HIPP 27: HUMAN PROGRESS

The HUMAN PROGRESS project aims to advance research in the natural sciences by drawing on methods, insights, and knowledge from across the humanities and social sciences. In doing so it also offers fresh frameworks of thinking for the humanities and social sciences, and works towards an interdisciplinarity that is essential in contemporary marine sciences to tackle complex environmental problems. Postdoctoral researchers funded under this project will work together as a team and in collaboration with experts from the arts, humanities, social and natural sciences. Our criterion of success is to make a demonstrable impact on research in the natural sciences by drawing on social data, humanities approaches and ways of thinking. Along the way all disciplines involved will have to adapt, extend and to some extent automatize their methodologies, to create impact in applications while maintaining a human perspective and mindset. 

The title HUMAN PROGRESS intended to provoke critical inquiry. It combines the progress-oriented thinking of the natural sciences and engineering with the word human to invite critical reflections on how progress can be achieved that takes humans into account, from the initial phrasing of problems to the impacts of eventual solutions. This includes engaging the meaning of progress, asking whom it serves, which vulnerability it generates, and how these might be challenged.

The cohort includes five positions:

#1 Words and Power in Marine Biodiversity

Ecologically and Biologically Significant marine Areas (EBSAs) are prospective Marine Protected Areas (MPAs) that could contribute to the 30-by-30 goal of the global biodiversity Kumming-Montreal Agreement for marine protection: safegarding 30% of the ocean’s area by the year 2030. However, among these prospective protected areas only 28 reference any biology or biological entities in their name. By comparison 97 EBSAs reference seafloor features. What is behind the naming of these areas and what significance does such naming hold? What narratives and imaginaries are produced, and what do they mean for potential ocean protection? These are the questions at the heart of this project that seeks to analyse the naming of EBSAs as they emerge as a critical aspect of future MPA planning. 

Such an effort requires insights from multiple fields to make sense of how such designations— names—for geographic zones of the ocean have emerged. This project will bring together Linguistics, Geography, Microbial Ecology and Complexity theory to learn from various approaches to render new understandings of naming and its implications for ocean protection. Names reveal certain perspectives and power relations at the time of naming, but also consolidate nascent fields, shape expectations, and set agendas. 

This project is to publish a careful linguistic analysis of the EBSA names that draws attention to the underlying reasoning that the names reveal. The greater goal of this project is to gain a deeper understanding of the lifecycle of scientific terms: how they emerge, proliferate, and decline, how they migrate into everyday language, influence public discourse, and ultimately shape science and society.

#2 Historical Observations of the Marine Environment

Environmental research (particularly in climate change) has profited from the analysis of big data sources, which focused on structured data, such as tables of curated observations, from ecological time series stations or expeditions. However, there is still a considerable knowledge gap regarding the response of biodiversity to climate change as data tends to be recent (e.g. spanning decades) or from the fossil record (spanning millions of years with gaps lasting hundred thousands of years). Therefore data covering the timescale of climate change is still sparse. Meanwhile a wealth of less-structured data spanning centuries has been left untapped. This data comes in the forms of historical sources , both in writing, as images, drawings, and objects, as well as collective memories and knowledge including indigenous knowledge. Hence a logical next challenge is to tap these records by enabling large-scale computer-aided analysis. This work can profit from recent advances in hand-writing, speech recognition, large language models and 3D analysis, but further steps in the knowledge creation pipeline consisting of computer-aided systematization and canonization of data is still missing. For data, a natural middle ground between structured and unstructured representation is offered by knowledge graphs, i.e. networks in which data entities, such as people, places or objects are represented by network nodes, while network links encode their relationships. Knowledge graphs haven’t yet received much attention in network science, due to their often complicated diversity of generating mechanisms. As complex structure emerges during knowledge graph aggregation, the development of new analysis methods is necessary, which can draw inspiration from both network science and established non-computational workflows and analytical methods in historical research. A key challenge for the interpretation of computer aided systematizations of historical records and data created by knowledge graphs will be the attribution of meaning which depends on a number of factors such as perspective, cultural differences, or social practices.

