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Beckett Sterner

Assistant Professor
Faculty, TEMPE Campus, Mailcode 4501
Senior Global Futures Scientist
Faculty, TEMPE Campus, Mailcode 4501
Asst Professor
Faculty, TEMPE Campus, Mailcode 4501
Biography: 

The driving question for my research is: what knowledge do we need to work together while differing in fundamental ways? Urgent global challenges such as biodiversity loss or climate change depend on research and decision-making processes that are highly decentralized yet must be coordinated worldwide and moreover frequently operate under incompatible or changing assumptions. Computational methods and infrastructure have become essential mediators in this regard by helping data travel across different temporal and spatial scales while preserving their relevance to the needs of people working in local, national, and international settings. Nonetheless, it is difficult to determine which approaches to data-intensive science and its knowledge infrastructure are best suited to bridging our differences without collapsing into overwhelming chaos or fragmentation. My research studies how and why pluralism— i.e. advancing multiple approaches to an issue— makes a difference to current and historical practices of computational science. I apply these insights to develop novel, collaborative approaches to making data and models relevant to global societal challenges.

Biodiversity provides an exemplary setting for investigating how pluralism can enrich rather than obstruct the value of big data and computational methods for science. Biodiversity data is collected through globally decentralized efforts that reflect a dynamic mix of aims, sampling methods, taxonomic assumptions, and technologies. The core observations at issue describe the locations, traits, and interactions of biological species and provide the basis for projects such as modeling future risks of zoonotic diseases and species going extinct. The significance of these observations is inherently tied to the classifications we use to label them with species, ecosystems, and physical environments. These classifications are themselves in flux as the world changes, research leads to new insights, and stakeholders such as governmental agencies or conservation organizations bring new priorities to the table.  

While my research straddles multiple fields and topics, my approach is anchored in the branch of history and philosophy of science that studies scientists’ research practices in order to illuminate how science works and what it tells us about the world. I collaborate with biologists and social scientists to investigate how pressures to harness the data revolution are challenging the future scope for pluralism about nature and method. As a historian and philosopher in these projects, I identify and question assumptions that lead to systemic failures or blind spots because one community seeks to restrict or simplify the knowledge produced by others. Drawing on my interdisciplinary training in statistics and computational science, I then work with my collaborators to develop these insights into innovative, constructive approaches to scientific data and modeling.

Education: 

Ph.D. in history and philosophy of science, University of Chicago 2012

M.Sc. Statistics, University of Chicago 2011

M.A. Philosophy, University of Chicago 2009

B.S. Mathematics, Massachusetts Institute of Technology 2006

 

Research Interests: 

An important unifying theme across my work is uncovering and sustaining the practical value of pluralistic understandings of nature. My work on traditional topics in philosophy of science has developed this theme in several directions. On modeling practices, I’ve shown how even purely instrumental simulation techniques become objects of shared empirical knowledge as scientists negotiate conflict among differing aims of representational versus predictive accuracy (Sterner and DiTeresi 2021). I’ve pioneered a new approach to defining the concept of biological individuality based on a more general representation of the causal and material structure of life cycles, showing how the nature of units of evolution such as population lineages and evolutionary species can be characterized without requiring natural selection (Sterner 2017, 2019). I’ve also shown how biologists integrate multiple meanings of function to solve research problems not captured by the common pluralist view that each meaning of function operates independently in different fields (Cusimano and Sterner 2019).

Pluralism about biological classification is only practical if biodiversity data can be accurately and efficiently synthesized according to a user’s preferred species taxonomy. A species taxonomy represents a scientific theory through which any biological data about a group of organisms can be aggregated and interpreted, but comprehensive biodiversity datasets are typically produced with methods that mix observations labelled according to incompatible taxonomies. In the project Intelligently predicting viral spillover risks from bats and other wild mammals (National Institutes of Health, Co-PI), we aim to demonstrate the value of taxonomic intelligence — the ability to label data records according to the precise meaning of concepts in a classification — for documenting and modeling the distribution of viruses in mammal hosts worldwide. The project uses natural language processing methods to extract observations of viruses in mammal species from article pdfs and to generate metadata documenting information about the taxonomies used. We use this metadata to more precisely map observations to a single reference taxonomy and quantify the effects on models of zoonotic disease risk. I serve as the project lead for computational approaches to producing and using taxonomic intelligence in collaboration with project PI Nate Upham and Co-PI Atriya Sen.

