Studying human values in software engineering

Authors: Emily Winter and Maria Angela Ferrario
Associate Editor: Jinghui Cheng (@JinghuiCheng)

The Values in Computing (ViC) project: http://www.valuesincomputing.org

Why do human values matter for software engineering? Recent years have seen high profile software scandals and malpractices, in which individual privacy and social democracy have been undermined, as in the case of Cambridge Analytica’s use of Facebook data [1] and even human lives lost, as in the case of Boeing 737 [2]. As another recent IEEE Software post puts it, we are heading into an age of considerable ‘values debt’ [3], as the negative societal consequences, both intended and unintended, of our software systems mount up.

There is a pressing need then to understand how human values operate, to develop methods and tools to study them in a software engineering context, and to build on this understanding to consider how SE research might contribute to a more socially responsible software industry.

How do values operate?

We use values research from social psychology as our framework. In particularly, we draw on Schwartz’s values model, based on extensive empirical research spanning the last three decades. Schwartz’s work has identified, through survey research, a range of values that are recognised across cultures and that operate relationally. Schwartz’s values model operates across two key oppositional axes: self-enhancement vs. self-transcendence; and openness vs. conservation [4].

We also use Maio’s work, which considers values as mental constructs that can be studied at three different levels: the system level (the relationships outlined by Schwartz); the personal level (the different interpretations of values held by individuals); and the instantiation level (how values are expressed through behaviours) [5]. At the system level, for example, a software engineer who is highly concerned about their personal career development (achievement) is – according to Schwartz’s model – less likely to be concerned about the environmental sustainability (universalism) of the systems they are building. At the personal level, software engineers may have different interpretations of high quality code (achievement) - e.g. ‘code that does the job’ vs. ‘elegant code’. At the instantiation level, a concern with privacy may manifest in a development decision not to track user queries.

Understanding values in software engineering

In order to study human values in a software engineering context, we required methods that were relatable and relevant to the software engineering community. We used Q-methodology as our starting point [6]. Q-methodology is a well-established method designed to systematically study subjectivity. It involves participants taking part in a card ranking exercise; they are interviewed about their decisions and multiple participants’ ‘sorts’ can be statistically analysed. The structured nature of the sorting helped with the systematic articulation and analysis of the qualitative data elicited from participant’s narratives; it was also important that the card statements were specific to the software engineering community. We used the newly revised ACM Code of Ethics [7] as a basis, choosing principles that corresponded with Schwartz’s values types and filling in any gaps by creating statements in accordance with the missing values. It was important, in order to gain a full understanding of the software engineering context, to consider a wide range of values, not just those considered ethical, in order to understand fully values trade-offs within complex industry contexts. Power and profit were as important for our study as honesty and the social good.

The role of the researcher in promoting a socially responsible software industry

One of our key findings is that people interpret and act out values in very different ways. Two of our study participants, for example, who both placed the statement ‘it is important for me that the public good is the central concern of all professional computing work’ in their ‘top 3’, showed almost opposite understandings of this value. For Laura, for example, the public good was about optimising the user experience: she explained they would ‘analyse the data once the user hits our website; we would then optimise off that behaviour’. By contrast, Stuart didn’t want to overly ‘structure’ the experience of users. He explained that an e-commerce site could ask users ‘do you want us to try and automate your offers? Yes or no’. He viewed an overly structured web experience as being oppositional to users’ freedom of choice.

By simply introducing the Q-Sort to software engineers, we have already encouraged articulation of these differences of interpretation, things that are often taken for granted and rarely explained. Maio and Olson, for example, argue that values often act as truisms, ‘widely shared, rarely questioned, and, therefore, relatively bereft of cognitive support’ [8]. Carrying out this kind of research may be the first step in encouraging a more values-aware and values-reflective technology industry – in which the taken-for granted may begin to be reflected upon and articulated. Avenues for future work include identifying opportunities for light-weight interventions that enable values reflection as an integral part of the agile process, for example.

As well as encouraging discussion of values within industry, we (SE researchers and academics) need to foster reflective, critical skills within our students. For example, we used the Q-Sort as a teaching tool in our Software Studio, a 20-week long module for second year Software Engineering undergraduate students. Within this module, students work in small teams to ideate, design and develop a software application. We introduced the Q-Sort to teams early on in the process as a way of encouraging values articulation and prioritisation that would underpin the entire software engineering decision making process. As well as generating discussion, reflection and critical thinking, this led to concrete future design decisions. One team, for example, went on to adopt a ‘most-vulnerable-first’ approach to system design and development for their train journey planning app, prioritizing search needs for people with disabilities, people with young children, and the elderly. In contrast to standalone ethics courses, the Software Studio embedded values and ethical considerations into the module; they were integrated with technical skills, not an optional add-on.

This is one example of teaching practice that supports the Values in Computing mission: that the next generation of computing professionals will be equipped with the technical tools, foundational knowledge, and critical skills necessary to distinguish responsible software engineering decisions from those that are potentially harmful to self and society.

References

1. The Guardian, Cambridge Analytica Files. Retrieved on 12 August 2019 from https://www.theguardian.com/news/series/cambridge-analytica-files
2. Helmore, E. (2019) ‘Profit over safety? Boeing under fire over 737 Max crashes as families demand answers’, The Guardian. Retrieved on 12 August 2019 from https://www.theguardian.com/business/2019/jun/17/boeing-737-max-ethiopian-airlines-crash
3. Hussain, W. (2019) ‘Values debt is eating software’, IEEE Software blog. Retrieved on 12 August 2019 from http://blog.ieeesoftware.org/2019/07/values-debt-is-eating-software.html
4. Schwartz, S. H. et al. (2012) ‘Refining the theory of basic individual values’. Journal of personality and social psychology 103(4): 663-688
5. Maio, G. R. (2010) ‘Mental representations of social values’. in Advances in Experimental Social Psychology (Vol 42). Academic Press, pp. 1–43.
6. Winter, E. et al. (2019) ‘Advancing the study of human values in software engineering’. In Proceedings of the 12^thInternational Workshop on Cooperative and Human Aspects of Software Engineering (CHASE '19). IEEE Press, pp. 19-26. 
7. ACM (2019) Code of Ethics and Professional Conduct. Retrieved on 12 August 2019 from https://www.acm.org/code-of-ethics
8. Maio, G. R. and J. M. Olson (1998) ‘Values as truisms: Evidence and implications’. Journal of Personality and Social Psychology, 74(2): 294-311.