Data sharing initiatives, big data, and recently publicised commercial research initiatives have shone a spotlight on a problem that has always existed. Data about people, whether it is publically available on the internet or gathered in a rigourously confidential research environment can reveal far more about those people than the original data gathering body--much less any participants--might expect.
HCI ethics has traditionally focused on how to avoid negative consequences for research participants while they are participating or as a direct result of the research. The processes around these issues do not apply to commercial research, and offer little or no guidance when one is working with data available on the internet or gathered by someone else. Nonetheless ethical challenges can arise when working with all kinds of data--commercially or academically gathered, curated or gathered by an automated process, public or confidential--and we must, as a discipline, find ways to manage these issues.
The limitations of formal ethics processes--that they only apply in academic contexts, and then not to how data is used after it is collected, or to publically available data--are well known to HCI researchers. Given the significant increase in publically available data and the more and more frequent forays of HCI into sensitive areas, the ethics of how we handle data post-collection is of increasing research importance.
We invite position papers from participants with ethical challenges in:
Using data gathered from less-privileged or currently vulnerable individuals in a respectful way
Using publicly available data in ethically sensitive and accountable ways
Using data gathered legitimately (e.g. data from participants who later withdrew from a study)
The use of big data
The use of commercial data
Working on with sensitive and controversial subjects
The potential misuse of critically necessary data (e.g. appropriation of clinical data gathered for one purpose for another purpose)
Any other ethical data use challenges not mentioned here
We seek contributions from CHI, UX, library and information sciences and related disciplines that specifically address the challenges of working with research data. We hope to use these contributions to provoke discussion and inform the beginnings of a new best practice in research ethics.
We welcome all relevant proposals regardless of how unconventional they may be.
Participants should submit an abstract of up to four pages in the CHI-Extended Abstract format without identifying materials to allow for double-blind peer review. Papers will be peer reviewed by a minimum of two reviewers. Papers will be reviewed on the basis of their ethical sensitivity, relevance to the workshop themes and their potential to generate discussion at the workshop.
The workshop will run within the programme of ACM SIG-CHI, in Montreal, Canada on the 21st April. Accepted participants must register for the workshop and at least one day of CHI. Participants can expect a highly interactive workshop, with two panel sessions and two small-group interactive sessions. The long-term aim of this workshop is to generate an edited book.
Full details of the workshop are available at hci-data-ethics.com
Submission: 2nd February 2018
Notifications of Acceptance: 22nd February 2018
Workshop: 21st April 2018
George Buchanan, University of Melbourne
Dana McKay, University of Melbourne
Cosmin Munteanu, University of Toronto Mississauga
Jenny Waycott, University of Melbourne
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