning of my approach is to design AI systems ethically and responsibly, so that they are free from bias, unfairness or inaccuracies, and to help users to correct them if they are. A lot of my work has therefore been in interactive machine learning to allow users to directly interact with AI systems and teach them how to behave.
I also have an interest in applying AI to user-generated and personal data, especially in the context of heath and well-being. I have worked closely with people who are blind or have low vision, and people living with dementia and/or Parkinson's Disease.
I am a firm believer in including everyone in design and I champion co-design approaches in my research. I take an intersectional approach to my work but am partciaulry invested in making solutions usable and useful to people with physical and cognitive impairments, as well as people of all genders.
- 2019-2021, Fujitsu Ltd., Japan, Principal Investigator, CoFAI: Codesigning Fair AI Interactions, ¥21,500,000. Industry-funded investigation into interfaces for human-in-the-loop AI fairness for a variety of stakeholders, and cultural aspects in fairness perceptions.
- 2019-2021, Microsoft AI for Accessibility, UK, Principal Investigator, ORBIT: Meta Learning for Personalised Object Recognition, $193,000. Collection of a large dataset for teachable object recognition using few-shot learning from blind and low vision people. Release of public dataset containing 4733 videos of 588 objects from 97 collectors. Developing a curriculum for AI for accessibility for people who are blind and low vision as additional impact activity.
- 2018-2022, Engineering and Physical Sciences Research Council (EPSRC), UK, Co-Investigator, INTUIT: Interaction design for trusted sharing of personal health data to live well with HIV, £816,126. Work package leader for investigating trust, identify, privacy and security attitudes for data-sharing between people living with HIV, with input to the design and implementation of a personal information management app.
- 2017-2020, Engineering and Physical Sciences Research Council (EPSRC), UK, Co-Investigator, SCAMPI: Self-Care Advice, Monitoring, Planning and Intervention, £1,006,003. Work package leader for co-designing an app to set up and monitor goals and activities as part of a selfcare plan. Input to sensor-based activity recognition as part of wider toolset. .
I am co-cordinator for COMPSCI5012 Internet Technologies (ITECH) in Session 2, 2021/22.
Professional activities & recognition
Professional & learned societies
- Senior Member, Association of Computing Machinery (ACM)
- Member, AAAI
- Memeber, UXPA UK