Achieving a Data‐Driven Risk Assessment Methodology for Ethical AI

The AI landscape demands a broad set of legal, ethical, and societal considerations to be accounted for in order to develop ethical AI (eAI) solutions which sustain human values and rights. Currently, a variety of guidelines and a handful of niche tools exist to account for and tackle individual challenges. However, it is also well established that many organizations face practical challenges in navigating these considerations from a risk management perspective within AI governance. Therefore, new methodologies are needed to provide a well-vetted and real-world applicable structure and path through the checks and balances needed for ethically assessing and guiding the development of AI. In this paper, we show that a multidisciplinary research approach, spanning cross-sectional viewpoints, is the foundation of a pragmatic definition of ethical and societal risks faced by organizations using AI. Equally important are the findings of cross-structural governance for implementing eAI successfully. Based on evidence acquired from our multidisciplinary research investigation, we propose a novel data-driven risk assessment methodology, entitled DRESS-eAI. In addition, through the evaluation of our methodological implementation, we demonstrate its state-of-the-art relevance as a tool for sustaining human values in the data-driven AI era

Unraveling spatiotemporal variability of arbuscular mycorrhizal fungi in a temperate grassland plot

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldmann, K., Boeddinghaus, R. S., Klemmer, S., Regan, K. M., Heintz-Buschart, A., Fischer, M., Prati, D., Piepho, H., Berner, D., Marhan, S., Kandeler, E., Buscot, F., & Wubet, T. Unraveling spatiotemporal variability of arbuscular mycorrhizal fungi in a temperate grassland plot. Environmental Microbiology, 22(3),(2020): 873-888, doi:10.1111/1462-2920.14653.Soils provide a heterogeneous environment varying in space and time; consequently, the biodiversity of soil microorganisms also differs spatially and temporally. For soil microbes tightly associated with plant roots, such as arbuscular mycorrhizal fungi (AMF), the diversity of plant partners and seasonal variability in trophic exchanges between the symbionts introduce additional heterogeneity. To clarify the impact of such heterogeneity, we investigated spatiotemporal variation in AMF diversity on a plot scale (10 × 10 m) in a grassland managed at low intensity in southwest Germany. AMF diversity was determined using 18S rDNA pyrosequencing analysis of 360 soil samples taken at six time points within a year. We observed high AMF alpha‐ and beta‐diversity across the plot and at all investigated time points. Relationships were detected between spatiotemporal variation in AMF OTU richness and plant species richness, root biomass, minimal changes in soil texture and pH. The plot was characterized by high AMF turnover rates with a positive spatiotemporal relationship for AMF beta‐diversity. However, environmental variables explained only ≈20% of the variation in AMF communities. This indicates that the observed spatiotemporal richness and community variability of AMF was largely independent of the abiotic environment, but related to plant properties and the cooccurring microbiome.We thank the managers of the three Exploratories, Kirsten Reichel‐Jung, Swen Renner, Katrin Hartwich, Sonja Gockel, Kerstin Wiesner, and Martin Gorke for their work in maintaining the plot and project infrastructure; Christiane Fischer and Simone Pfeiffer for giving support through the central office, Michael Owonibi and Andreas Ostrowski for managing the central data base, and Eduard Linsenmair, Dominik Hessenmöller, Jens Nieschulze, Ernst‐Detlef Schulze, Wolfgang W. Weisser and the late Elisabeth Kalko for their role in setting up the Biodiversity Exploratories project. The work has been funded by the DFG Priority Program 1374 ‘Infrastructure‐Biodiversity‐Exploratories’ (BU 941/22‐1, BU 941/22‐3, KA 1590/8‐2, KA 1590/8‐3). Field work permits were issued by the responsible state environmental office of Baden‐Württemberg (according to § 72 BbgNatSchG). Likewise, we kindly thank Beatrix Schnabel, Melanie Günther and Sigrid Härtling for 454 sequencing in Halle. AHB gratefully acknowledges the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig funded by the German Research Foundation (FZT 118). Authors declare no conflict of interests

Sustainable AI : An inventory of the state of knowledge of ethical, social, and legal challenges related to artificial intelligence

