My interests in M4L fall under three headings. First of all, as a psychologist and computer scientist, my interests in interdisciplinary research have always been strong. My early career in AI and Cognitive Science exposed me to a broad range of techniques and paradigms. Understanding the basis of human and machine intelligence demands an interdisciplinary approach. The Memories for Life problem space, fragmented as it currently is, could well be made more coherent and open to a wide range of disciplines, as it raises issues in both the life sciences and engineering and technology.

Second, my interests in nature-inspired computing also go back many years. The exploitation of processes, such as phylogeny, ontogeny and epigenesis, that occur in the natural world for the processing of information could help implement high-level functionality with little top-down specification. Currently, one of my research strands involves the modelling of neural plasticity, that is, the implementation of biologically-realistic models of synaptic modification and topological rearrangement in artificial nervous systems.

Third, the problems of information overload have been well-advertised, and my work with AKT, grid computing, and e-Science have all been concerned with methods of extracting as much meaningful information as possible from the deluge of content that we are creating. The application of this work to the issue of memory, and the potential for use of biologically-realistic mechanisms for information storage, retrieval and maintenance, is high. Can we use insights from psychology and neuroscience to understand the elusive notions of salience and context? Indeed, could we even begin to address the intriguing question of how to teach computers to forget?