To the extent that biodiversity data is openly available online and fit-for-use in a range of projects, it is due to the ongoing collection and curation efforts of scientists and enthusiasts. Collaborative data portals are a growing and novel class of scientific organization that straddles organizational, geopolitical, and disciplinary boundaries, but their long-term persistence is threatened by financial, social, and technological challenges. In the project Explaining Differential Success in Biodiversity Knowledge Commons (National Science Foundation, PI), we investigate how the production and maintenance of open biodiversity data is being transformed by software for online collaborative data digitization and management. My Co-PIs are Zoe Nyssa, an anthropologist of science, and Steve Elliott, an expert in organizational aspects of scientific research. We focus on the ASU-led Symbiota platform, which is used internationally by over 3k active registered users contributing to 40 community-led data portals that manage 70+ million data records. The project will collect holistic qualitative and quantitative data describing the social and technical characteristics of these portals since the first one launched a decade ago. We then aim to uncover factors explaining how some portals have effectively coordinated efforts among their distributed networks of participants in order to achieve sustained activity or growth.

When faced with complex evolutionary phenomena, scientists often adopt divergent assumptions about the aims and adequacy of their modeling practices, challenging the objectivity of their results. In (Sterner and Lidgard 2021), we showed how leading statistical model selection methods can produce incompatible results even when applied to the same data with the same models: when scientists disagree about whether the candidate models include the true process, they quantify statistical evidence in divergent ways. I take up this challenge with mathematical biologist and Co-PI John Fricks in the project Dynamic Linear Modeling to Unlock New Tests of Directionality in Fossil Lineages (Templeton Foundation, PI). Our solution is to deepen the pluralism of modeling approaches in order to better diagnose and triangulate the effects of divergent background assumptions on empirical conclusions. We introduce a more general mathematical framework, dynamic linear modeling, than is currently used for fossil lineages, and we use this framework to develop more comprehensive methods for model estimation and diagnostics. This approach is necessary to unlocking richer but still reliable multivariate tests of how species evolved in response to historical environmental changes, e.g. in global temperature.

Research Group: 

I'm Associate Director of the Biodiversity Knowledge Integration Center at ASU, Program Lead for big data in biodiversity at the Center for Biodiversity Outcomes, and a faculty member of the Center for Biology and Society.

Publications: 

2021

*Sterner, B, and S Lidgard. “Objectivity and Underdetermination in Statistical Model Selection.” British Journal for the Philosophy of Science.

*Upham, N, JH Poelen, DL Paul, Q Groom, NB Simmons, MPM Vanhove, S Bertolino, DM Reeder, C Bastos-Silveira, A Sen, B Sterner, N Franz, M Guidoti, L Penev, and D Agosti. 2021. “Liberating Host-Virus Knowledge from COVID-19 Lockdown.” The Lancet: Planetary Health.

*Sen, A, B Sterner, N Franz, C Powell, N Upham. “Combining Machine Learning and Reasoning for Biodiversity Data Intelligence.” Proceedings of the Association for the Advancement of Artificial Intelligence Conference 2021.

*Sterner, B, S Elliott, N Franz, and N Upham. “Bats, Objectivity, and Viral Spillover Risk.” History and Philosophy of Life Sciences.

*Sterner, B, and C DiTeresi. 2021. “Making Coherent Senses of Success: Falsification and Representation in Scientific Modeling.” European Journal of Philosophy of Science.

Sterner, B, E Boyle, *P Jevtic. “Emerging Risks in the Health Sector from Changing Species Distributions and Seasonality.” Environmental Risk Series, Society of Actuaries. https://www.soa.org/globalassets/assets/files/resources/research-report/2021/emerging-risks-health-sector.pdf

Boyle, E, B Sterner, A Kinzig, *P Jevtic. “New Fire Hazard Risk from Policy Responses to Climate Change.” Environmental Risk Series, Society of Actuaries. https://www.soa.org/globalassets/assets/files/resources/research-report/2021/fire-hazard-risk.pdf

*Sterner, B, N Upham, P Gupta, C Powell, and N Franz. 2021. “Wanted: Standards for FAIR Taxonomic Concept Representations and Relationships.” Biodiversity Information Science and Standards 5: e75587.

2020

*Sterner, B, E Gilbert, and N Franz. 2020. “Decentralized but Globally Coordinated Biodiversity Data.” Frontiers in Big Data.

*Sterner, B, J Witteveen, and N Franz. 2020. “Coordinating dissent as an alternative to consensus classification: insights from systematics for bio-ontologies.” History and philosophy of the life sciences 42 (8).

Cullan, M, S Lidgard, and *B Sterner. “Controlling the Error Probabilities of Model Selection Information Criteria Using Bootstrapping.” Journal of Applied Statistics.

*Gilbert, E, N Franz, B Sterner. “Historical Overview of the Development of the Symbiota Specimen Management Software and Review of the Interoperability Challenges and Opportunities Informing Future Development.” Biodiversity Information Science and Standards. 4: e59077.

*Sen, A, N Franz, B Sterner, N Upham. “The Automated Taxonomic Concept Reasoner.” Biodiversity Information Science and Standards. 4: e59074.

