Bio

Muhammad Abdul-Mageed maintains a Canada Research Chair in Natural Language Processing and Machine Learning at the University of British Columbia, Canada. His research focuses on deep representation learning and natural language socio-pragmatics, with two main goals: (1) development of `social' machines for improved human health, safer social networking, and reduced information overload; and (2) use of machine learning as a vehicle for making discoveries with and about human language. Professor Abdul-Mageed is Director of UBC Deep Learning and Natural Language Processing group and Co-Director of the Interpares Trust AI Project.

Project

A vast treasure of records and data exists on paper and in analogue forms. More and more organizations are digitizing their physical records to increase their accessibility, to help conserve non-digital archives through the creation of digital copies, and to unlock possibilities for how digitized data may be used. Digitization has the potential to profoundly change the way archival records are accessed and how researchers and users engage with them. Yet digitization projects are complex and involve multiple processes based on various functions, expertise, and technologies. The introduction of AI technologies has added yet another layer of complexity to digitization processes. Digitization may be improved through the intervention of AI technologies, and in turn, digitization may help to increase the availability of diverse and historical data sets that can enrich machine learning and AI technologies. The processes and potential impacts of digitization are therefore important to consider and understand.