Paper short abstract:

Transhumanist philosophy exerts a profound influence on contemporary visions of AI. This paper critiques key issues within this school of thought and advocates for educational projects in which students incorporate anthropological thinking and ethics into the design of AI technologies.

Paper long abstract:

Transhumanist philosophy, with its focus on leveraging technology to expand the powers of self in competitive struggle, exerts a profound influence on contemporary visions of AI. This paper critiques key issues within this school of thought and advocates for educational projects in which students incorporate anthropological thinking and ethics into the design of AI technologies. I discuss two frameworks that can help in this endeavor. The first is a general framework, supplied by Arjun Appadurai, for thinking about anthropology as a future-making discipline. According to his view, anthropologists should not only analyze the logic and forces of cultural reproduction but should also find ways to interrupt and displace them. Ideally, such work would manifest an “ethics of possibility” by incorporating other (non-status quo) ways of being into those processes. The second is a design framework, supplied by cultural theorist Anne Balsamo, for developing what she calls technological imaginations—mindsets that enable people to think critically and creatively with technology. I present her method as a vehicle for incorporating an ethics of possibility into students’ thinking about practical and desirable applications for AI technologies. To illustrate her method and provide an example of an anthropologically inspired technological imagination, I look at a concept called Wave+ that was produced by students in a course taught by the author.

Paper short abstract:

ChatGPT's launch in November 2022 signifies a major shift in AI's role in education and anthropology. This paper explores the integration of generative AI and LLM’s in post-fieldwork anthropology teaching and supervision, considering their impacts on the analytical process.

Paper long abstract:

The Launch in November 2022 of ChatGPT has occasioned what Silicon Valley pundits have called an ‘Oppenheimer moment’ to capture the gravity and impact of generative AI. Moving beyond initial tech hype, the Large Language Models have since been given serious attention at all levels, also in educational institutions. They are sure to affect the way we study, learn, and think, including the way we teach and practice anthropology. In other words, these new technologies demand our attention.

Anthropologists have been hesitant to embrace generative AI, and for good reasons: We have legitimate concerns about the technologies being an extension of Western economic and cultural dominance. Furthermore, the technologies run counter to the nature of ethnography and anthropological analysis, which demands extensive time and immersion and contrasts sharply with the rapid information processing capabilities of chatbots — or ‘Google on speed’ as one commentator called them. However, aligning with core anthropological principles, this paper adopts an exploratory, curious, and critically reflective stance: It details a six-month project integrating ChatGPT into supervisory practices within post-fieldwork stages of anthropology education. This integration aims to assess and discuss how LLMs can enhance analytical skills in anthropology while remaining cautious of potential conflicts with ethnographic values and objectives. The study focuses on master's and Ph.D. students, offering insights into how these advanced technologies might or might not be reconciled with traditional anthropological sensibilities and methodologies.

Paper short abstract:

Word clouds have become a common feature in higher education teaching. The “Wolf Rapsody in C-Major” case study introduces how applying a generative machine learning approach to the analysis of ethnographic data can contribute to softening the polarised debate about the return of large carnivores.

Paper long abstract:

Word clouds have become a common feature in higher education teaching. Intrigued by their popularity, this contribution sets out to explore the viability and usefulness of “word cloud seeding” in ethnographic anthropological practice. To what effect? The “Wolf Rapsody in C-Major” case study introduces how applying a generative machine learning approach to the analysis of ethnographic data can contribute to breaking down the polarised debate surrounding the return of large carnivores to Western continental Europe. The traveling exhibition “Kushti Bok” (meaning “Good hunger”, or “all is well” in the Romani language) by David Weiss serves as a testbed for establishing the effectiveness of word clouds that seek to visualize the “vibe” of the core problematics of “Rewilding Europe”, as well as the newer sensibilities of the Anthropocene Zeitgeist at street level. Of particular concern to this elucidation of ecological sentiments are the paradoxes and dilemmas arising from the Green Deal’s endeavor to safeguard biodiversity, while legislators deliberate on weakening the protected status of the wolf in the European Union. The alphabetical letters “C” (in English), respectively “K” in German, provide the entry point. Why this linguistic detail matters to the programmer as well as to the anthropologist relates to the underlying wordplay (Bock/Bok). The “C” is the key to decoding this artistic intervention made possible by the consonant shift and end syllable devoicing – a perk that seeds the clouds presented here.

Paper short abstract:

This paper provides a notion of big data and an account on its adoption in several social sciences, with an emphasis on Anthropology and a focus on methodological challenges, debates, controversies and epistemological issues on analysing information through AI and producing digital ethnographies.

Paper long abstract:

This paper introduces the notion of big data and provides an account on its progressive adoption in several social sciences since 2010, with an emphasis on Anthropology. In this sense, the methodological challenges of these new ways of information understanding, processing and representation are approached, as well as the debates and controversies it has risen within the traditional quantitative/qualitative question of these disciplines in particular. That drives towards epistemological issues on analysing information, in which statistical procedures such as machine learning and other types of Artificial Intelligence are crucial for answering questions and solving problems through big data and, therefore, towards one of the characteristics of Anthropology: interdisciplinarity.

Moreover, the paper frames this phenomenon within the practices of digital ethnography from a critical point of view which considers human experiences, practices, things, relations, social worlds, localities and events as its objects of study. Consequently, the central but unequal role of Internet and the digital in modern-day societies demands more and more the ethnographer to displace and to expand his/her interests and methods towards multi-sited approaches, as well as towards multiple types of sources beyond text such as visual, film, audio or mapping ones. Since the integration of them into any analytical process is complex, big data and AI are becoming fundamental means to apprehend human individuals, societies and cultures more widely, as well as their diversity, so it may be stated that they deserve a place within anthropological research and, therefore, into the teaching and learning of the discipline.

Paper short abstract:

This paper analyzes GenAI's dual effects on anthropological thinking, both limiting views and enhancing debate. It advocates for a paradigm shift from generation to augmentation, emphasizing the need for reflective cybernetic dialogue in understanding technology's impact on critical thought.

Paper long abstract:

This paper examines the dual role of technology, specifically generative artificial intelligence (GenAI), in shaping contemporary critical thinking in anthropology. It addresses the paradoxical nature of AI as both a constraint and an enabler in the development of human thought processes. On one hand, algorithm-driven platforms can limit perspective and reinforce existing beliefs, potentially leading to cognitive tunnel vision. This phenomenon is critical in understanding the challenges posed to critical thinking in an increasingly digital world.

In contrast, generative AI can also act as a tool for augmenting human thought. AI systems can provide counter-arguments, simulate debates, and expose users to diverse perspectives, thereby enriching intellectual diversity and fostering a more nuanced approach to problem-solving.

This paper advocates for a paradigm shift working with GenAI from focusing on generation to augmentation, emphasizing the need for transforming thought processes in the age of AI. It also outlines a re-humanized future of technology where cybernetic dialogue, clear communication, original, disruptive ideas, and relational thinking become paramount. This involves reevaluating the frameworks and assumptions underlying idea generation, moving towards a more reflective and critical approach. The paper concludes by highlighting the transformative potential of AI in revolutionizing intellectual engagement and urging a reevaluation of our relationship with technology in fostering intellectual growth.