Computing Research Communities
Data Ethics Among Computational Researchers
Lead: Michael Zimmer with Jessica Vitak & Jacob Metcalf
The current state of ethics practice among pervasive data researchers will be investigated using three mixed-methods approaches. First, a content analysis of research publications from a set of relevant venues (such as WebSci, ICWSM, related ACM proceedings) will seek to determine how data ethics is discussed, if at all, within formal dissemination of research that relies on pervasive data. Second, an analysis of curriculum and degree requirements for computational and data science-related doctoral programs at R1 and R2 research institutions will determine the extent to which training in data ethics is present for new researchers in the field. Third, a survey of computational and pervasive data researchers will gain deeper insights into common data ethics training received, and measure current attitudes and practices on ethical issues relevant to their work with pervasive data.
In partnership with the ACM SIGCHI working group on ethics, we will use data collected from the survey to develop guidelines that clarify “best practices” for social computing researchers to ensure protection of individual users in a dataset. These surveys will also measure researchers’ attitudes toward controversial research practices, including using deception, reporting public data, and ignoring sites’ Terms of Service (TOS). In previous work by the research team, the acceptability of these areas exhibited high variance across social computing researchers, but further unpacking of why researchers have these opinions will help with developing cross-cutting guidelines that account for variations in research practices across disciplines.
Ethics of Data Sharing Practices
Lead: Michael Zimmer with Matthew Bietz
In 2013, the White House’s Office of Science and Technology Policy (OSTP) directed federal agencies to require researchers to better account for and manage the digital data resulting from federally funded scientific research with the goal of making the data publicly accessible. The NSF, for example, has mandated that investigators must share with other researchers the primary data gathered in the course of work under NSF grants. In the case of research involving pervasive data, such data sharing practices can pose unique ethical dilemmas. This project will explore how pervasive data researchers craft their data management plans, assess whether concerns of data ethics are reflected in the details of the plans, and determine how effectively the plans have been executed in terms of the ethical dimensions of sharing pervasive data sets. The project will analyze data management plans for NSF projects in SBE and CISE dealing with pervasive data sets, and a subset of researchers who have shared datasets will be interviewed to obtain a richer understanding of their decisions and approaches to sharing data.
Informal and Non-Traditional Data Ethics Practices in Research
Lead: Jacob Metcalf with Katie Shilton & Casey Fiesler
This subproject investigates data ethics practices outside of the purview of established ethics regulations. Although IRBs and mandated ethics training have a large footprint as the formal venue for “ethics” in science and engineering research, informal and non-traditional forms of ethics practice, education, and reasoning are often more influential. For example, conference paper committees have become an ethics review gateway in pervasive computing because university-based IRBs often do not review computing research. Similarly, design practices for data-intensive products have become a site for determining how longstanding ethics commitments— such as consent or privacy—can have traction inside these new models of research. This research looks at pervasive computing researchers and seeks access to sites where informal and nontraditional ethics practices occur. Research questions include:
- How do researchers decide what rules to follow?
- Who is influential in setting informal norms and guiding informal practices?
- How should norms be propagated when non-experts have access to sophisticated research tools and datasets?
Computing Research and Terms of Service
Lead: Casey Fiesler with Michael Zimmer
One of the recent controversies within social computing research pertains to whether researchers should be bound by the rules of TOS, such as prohibitions on automated methods to collect publicly available data. Both the law and ethics surrounding this practice are unclear. The ACLU is currently challenging the application of the Computer Fraud and Abuse Act to researchers, and the wording of the ACM Code of Ethics is ambiguous as to whether breaking TOS is contrary to professional ethics. Additionally, prior work has shown that TOS are difficult to understand and that most users do not read them. Using similar analysis and survey methods from PI Fiesler’s prior work examining perceptions of TOS, this study will address whether pervasive data researchers are aware of (and understand) the TOS terms that could apply to their work, as well as researchers’ attitudes towards the ethics of following TOS.