Evaluating Systems for the Augmentation of Human Cognition

Project description

There is a growing interest in the use of technology to extend the capabilities of the human mind. Examples include:
(i) systems that capture and represent data about human experiences in order to support retrospective memory;
(ii) systems that visualise data from multiple sources in order to help people reason and/or make considered decisions, and
(iii) systems designed to facilitate reflection, manage mood and shape emotional state.

Understanding the success of developed technologies at meeting their goal is a core part of the design process. However, current approaches to the evaluation of human augmentation systems are highly heterogeneous and there are no gold-standard measures even in a single application domain. This lack of established evaluation techniques is problematic, making it challenging for developers of new systems to compare against prior work and for users to make informed judgments about which tools they might adopt. Further, chosen measures are largely disconnected from real-world, everyday use cases, offering little-to-no-evaluative evidence with regards to an intervention's impact on everyday activities.

This project would explore means of evaluating current and future cognitive technologies, with a particular focus on developing techniques and tools that scale to large volumes of users in real-world settings. The suggested focus of this project would be on the evaluation of human memory augmentation systems, but this could be substituted for another cognitive processes on discussion with the supervisor.

A possible roadmap for this PhD may look something like:
* Year 1: A literature review that establishes the different techniques used to evaluate human memory augmentation systems. Further literature review and/or study that establishes the everyday practices by which individuals determine if their memory is performing better or worse than expected.
* Year 2: Design and development of a platform that operationalises the everyday practices identified in year 1.
* Year 3: Use of the platform to evaluate one or more human memory augmentation systems. Writing of thesis (or alternate format submission) for examination.
The student should expect to publish their work in the form of academic papers at venues such as ACM CHI, PACM IMWUT and the Computers in Human Behavior journal.

This PhD would be attractive to candidates with experience and training in human-computer interaction or other related disciplines (e.g., experimental/cognitive psychology, mobile/pervasive computing). A successful applicant is likely to have demonstrable experience of EITHER experimental design OR software development; they will need to demonstrate both capability and willingness to develop the missing skill.