Workshop 21 Feb

21 February Lunchtime Seminar
12-1.30pm
Agnes Cuming Room, Newman Building D520
Catered lunch will be provided.
All are welcome to attend

We are kicking off the series of lunchtime mini-workshops with a two-person panel on the ethics of information collection in big data domains.

Ethics of using big data in humanities and social sciences.

Smart-phones and other digital devices provide unprecedented opportunities to extract data about humans. This opportunity is paralleled with the development of data-mining methods that allow analysing and comparing groups of people and their behavior. As the use of these datasets and analytical methods become more prevalent in conducting research, established ethical principles may fail to protect human participants. By taking a closer look at the current principles of research involving human subjects, this talk will focus on the challenges of addressing and enforcing ethical norms within humanities and social science research projects that use big data.

Necessary and Opportunistic Data Collection

Marinus Ferreira - UCD CEPL

Here I suggest that we can transplant work done in the ethics of war into the domain of big data ethics when distinguishing between necessary and opportunistic interventions. In the ethics of war many theorists distinguish between necessary (so-called 'eliminative') killing, where there is some aim which cannot be achieved in the presence of the enemy, and opportunistic killing, where there is some aim that can only be achieved through the killing of the enemy. The thought is that opportunistic killing is harder to justify that eliminative killing, even if the aim in question is worthwhile. I suggest that we can use this same distinction by thinking about data collection as a way to eliminate gaps in our knowledge of existing conditions, and accordingly evaluating its use by way of how the data enables the pursuit of further aims. This allows us to distinguish necessary data collection, where the data negatively contributes to the aim by eliminating this gap, and opportunistic data collection, where the presence of the data that fills the gap allows for a positive enabling of some further aim. I illustrate the suggestion by discussing a paradigmatic instance of necessary data collection, medical auditing, from a paradigmatic instance of opportunistic data collection, targeted advertising.