Industry Funded PhD Scholarship on Trust and Transparency: Understanding and Communicating with Machine Learning and Artificially Intelligent Agents
Assoc Prof Leif Azzopardi
Assoc Prof M Halvey
No more applications being accepted
Funded PhD Project (European/UK Students Only)
This Industry Funded PhD Scholarhsip will explore how people trust and understand the actions and decisions of Artificial Intelligence (AI) and Machine Learning (ML) agents and develop methods to communicate and interact efficiently and effectively with such agents. This will be in the context of high pressured and complex information environments, where people are placed under enormous amounts of stress to deal with huge amounts of data, make sense of the information, and to report and act on emerging events, threats and anomalies. Often operators need to focus on the important features concerning suspicious events and targets while maintaining overall comprehensive situational awareness. A single mistake could mean the difference between life and death.
Since human cognition and concentration is limited, intelligent agents that collaborate with human operators are being developed to ensure that teams of agents and humans are working together in an optimal fashion - in order to ensure success in mission critical environments. There is a need to develop agents that are sensitive to the situation and who can minimize the overall load and burden placed upon the operators. Furthermore there is a need to develop interfaces that more efficiently communicate sensor data without overwhelming and overloading operators, and the need to develop the underlying agent technology that intelligently collaborates with operators. The overall goal of this research area is to reduce the effort and cognitive burden in assessing high dimensional real time data in high pressured complex information environments, by providing a collaborative intelligent assistant that helps to:(1) identify potential relevant events, (2) assess the importance and quality of those events, and (3) whether they are targets or threats and assists in further investigating, monitoring and coordinating the share of information and intelligence amongst the team.
This project will involve the combination of Human Computer Interaction (HCI) and Machine Learning (ML) to understand and explore how people interact with intelligent agents:
- Human Computer Interaction (HCI) / Human Agent Interaction (HAI) - exploring how people build up trust with intelligent agents, and
- Machine Learning (ML) / Artificial Intelligence (AI) - developing intelligent agents promote transparency through explaining and communicating their actions.
The project focus will be tailored depending on the candidate’s experience, background and interest.
The project will be supervised by Dr. Leif Azzopardi, who is an Associate Professor in the Department of Computer and Information Sciences. He leads the Interactive Information Retrieval research. The project will be co-supervised by Dr. Martin Halvey, who is also an Associate Professor in the department who specialises on Human-Computer Interaction.
The candidate will join our team within the Strathclyde iSchool, in the Department of Computer and Information Sciences, and work with team who undertake research on developing and understanding intelligent agents in a variety of contexts i.e. customer service agents, conversational search agents, intelligent search agents, etc. The iSchool at Strathclyde, is one of the leading and largest iSchools in the UK, and consists of over 35 staff and researchers working on a variety of problems from machine learning, algorithm bias and explainability to information seeking, retrieval and behaviour to human computer interaction and information interaction.
We are currently offering fully-funded studentship commencing October 2018. Due to the funding nature of this call only Home/EU students are eligible to apply. This is a fully-funded PhD studentship and will run for a four year period. It includes:
- A fee waiver equivalent to the Home/EU rate
- A competitive tax-free stipend for a maximum of four years
How good is research at University of Strathclyde in Computer Science and Informatics?
FTE Category A staff submitted: 20.20
Research output data provided by the Research Excellence Framework (REF)
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