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- Convenors:
-
EJ Gonzalez-Polledo
(Goldsmiths, University of London)
Silvia Posocco (Birkbeck, University of London)
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- Format:
- Panel
- Sessions:
- Thursday 9 June, -
Time zone: Europe/London
Short Abstract:
The collection and analysis of bioinformation, or information that derives from biological life processes, increasingly shapes contemporary socialities. This panel takes bioinformation as an ethnographic lens to explore new interfaces between biology and anthropology.
Long Abstract:
The collection and analysis of bioinformation, or information that derives from biological life processes, increasingly shapes contemporary socialities. Bioinformation ontologies and infrastructures demand thinking through and against indeterminacy, multiplicity, interoperability and cooperation, as the orders they create deeply transform the answers biology can provide to anthropologists - and as concepts, theories and methods tied to bioinformation processing travel through and across worlds. Against this background, practices of bioinformation accession and aggregation from the colonial period to the digital age raises questions about the political structures that sustain fantasies of ‘total knowledge’, particularly in the aftermath of legacies of violence.
Thinking how life emerges and is made readable through bioinformation has taken anthropologists to confront technological spectres and yet to be realised potentialities of connection. This panel takes bioinformation as an ethnographic lens to explore new interfaces that emerge between biology and anthropology through the particular prism of data aggregation, computation and control. The panel proposes a cross-sectional approach to bring together case studies in synthetic biology, forensics, biotechnology, biosecurity and surveillance. The panel aims to connect these cases to address the question of biopolitics by interrogating bioinformation itself as an archive, that is, a sedimented substance in which agents, collectivities, structures and relations make, and transduce, social orders. Indeed, the analysis of bioinformation, as a ‘pattern that connects’ socialities and futures has not only enabled the extractive economies of the Anthropocene, but is promising a new world to come from a full rewriting of nature in the fast-approaching Plastocene.
Accepted papers:
Session 1 Thursday 9 June, 2022, -Rafi Grosglik (Ben-Gurion University of the Negev) Dan M. Kotliar (University of Haifa)
Paper short abstract:
The study of human microbiota has suggested seeing humans as “homo-microbis”– complex biomolecular networks composed of a human host and microbes. Focusing on the microbiome-based personalized nutrition plan, we argue that the homo-microbis is necessarily also a homo-algorithmicus.
Paper long abstract:
In the last two decades, the study of human microbiota – the vast microbial communities in and around the human body – has highlighted human and microbial interdependency and co-evolution, thus offering a radical epistemic and ontological shift from the individualistic, modernistic view of the human self. Research has accordingly suggested seeing humans as “homo-microbis”– complex biomolecular networks composed of a human host and its associated microbes. But what happens to this epistemic shift when it gets commodified and implemented in technological devices such as apps for dietary recommendations? Based on an ethnographic account of a prominent scientific research project that offers microbiome-based personalized nutrition, and of the successful start-up that emerged from it, this paper examines the popularization and commodification of the microbiome, and the ensuing constitution of the human subject. We show that human-microbe relations are acknowledged in the discourse of personalized nutrition, but the microbiome is paradoxically seen as a data-driven, individuating marker that does not question humans’ individuality, but rather, highlights it. We further argue that this view necessarily depends on opaque machine learning algorithms that produce a quantified self – a supra-human, neoliberal agent who relies on meticulous self-tracking, including food-tracking. We accordingly show that the homo-microbis is also a homo-algorithmicus – a being that can only access its own nonhuman sub-parts by blindly following opaque algorithmic recommendations on an app. Thus, we argue that microbiome-based personalized nutrition is highly dependent on cultural, economic, and technological determinants, and is accordingly shaped by them.
Chandra Kala Clemente-Martinez (Autonomous University of Barcelona)
Paper short abstract:
This paper aims to reflect on the governance of rights and access to biogenetic information within the field of adoption. This paper uses the framework ‘biolegality’ to address the interrelationship among law, biology, rights, and personhood.
