Paper Short Abstract:

The paper explores how platform workers navigate algorithmic systems in their everyday working lives. It considers how the ethnographer, through fieldwork, creates “algorithmic folklore” together with the research participants to understand the unpredictable forces of platform algorithms.

Paper Abstract:

Platforms have become deeply integrated into everyday life—we work, communicate, shop, order food, and even find therapists through them. The term “platform economy” serves as a broad descriptor for various forms of labor mediated by these platforms (Berg, 2018). Increasingly, these platforms are governed by algorithms, placing workers in situations where they must navigate and negotiate their working conditions directly with or through these algorithms. This dynamic has given rise to phenomena such as algorithmic precarity (Chan, 2022) and algorithmic insecurity (Wood & Lehdonvirta, 2021). Workers who rely on algorithm-driven platforms to sustain their livelihoods develop strategies to interpret and engage with these opaque systems, forming what Bucher (2016) describes as "algorithmic imaginaries."

Drawing on long-term ethnographic fieldwork with a diverse range of platform workers—including content creators, delivery workers, and platform-dependent creative professionals—this paper examines how these individuals attempt to understand and adapt to the algorithms shaping their lives. Reflecting on my own role as an ethnographer, I explore the ways my research also depended on algorithmic systems: finding respondents, maintaining connections, tracking their content, and tailoring platform experiences to suit my research objectives. This paper delves into how both platform workers and the ethnographer create and share narratives, beliefs, and strategies—what I term “algorithmic folklore”—as a means of protecting themselves and trying to stay ahead of the enigmatic forces that govern their professional and personal realities.

Paper Short Abstract:

As AI and algorithms increasingly shape the "digital self" (Turkle, 1984), ethnographers must go beyond studying the individuals we aim to understand to also analyze the algorithms they interact with and the forms of digitality that shape their lives. This paper delves into the challenges and opportunities ethnographers encounter in navigating this complex interplay.

Paper Abstract:

This paper examines how AI and algorithms shape both the objects of ethnographic inquiry and the methods of digital ethnography. My doctoral research investigates how recruitment algorithms mediate talent selection and how job seekers adapt to these algorithmic filters to enhance their perceived employability. As part of this research, I, as an ethnographer, engage intensively with recruitment algorithms by participating in an "imitation game". This process involves not only replicating the algorithmic experiences of my interlocutors but also embodying a "hireable persona" that aligns with algorithmic filters, adopting traits and behaviors favored by these systems.

Drawing inspiration from the Turing Test, which assesses machines’ ability to mimic human behavior, this paper introduces the concept of a Reverse Turing Test. In this test, job seekers must conform to machine-defined standards of employability, reshaping their self-presentation to meet algorithmic expectations. Moreover, the paper argues that ethnographers themselves face a similar Reverse Turing Test, as they must navigate and adapt to algorithmically mediated environments to engage meaningfully with their research subjects.

This dual-layered exploration highlights the broader implications of algorithmic systems in redefining ethnographic practice. It underscores how these systems not only influence the behaviors and strategies of their users but also challenge the methodologies and positionalities of ethnographers. The paper contributes to critical discussions on the intersections of technology, labor, and ethnography, emphasizing the need to critically engage with the unseen forces shaping digital research and interaction.

Paper Short Abstract:

Social media platforms like Instagram and TikTok shape beauty standards through the collaboration between users and algorithmic systems. This research examines how algorithms mediate body representations and embodiment, utilizing media diaries and interviews to explore how AI-driven systems co-curate feeds and shape perceptions of beauty.

Paper Abstract:

Social media platforms like Instagram and TikTok are algorithmically curated spaces where users’ interactions with their feeds shape and reshape representations of beauty and the body. My dissertation, part of the interdisciplinary research project Curating the Feed, explores how idealized beauty standards are constructed through the collaboration between users and algorithmic systems. This collaboration remediates ‘ways of seeing’ (Berger 1972) and relating to representations of bodies and one’s own body, as platforms mediate both the visual and embodied practices of beauty.