*Sterner, B, N Upham, A Sen, N Franz. “Avenues into Integration: Communicating taxonomic intelligence from sender to recipient.” Biodiversity Information Science and Standards. 4: e59006.

2019

Cusimano, S and *B Sterner. “Integrative Pluralism for Biological Function.” Biology and Philosophy.

Cusimano, S and *B Sterner. “The Objectivity of Organizational Functions.” Acta Biotheoretica. DOI: 10.1007/s10441-019-09365-9

*Sterner, B. “Evolutionary Species in Light of Population Genomics.” Philosophy of Science. 86: 1-12.

*Franz, N, E Gilbert, and B Sterner. “Distributed, but Global in Reach: Outline of a de-centralized paradigm for biodiversity data intelligence.” Biodiversity Information Science and Standards. 3: e37749.

2018

*Sterner, B, and S Lidgard. “Moving Past the Systematics Wars.” Journal of the History of Biology. 51: 31–67.

*Franz, N, and B Sterner. “To Increase Trust, Change the Social Design of Biodiversity Data Aggregation.” Database. doi: 10.1093/database/bax100

*Sterner, B. (5000 words) “Review of Data-Centric Biology: A Philosophical Study.” Philosophy of Science. 85 (3): 540–550.

2017

*Sterner, B. “Individuating Population Lineages: A New Genealogical Criterion.” Biology and Philosophy. 32 (5): 683–703.

*Sterner, B and N Franz. “Taxonomy for Humans or Computers?” Biological Theory. 12 (2): 99–111.

*Sterner, B. “Individuality and the Control of Life Cycles.” In Biological Individuality, eds. Scott Lidgard and Lynn Nyhart. Chicago: University of Chicago Press, 84­–108.

2015

*Sterner, B. “Pathways to Pluralism about Biological Individuality.” Biology and Philosophy. 30 (5): 609–628.

2014

*Sterner, B. “The Practical Value of Biological Information for Research.” Philosophy of Science 81 (2): 175–94.

*Sterner, B, and S. Lidgard. “The Normative Structure of Mathematization in Systematic Biology.” Studies in the History and Philosophy of Biological and Biomedical Sciences 46: 44–54.

2013

*Sterner, B. “Well-Structured Biology: Numerical Taxonomy and Its Methodological Vision for Systematics.” In The Evolution of Phylogenetic Systematics, edited by Andrew Hamilton, 213–44. Los Angeles: University of California Press.

2009

*Sterner, B. “Object Spaces: An Organizing Strategy for Biological Theorizing.” Biological Theory 4(3): 280–286.

2008

Li, S, F Zhao, B Sterner, and *J Xu. “Discriminative Learning for Protein Conformation Sampling.” Proteins: Structure, Function, and Bioinformatics 73(1): 228–240.

2007

Sterner, B, R Singh, and *B Berger. “Predicting and Annotating Catalytic Residues: An Information-Theoretic Approach.” Journal of Computational Biology.  14(8): 1058–1073.

Summer 2022
Course NumberCourse Title
BIO 495Undergraduate Research
Fall 2021
Course NumberCourse Title
BIO 345Evolution
HSD 598Special Topics
HPS 598Special Topics
EVO 598Special Topics
BIO 598Special Topics
Fall 2020
Course NumberCourse Title
BIO 345Evolution
BIO 493Honors Thesis
HPS 598Special Topics
BIO 598Special Topics
EVO 598Special Topics
Spring 2020
Course NumberCourse Title
BIO 394Special Topics
PHI 394Special Topics
HPS 394Special Topics
BIO 492Honors Directed Study
BIO 493Honors Thesis
BIO 495Undergraduate Research
PHI 598Special Topics
BIO 598Special Topics
HPS 598Special Topics
BIO 615Biology and Society Lab
HPS 615Biology and Society Lab
Fall 2019
Course NumberCourse Title
BIO 345Evolution
BIO 492Honors Directed Study
HPS 598Special Topics
BIO 598Special Topics
EVO 598Special Topics
Spring 2019
Course NumberCourse Title
PHI 394Special Topics
BIO 394Special Topics
HPS 394Special Topics
BIO 495Undergraduate Research
PHI 598Special Topics
HPS 598Special Topics
BIO 598Special Topics
BIO 615Biology and Society Lab
HPS 615Biology and Society Lab
Fall 2018
Course NumberCourse Title
BIO 345Evolution
HPS 615Biology and Society Lab
BIO 615Biology and Society Lab
Spring 2018
Course NumberCourse Title
HPS 314Philosophy of Science
PHI 314Philosophy of Science
HPS 512Philosophy of Science
BIO 615Biology and Society Lab
HPS 615Biology and Society Lab
Fall 2017
Course NumberCourse Title
HPS 615Biology and Society Lab
BIO 615Biology and Society Lab