{"id":184,"date":"2024-01-18T17:40:23","date_gmt":"2024-01-18T17:40:23","guid":{"rendered":"https:\/\/wp.lancs.ac.uk\/caiss\/?p=184"},"modified":"2024-01-18T17:40:23","modified_gmt":"2024-01-18T17:40:23","slug":"caiss-talk-series-reports-professor-wendy-moncur","status":"publish","type":"post","link":"https:\/\/wp.lancs.ac.uk\/caiss\/2024\/01\/18\/caiss-talk-series-reports-professor-wendy-moncur\/","title":{"rendered":"CAISS Talk Series Reports: Professor Wendy Moncur"},"content":{"rendered":"\n
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CAISS were privileged to have Professor Wendy Moncur from the University of Strathclyde deliver our second talk in October.<\/p>\n

Wendy leads the Cybersecurity Group and her research focuses on online identity, reputation, trust and cybersecurity and crosses many disciplinary boundaries. Her current research \u2013 the 3.6million AP4L project \u2013 develops privacy enhancing technologies (PET\u2019s) to support people going through sensitive life transitions. The research is looking at four transition groups: (i) living with cancer, (ii) leaving the armed forces, (iii) LGBT+ and (iv) relationship breakdowns.<\/p>\n

Wendy talked to us about \u201cNavigating bias in online privacy research\u201d. She stressed that it is important that we ask the right questions and whilst doing this we also ask the right people. As researchers what do we ourselves \u201cbring\u201d to the research as we use our own \u201cinterpretive lens\u201d and it is important that we communicate our findings clearly so that others can understand the results.<\/p>\n

Wendy then went on to discuss our individual online identities, this is co-constructed, made up of data about an individual posted by themselves and by other people and organisations. The internet in general is swimming in personal data, the minute we share anything we have lost control \u2013 once it is \u201cout there\u201d this information persists. Her explanation of how threads of personal data can be used to construct information regarding an individual was very thought provoking; e.g. if you share your Strava run data then someone can easily ascertain your home address or where you work if you run in your lunch break!<\/p>\n<\/div>\n<\/div>\n

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To mitigate against bias in the research Wendy advocated the following:<\/p>\n<\/div>\n<\/div>\n

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