Algorithmic systems, as active constituents of the digital field, significantly shape how bodies—particularly faces—are represented, how beauty is enacted through technology, and how these ideals are practiced in real life. These invisible forces highlight the more-than-human agentic capacities of AI, raising critical questions about the nature of digital ethnographic engagement: How do algorithmic systems rewrite perceptions of embodiment, both online and offline?

This research utilizes long-term media diaries, in-depth and chat interviews, offering a nuanced ethnographic approach that accounts for the interplay between human and more-than-human actors. By examining how these systems co-curate image flows, the study investigates how algorithmic systems actively shape perceptions of embodiment, complicating established ethnographic methods of writing and unwriting narratives.

By focusing on the recursive entanglements between socially informed bodies, algorithms, and visual regimes, this study contributes to broader anthropological discussions on technology, embodiment, and the evolving challenges of conducting ethnographic research in algorithmically governed digital spaces.

Paper Short Abstract:

This paper examines the integration of artificial intelligence (AI) into academic labour (research, teaching, and service), addressing the challenges within the higher education sector subsumed under capital.

Paper Abstract:

This paper examines the integration of artificial intelligence (AI) into academic labour, addressing the challenges within the higher education sector subsumed under capital. Under the claim of enhanced efficiency, academic institutions increasingly deploy machine learning and natural language processing-generated AI technologies to streamline recruitment, admission, and performance evaluation processes, as well as to customize teaching materials and assessments. AI's (costly) 'purchase' comes both as a tool for administrative convenience and an instrument of surveillance and standardization, but as other recently embraced new technologies, it introduces serious concerns regarding discipline, control, and transformations of academic labour. The potential for AI to infringe on academic freedom, intellectual property, and worker rights through intensified monitoring and profiling activities reflecting and reinforcing intersectional inequalities are all critical concern. Yet, employing a materialist lens, the paper shows venues overlooked by most emergent academic literature on the subject: the enormous surplus extraction and value capture in higher education through formal and real subsumption of academic labor into segmented tasks that can be easily automated and outsourced, casualised, deprofessionalised and disembodied. At the same time, I show how traditional hierarchies, rituals, temporal and spatial dimensions of scholarly work make it particularly susceptible to such changes. Here, I also outline where anthropology stands in comparison/contrast with other disciplines. I thus outline potential venues for research and resistance, taking into account new vantage points of capitalist capture and their strategic choke points.

Paper Short Abstract:

Based on on-going ethnographic research, we will explore the implications of AI and algorithms on conduct of online ethnographies, in a sensitive issue as death. Does the use of AI, on-line memorials and chatbots help people in overcoming grief or do they prevent them from carrying it on?

Paper Abstract:

Death used to entail a great deal of writing: sending letters or posting on newspapers to announce the death of a dear one. What happens now when the memory of the dead one is shared by 3000 facebook “friends”, who no longer write letters but post on social media? How does one feel when receiving a fb invitation for a birthday celebration from someone who passed away a while ago and became a “digital ghost”?

This paper focuses on dying in the digital age in Portugal, where attitudes towards death have changed immensely in the past thirty years; lately, the interplay of AI and death has accelerated the changes. People turn to on-line memorials to imprint the memoires of the departed beloved ones, but also to seek comfort in their grief. What implication does this have on ethnographic research? How can ethnologists research the implications of the use of social media on grief, as what was before written in the tombstones or in cards sent to the grieved ones is now written digitally in on-line memorials? Furthermore, with AI, we now have persons using chatbots and other digital means to communicate with their dead.

Based on on-going ethnographic research, we aim to explore the implications of AI and algorithms on the equity and conduct of online ethnographies, especially in a sensitive issue as death. Does the use of AI, on-line memorials and chatbots help people in overcoming grief or, on the contrary, do they prevent them from carrying it on?