Must NLP be Extractive? (2024)

Abstract: How do we roll out language technologies across a world with 7,000 languages? In one story, we scale the successes of NLP further into ‘low-resource’ languages, doing ever more with less. However, this approach does not recognise the fact that, beyond the 500 institutional languages, the remaining languages are oral vernaculars spoken by communities who use a language of wider communication to interact with the outside world. I argue that such ‘contact languages’ are the appropriate target for technologies like machine translation, and that the 6,500 oral languages must be approached differently. I share a story from an Indigenous community, where local people reshaped an extractive agenda to align with their relational agenda. I describe the emerging paradigm of relational NLP and explain how it opens the way to non-extractive methods and to solutions that enhance human agency.

## introduction for over half a century this community has been developing methods for so-called 'natural' language processing (nlp). by natural this community does not mean the kinds of spoken interaction most people would regard as natural. we mean documents containing a textual trace of human language, as distinct from the default kind of language to be processed by computer, which is apparently programming languages. i believe that generative ai and large language models misconstrue the nature of language, and i argue that it is time for the nlp community to take 'natural language' seriously. meta's project "no language left behind" promises to enable people to make "more meaningful connections in their preferred or native languages, @xcite people together on a global scale" @xcite . google's universal speech model will "understand the world's 1,000 mostspoken languages" @xcite . the chatbots are going massively multilingual. so it was that i listened while an african scholar described the prospects for his friend in switzerland to learn ancestral food practices from her grandmother in nigeria. a translation app would solve the language barrier, he mused. i sketched the scenario (fig. 1(a) ). yes, that's it, he said. i asked if this system would need to be trained on familial conversations with an interpreter in the middle, to be replaced by his app. which of the 20+ dialects of yorùbá would he pick? it would need to handle words for ingredients and implements that have no translation. and how would this system interpret the kinds of utterance that are common between family members, whose meaning depends on shared knowledge that the system has not been exposed to? we sat in silence. yes, it's a problem, he said, and even if it was possible, it would take too long. i asked if the woman already knew some yorùbá and if she adds it to her english. yes, she already does that, he said, and she wants to learn more. i drew another diagram (fig. 1(b) ). this is an essay about designing technologies for so-called 'unwritten' languages, responding to the widely-held belief that language technology for all is to be accomplished by ingesting ever more languages into massively multilingual models. i examine the epistemics of language work that is assumed by these technology-driven approaches: first wave nlp with symbolic methods and language-as-code, and second wave nlp with subsymbolic methods and language-as-data. i argue that, by treating all languages as bounded and standardised @xcite , these approaches misconstrue 'natural' language and limit the possibilities for technologies. what would a third wave nlp look like, one that centres natural language in the fullest sense of 'natural'? i return to the fork in the road at the beginning of ai, between artificial and augmentative intelligence @xcite . is our agenda to replicate human intelligence inside a machine, or to expand human intelligence by using machines as tools? the former requires extraction of behavioural data and takes over human agency, whereas the latter carefully enhances human agency (cf. fig. 1 ). what would it be like to take the other fork, and seek a path towards a non-extractive nlp committed to augmentative solutions? by sharing stories from my time in an indigenous community, i reveal the ingenuity of local people in repurposing extractive efforts and reshaping deficit thinking. these stories demonstrate the resilience of a minoritised speech community in pivoting from deficit to strength. they show people enacting their sovereignty and agency in shaping their lives, landscapes, and languages, in the face of the eurocentric impulse to problematise the ways that minoritised groups fall short of western norms, beginning with the label of 'unwritten language.' this indigenous habit of preserving agency is instructive for anyone who is ceding their agency to technology. what would an agency-enhancing nlp look like? a promising answer to these questions that is emerging in recent work, i believe, could be called relational nlp. relationality was always implied by the communicative intent that underlies language use @xcite . however, it cuts deeper to the way language has been passed down, how it is embedded in the land, woven into kinship, and used to accomplish more-than-physical work @xcite . ## preliminaries beyond the 500 institutional languages, the world's linguistic diversity consists of about 6,500 oral languages @xcite . if we are to develop technologies here, we should grasp something of the nature of linguistic diversity (sec. 2.1), cultural diversity (sec. 2.2); and the history of our efforts in nlp to address them (sec. 2.3). ## conclusion the agenda of language technology for all risks perpetuating epistemic harm by centering the expectation that language is primarily textual, standardised, institutional. this misses the social function of language and renders speech communities invisible @xcite . there is no path from textual sequences to meaning, when "meaning is irreducibly connected to the viewpoints, interactions, histories, and local resources available to those making sense of the interface and therefore to some extent beyond the reach of formalization" @xcite . "we need to understand the sociocultural contexts of speakers... language is impossible to separate from context -it is continually both reflecting and creating aspects of context" @xcite . i stumbled upon a non-extractive nlp through an extended engagement with an indigenous community that still inhabits their ancestral country, and who resisted work that sought to capture, commodify, and carry off their language. i came to see my attachment to technological solutions as deeply problematic. i relinquished this agenda and began learning to speak the local vernacular, participating in the local lifeworld, and grasping what 'language' is and does locally. i started asking: what's happening with the children, the climate, the country (cf. @xcite . the theme of this acl meeting on open data arises in a period where researchers seek to extend nlp to the next thousand languages @xcite @xcite . how can we scale nlp without open data? this is second wave thinking. we need to approach oral vernaculars differently. we need to theorise the new paradigm of relational nlp with an authentic and grounded notion of language. the notation in figure 8 gives an inkling of the kind of shift that i have in mind, though it over-simplifies things. in each local place where we seek to deliver language technologies, we need to ask: what is language here, what does language do here? "we should recognize the importance of designing technologies with the cultures and communities they are supposed to serve [so] they can support not only the local ontologies and voices of these peoples but empower performances and practices that bind and sustain community" @xcite . the defence of third wave nlp rests on the need to take natural language seriously. we reexamine the nature of language, linguistic diversity, and human communication. the stories i shared represent one possible way of many. indigenous spaces are full of them, thanks to the habit of learning from the country and guarding human agency. we need but look.