What Natural Language Generation Means for Authorship and Why We Should Care

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.