Paper long abstract:
Do children born after ARTs and adoptees have the right to access this information in the age of reproductive biotechnology? Human reproductive technologies -including assisted reproductive technologies (ARTs), donation, and adoption- imply significant biotechnological, subjective, ethical, political, and legal challenges. This paper examines these challenges through the analysis of the ‘right to know’, which refers to the possibility of accessing information about a person’s background.
Access to information is more complex for persons incorporated into a family through assisted reproduction due to the multiplicity of persons involved, the variety of reproductive technologies, the high technological development and the unique mobility of persons and tissues. Engaging with a case study of Spanish-Nepalese adoptions, in this paper I seek to explore the governance of rights in the age of ‘biolegality’ (De Leeuw & van Wichelen, 2020). It focuses on the existence of many barriers to access to information, making the potential search for origins difficult. It highlights the notable tension between law and its translation into practice.
Brígida Riso (Lisbon School of Medicine)
Paper short abstract:
Biobanks are support infrastructures for biomedical research that store biological samples. This ethnography highlighted the processes of bioinformation construction: besides the cooperative practices sustaining the biobank, power-knowledge relationships are central in defining samples collections.
Paper long abstract:
Biobanks are commonly designed to support biomedical research, by systematically collecting human biological samples associated with medical and personal data, to respond to scientific research demands.
This study followed the biological samples trajectories from their collection at the hospital, to their processing into the biobank, and then to the distribution to researchers. This has brought to the fore the relationships between medical doctors, sample’s donors, biobank staff, and biomedical researchers.
Although the biobank is said to be a structure for openly sharing samples and data for the scientific community, this research highlighted the mechanisms enabling the biobank to function, and particularly whether doctors and researchers cooperate and exercise their power over the samples and the sick bodies.
There is a set of practices that influence the construction of bioinformation. From the moment of collection, where donors decide how and what data is to be shared, to the biobank, where technicians decide how to process samples and manage lab protocols, and to the more complex relationships of power-knowledge among medical doctors and researchers. Besides, the struggle to grant research funding and the professional culture trigger closure strategies, such as keeping sets of data apart, or limiting which information is to be shared and with whom. These processes also prompt a wide range of classification systems, that are not always convergent, amplifying the diversity in bioinformation construction.
Ludwig Weh (Fraunhofer IMW)
Paper short abstract:
Shaping social realities of people in digitized environments, AI technology relies on models of biological information processing. This paper explores biological factors omitted in technological abstraction and their potential changes to AI embodiment in a combined bioethics and AI ethics framing.
Paper long abstract:
Based on mathematical models of biological learning processes, computational algorithms are forming the basis of machine learning or artifical intelligence (AI). Following a largely dualistic and disembodied understanding of human mental processes, their technological abstraction is creating a wealth of application opportunities and promises immense transformative potential across social sectors.
AI ethics discuss effects and desirability of such transformations for living realities of affected people; however, a merely technology-centered discourse about desirable social effects of widespread AI implementation overlooks the technology’s origins in biological information processing from a life sciences and human sciences perspective as well as its complex, multi-layered effects on psychic, social and cultural systems as humanly embodied entities.
Especially with the rise of emerging neurotechnologies enabling novel interfaces between biological and technologically abstracted forms of intelligence, acknowledging these aspects in capable and integrated ethical concepts is gaining increasing importance. Drawing on central concepts in bioethics and AI ethics, an integrated embodiment approach can strengthen these reflexive elements in AI ethical and regulatory debates, as well as improve social discourse and agency relating to technology-driven transformations of living environments as application fields of AI technology.
Biological factors other than electrophysiological activity (e.g. chemical, hormonal, metabolic signals) are strongly influencing neural or bacterial information processing, yet they are omitted in AI technological abstraction. This paper explores technoscientific imaginaries potentially arising from their inclusion in AI development, and how social interaction with the differently embodied technology might change if more diverse sources of bioinformation were included in AI production.