electronic literature authorship

Natural language generation (NLG) – the process wherein computers translate data into readable human languages – has become increasingly present in our modern digital climate. In the last decade, numerous companies specialising in the mass-production of computer-generated news articles have emerged; National Novel Generation Month (NaNoGenMo) has become a popular annual event; #botALLY is used to identify those in support of automated agents producing tweets. Yet NLG has not been subject to any systematic study within the humanities.

This paper offers a glimpse into the social and literary implications of computer-generated texts and NLG. More particularly, and in line with the ELO 2018 Conference’s 'Mind the Gap!' theme, this paper examines how NLG output challenges traditional understandings of authorship and what it means to be a reader. Any act of reading engages interpretive faculties; modern readers tend to assume that a text is an effort to communicate a particular pre-determined message. With this assumption, readers assign authorial intention, and hence develop a perceived contract between the author and the reader. This paper refers to this author-reader contract as ‘the hermeneutic contract’.

NLG output in its current state brings the hermeneutic contract into question. The hermeneutic contract’s communication principle rests on two assumptions: that readers believe that authors want them to be interested in their texts, and that authors want readers to understand their texts. Yet the author of a computer-generated text is often an obscured figure, an uncertain entanglement of human and computer. How does this obscuration of authorship change how text is received?

This paper will begin with an introduction to, and brief history of, NLG geared towards those with no previous knowledge of the subject. The remainder of the paper will review the results of a series of studies conducted by the researcher to discern readers’ emotional responses to NLG and their approaches to attributing authorship to computer-generated texts. Studies have indicated that a sense of agency is assigned to an NLG system, and that a continuum from authorship to generation is perhaps the most suitable schema for considering computer-generated texts. Who is responsible for the text? Are computer-generated texts worthy of serious literary analysis? What do computer-generated texts reveal about human creativity and lived experience?

The paper will conclude with an argument for why consideration of the social and literary implications of NLG and computer-generated texts is vital as we venture deeper into the digital age. Computer-generated texts may not just challenge traditional understandings of authorship: they may engender new understandings of authorship altogether as readers explore the conceptual gap between human and computer language production.

Many digital narratives feature avatars onto which we project our agency, aspirations, and biases – consciously and unconsciously. This paper presents two projects towards understanding why we construct the avatars that we do and how these avatars impact us. The upshot is that electronic literature authors should take constructing avatars in digital systems seriously since they can potentially reinforce real-world stereotypes.

The first project consists of a system called AIRvatar (named for the Advanced Identity Representation), which is an avatar constructor for collecting analytical data such as mouse-click events and the amount of time spent in the different parts of the menu.

With AIRvatar, we found that social phenomena such as gender-related stereotyping could be observed through choices made by players (Lim, 2015). For example, female players appeared to conform more toward stereotypical notions of masculinity and femininity. Many gave male avatars significantly more strength and endurance points than female avatars, and significantly more intelligence and wisdom points for female avatars than male avatars. This effect appears related to the idea of “cross-­stereotyping,” a type of “identity tourism” (Nakamura, 2008) in which players attribute a more limited range of behaviors to other genders than they do to their own. The fact is that avatars constructed by users introduce new audience-driven types of stereotyping. Electronic literature authors must ask whether, if such stereotypes are commonplace, we want to subvert, challenge, or change them in the systems we create.

The second project studies how avatar construction impacts user performance, identity development, and emotional engagement (Kao and Harrell, 2015). Experiments were conducted in our game called Mazzy (1892 online participants total in the studies discussed here). We contrasted outcomes during which users either deployed a minimal avatar (black dot), an abstract avatar (geometrical shape), or a likeness avatar (that looks like the user). We also investigated the impacts of user face photos, famous figures, and user-selected role models.

Minimal and shape avatar users were more engaged, had significantly higher enjoyment, and less difficulty. Likeness avatar users had significantly higher affect towards their avatars, yet reported significantly higher difficulty. Results suggest that Black or African American participants have lower affect towards the game than White participants in the user face photo condition. Yet, women using famous figures performed better than when using shape avatars and low performing users with role-model avatars did better than low performing users with shape avatars.

Although game-oriented, our results are more broadly informative for electronic literature. The fact that the replayability and emotional engagement are impacted by the types of avatar used in light of the demographics of those users is important. We have shown that such systems impact how users see themselves, perform, and feel about themselves. As such, authors have a great responsibility to their users. We hope that the results and discussion here will help inform electronic literature authors who are concerned about their impacts on diverse audiences.

(Source: ELO 2015 Conference Catalog)