 A first goal of this project is to highlight the potential of knowledge graphs for the analysis of less-structured data in a perspectives paper which will focus on both the potential of knowledge graphs, and the challenges posed by a multiperspective and space-time-acteur related  historical analysis . This potential can be illustrated by applying established network metrics to existing knowledge graphs, and to test  these by creating and applying used cases from historical research on climate change. In the mid-term our goal is to create new knowledge graphs from textual and material sources such as the Prize Papers data set; to develop new network science tools for extracting information from these knowledge graphs, by learning from historical research; and finally,  to gain new insights into historical biodiversity, using these methods. 

#3 (Re-)examining Modelling

One of the pressing societal issues we face today is the loss of trust in science, which is particularly evident in the area of modelling. To address this loss of trust we must understand its origins. Presently mathematical models are mostly black boxes that are only understood by a few experts. Others are not in a position to meaningfully question these models and are thus left in a position where the only apparent options are to accept the models and their implications or to reject them. Modellers are aware that modelling necessarily involves simplifications that are not without alternatives, such that the choices made reflect the modellers ideas, experiences, values and the contexts in which they work and hence are subject  to being questioned. Indeed, a major way in which models generate knowledge is by enabling a critical questioning of assumptions. However, only a small group of modellers and nearly no layperson is acquainted with this power of advancing through questioning. Modelling must therefore aim to create a meaningful dialogue that enables a wider base of people to question models and modelling practices without needing to understand their mathematical basis. We believe that such a dialogue can be enabled by gaining a philosophical understanding of how models produce insights and by communicating these pathways directly and openly.  

A first goal of this project is to draw attention to the societal need for a philosophical reexamination of knowledge production in modelling. In the mid-term we will consider in case studies how models produce insights and then construct a conceptual toolkit allowing people to understand and discuss the process of knowledge production in modelling without understanding the mathematics, especially in the realm of biodiversity research.  

#4 Human Decisions in Environmental Systems

In mathematical models we typically model ecological systems as if humans did not exist. For example a large majority of published ecological food webs do not include humans. By contrast there is hardly any system left on the planet that is not severely impacted by humans. When we incorporate humans into models, e.g. in the context of socio-ecological system models, we typically treat the humans as an additional predator—the fisherman becomes indistinguishable from a shark. Modelling humans in this way ignores a wealth of knowledge on human behavior and decision making, including psychological, social, political, and economic dimensions. Taking these additional complexities into account and properly incorporating them in models has the potential to shift our perspective on the ecological dynamics. 

A first goal of this project is to review the different ways in which human decision making is modelled across disciplines and particularly contrast other disciplinary traditions with ecological modelling of humans. In the mid-term we seek to develop better approaches for incorporating human behavior into ecological models. We will focus on case studies such as water management or offshore wind parks and pay particular attention to decisions that are made in situations where both qualitative and quantitative information is available. 

#5 Science Narratives

Even in abstract mathematics the products of research are papers that present human-readable narratives. In the environmental sciences new narratives appear to be relatively rare, and seem to emerge mostly from agenda-setting papers in leading journals while most publications restate and reinforce existing narratives. The emergence of new narratives are thus major events that can shift the focus of research. However, while narratives are commonly studied in the context of novels, short stories and plays, there is almost no work on the narratology of science. We can ask for example, what is the structure of successful scientific narratives? What are the circumstances in which new narratives can be established? Are there research themes that are not pursued because they don’t make good stories? What is the relationship between the emergence of narratives and the emergence of new research fields? And, how do scientific narratives change when they are communicated to the general public? 

This project aims to understand the emergence and evolution of successful narratives in the environmental sciences. A first goal is to identify leading narratives and map both their evolution between papers and the narrative structures employed to convey them within a paper. In the mid-term we seek to gain a deeper understanding how prevailing narratives shape current research and how scientific narratives are presented both within science and to a wider audience.