Paper short abstract:

This paper presents a collaborative interdisciplinary project between anthropology and artificial vision programming. It aims to design alternative interfaces that 'model interpretation' —instead of displaying AI outputs— through non-standard co-presence between both human and artificial agencies.

Paper long abstract:

Despite its relevance and popularity in the cognitive ecology of the current digital age, AI often exercises its agency 'off-stage' (Gell), through technological artifacts that mediate most of our daily actions and, at the same time, offers them intelligence, vision, self-learning and other qualities that were, until now, regarded as human qualities. Such is the case of artificial neural networks for image recognition, classification and generation; a 'secret agent' that co-shapes visual culture, redefining —ideologically or unconsciously— both what it means to see, and what there is to see, since how we see the world, makes it visible.

This paper focuses on an experimental interdisciplinary project developed with artificial vision programming, currently developed in collaboration with deep learning engineers and researchers in computational co-creativity and information visualization. The goal is to use anthropological theories about the 'co-composition' of agency in our technological cognitive ecologies (Latour; Lévy; Sánchez-Criado) in dialogue with the ethnographic findings that arise from working on/using algorithms alongside programmers. This project aims to design alternative human-AI interfaces that are able to activate a non-standard co-presence between both human and artificial agencies. This allows a 'modeling interpretation' (Drucker) of visual and archival resources, through the visualization of (and interaction with) artificial vision 'learning' processes, instead of displaying output information that emerges from its obscured activity.

Paper short abstract:

AI futures emerge in the “hinge” between techno-ideologies and the everyday failings of algorithmic systems. For anthropologists to engage with these, they must attend to this convergence. In addition, to intervene ethnographically they must build interdisciplinary and participatory collaborations.

Paper long abstract:

Despite repeated non-fulfillments and disappointments, AI remains a field surrounded by myth in which past and futures converge. Algorithmic systems are written through a layering over of prior code and the preexisting techno-social infrastructures which help to realize and convey them. Possibilities for code then are channeled by previous iterations, scaffolded onto what came before. Yet, algorithmic systems conjoin temporalities which are working in reverse and contingent fields of tension, acting in effect within a “trans-temporal hinge”—one vector “anticipatory,” the other, “protospective” (Pedersen/Nielsen 2013). In this presentation we argue that the first is an ideological movement towards a future where social myths are always in a state of becoming. For algorithmic systems, these anticipatory futures are guided by three foundational techno-idealizations: the myth of operability, neutrality and unfetteredness. The second vector is the “present” moment where these same myths are revealed to be, in practice, continually negotiated, layered on, and breaking down in relation to what came before. Typically, this second temporality is the moment of ethnographic intervention, where everyday unravelings become the etic evidence of ideological power. Building on our experiences with algorithmic systems as ethnographers in the field of bioscience and human computation, we argue that ethnographers need to better attend to the “hinge”—this intersection of ideological momentum and the protospective grounding of its inverse failure, out of which the future emerges. We argue further that anthropologists should intervene within and alongside algorithmic practices and form interdisciplinary collaborations to engage with AI and futures in real-time.

Paper short abstract:

We propose the idea of an AI/nthropology as a new way to conduct anthropological research. We describe risks and opportunities when using AI to see 'patterns of culture'.

Paper long abstract:

Since its inception, anthropology's mantra has been to understand culture from "the native's point of view" (Malinowski1920). The goal has been to create a comprehensive reflection of the vast diversity of human social worlds in their entirety. Historically, anthropology has sought to provide an "inside" account of a new cultural reality that from the outside may have had characteristics of a "black box". However, since the field underwent a reflexive turn focusing on the cultures of the anthropologists themselves (Foley2002), anthropology has turned its critical gaze toward technologists and we have seen an increase in forensic ethnographies of algorithmic decision making (Seaver2017), algorithmic accountability (Eilish, 2019) or data collection procedures (Angèle, 2017) where machine learning engineers are being studied like "natives" (Downey, 1998) and socio-technical systems as culture (although the field of cybernetics and Science and Technology Studies (STS) is not new, Moss et al, 2019). However, instead of applying anthropological methods to the study of AI, this paper lays out how AI can be applied in new ways to gather cultural insights at scale. We describe the idea of an AI/nthropology, its potentials and risks, and what it can look like when ML and anthropology complement each other. We describe how both ML and social sciences are fundamentally inductive methods, provide examples for how ML can be applied to understand group biases, cultural practices and intersectionality, and whether computational approaches in anthropology are able to address the subjectivity/objectivity problem (Fleck, 1937; Keller, 1985).

Paper short abstract:

We present the Cryptic Commons, a co-created space where cyber-physical systems are objects for transdisciplinary research and public debate. What new tasks do AI and the digital era present for anthropology? How can anthropology critically and caringly engage with these new socio-technical forms?

Paper long abstract:

CRYPTIC COMMONS is a space and concept that is under development and is formed through relations– a kind of socio-technical construction site – where data security, digitalization, cryptography and cyber-physical systems are objects for transdisciplinary debate and co-creation.

It is conceived and constructed by anthropologists and with cryptographers and engineers during a research project aiming to develop algorithms and protocols that secure data and privacy in future cyber-physical systems. Based on ethnographic fieldwork among cryptographers and engineers the Cryptic Commons has, so far, materialized as a physical and online exhibition, a science TV series, and an art film, as well as an interdisciplinary research workshop.

In this paper, we present and perform elements from the Cryptic Commons, and through these materializations we ask what new tasks, methods, modalities, and approaches AI and the digital era present for anthropology, and how anthropology can engage critically and caringly with these new socio-technical forms. Co-creating the Cryptic Commons paves the way for new anthropological engagements into interdisciplinary work in the fields of datafication and social life in future cyber-physical systems.

We argue that new modes of engagement are needed, in academia as well as in public spaces, for the building of vocabularies and practices that can secure the well-being of communities and social structures. Socio-mathematics is one vocabulary to develop for the construction of a data-democracy. Enter with us into the Ideal, the Real and the Actual of interdisciplinary Futures Anthropology!

Paper short abstract:

The paper explores the relevance of the concept of sympoiesis for an engaged and interdisciplinary Futures focused AI Anthropology.

Paper long abstract:

Sympoiesis, a concept first proposed by a student of environmental science Beth Dempster in the 1990s but more recently scrutinised by Donna Haraway, signifies a process of collective and collaborative constitution, or - as Haraway puts it - “making-with”. As such, it allows us to explore “intra-active relatings”, which cannot be explained by "self-producing" approaches to being and living (Haraway 2016). At the same time, paying attention to constitutive relatings offers a crucial means for cherishing livability in deeply disturbed environments we all inhabit (Tsing et al. 2017).

In this paper, I elaborate on the significance of the concept of sympoiesis for Interdisciplinary Futures focused AI Anthropology. I argue that a sympoietic approach can advance anthropologists’ engagements with both futures and AI in at least three different ways. First, it could help further develop futures anthropology, pointing towards an additional technique for this anticipatory and interventionist anthropological practice (Pink and Salazar 2017). Second, it challenges the mainstream approaches to AI as autonomous entities in the world and offers a way to explore data-driven algorithmic systems at a planetary scale (Crawford 2021). Third, it enables us to interrogate how new relationalities further reconfigure anthropological practice, as anthropologists begin their own experimentations with computational tools (Ruckenstein 2019). For all these reasons, the concept of sympoiesis opens a fertile pathway for anthropologists to participate in co-creating liveable AI futures.