This report is an inventory of the state of knowledge of ethical, social, and legal challenges related to artificial intelligence conducted within the Swedish Vinnova-funded project “Hållbar AI – AI Ethics and Sustainability”, led by Anna Felländer. Based on a review and mapping of reports and studies, a quantitative and bibliometric analysis, and in-depth analyses of the healt- care sector, the telecom sector, and digital platforms, the report proposes three recommendations. Sustainable AI requires: 1. a broad focus on AI governance and regulation issues, 2. promoting multi-disciplinary collaboration, and 3. building trust in AI applications and applied machine-learning, which is a matter of key importance and requires further study of the relationship between transparency and accountability

Sample Preservation and Storage Significantly Impact Taxonomic and Functional Profiles in Metaproteomics Studies of the Human Gut Microbiome

With the technological advances of the last decade, it is now feasible to analyze microbiome samples, such as human stool specimens, using multi-omic techniques. Given the inherent sample complexity, there exists a need for sample methods which preserve as much information as possible about the biological system at the time of sampling. Here, we analyzed human stool samples preserved and stored using different methods, applying metagenomics as well as metaproteomics. Our results demonstrate that sample preservation and storage have a significant effect on the taxonomic composition of identified proteins. The overall identification rates, as well as the proportion of proteins from Actinobacteria were much higher when samples were flash frozen. Preservation in RNAlater overall led to fewer protein identifications and a considerable increase in the share of Bacteroidetes, as well as Proteobacteria. Additionally, a decrease in the share of metabolism-related proteins and an increase of the relative amount of proteins involved in the processing of genetic information was observed for RNAlater-stored samples. This suggests that great care should be taken in choosing methods for the preservation and storage of microbiome samples, as well as in comparing the results of analyses using different sampling and storage methods. Flash freezing and subsequent storage at −80 °C should be chosen wherever possible

The multidimensionality of soil macroecology

The recent past has seen a tremendous surge in soil macroecological studies and new insights into the global drivers of one‐quarter of the biodiversity of the Earth. Building on these important developments, a recent paper in Global Ecology and Biogeography outlined promising methods and approaches to advance soil macroecology. Among other recommendations, White and colleagues introduced the concept of a spatial three‐dimensionality in soil macroecology by considering the different spheres of influence and scales, as soil organism size ranges vary from bacteria to macro‐ and megafauna. Here, we extend this concept by discussing three additional dimensions (biological, physical, and societal) that are crucial to steer soil macroecology from pattern description towards better mechanistic understanding. In our view, these are the requirements to establish it as a predictive science that can inform policy about relevant nature and management conservation actions. We highlight the need to explore temporal dynamics of soil biodiversity and functions across multiple temporal scales, integrating different facets of biodiversity (i.e., variability in body size, life‐history traits, species identities, and groups of taxa) and their relationships to multiple ecosystem functions, in addition to the feedback effects between humans and soil biodiversity. We also argue that future research needs to consider effective soil conservation policy and management in combination with higher awareness of the contributions of soil‐based nature's contributions to people. To verify causal relationships, soil macroecology should be paired with local and globally distributed experiments. The present paper expands the multidimensional perspective on soil macroecology to guide future research contents and funding. We recommend considering these multiple dimensions in projected global soil biodiversity monitoring initiatives

Organic agricultural practice enhances arbuscular mycorrhizal symbiosis in correspondence to soil warming and altered precipitation patterns

Climate and agricultural practice interact to influence both crop production and soil microbes in agroecosystems. Here, we carried out a unique experiment in Central Germany to simultaneously investigate the effects of climates (ambient climate vs. future climate expected in 50–70 years), agricultural practices (conventional vs. organic farming), and their interaction on arbuscular mycorrhizal fungi (AMF) inside wheat (Triticum aestivum L.) roots. AMF communities were characterized using Illumina sequencing of 18S rRNA gene amplicons. We showed that climatic conditions and agricultural practices significantly altered total AMF community composition. Conventional farming significantly affected the AMF community and caused a decline in AMF richness. Factors shaping AMF community composition and richness at family level differed greatly among Glomeraceae, Gigasporaceae and Diversisporaceae. An interactive impact of climate and agricultural practices was detected in the community composition of Diversisporaceae. Organic farming mitigated the negative effect of future climate and promoted total AMF and Gigasporaceae richness. AMF richness was significantly linked with nutrient content of wheat grains under both agricultural practices

Targeting the Active Rhizosphere Microbiome of Trifolium pratense in Grassland Evidences a Stronger-Than-Expected Belowground Biodiversity-Ecosystem Functioning Link

The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in soil and microbial ecology. To date, most belowground BEF studies focus on the diversity of microbes analyzed by barcoding on total DNA, which targets both active and inactive microbes. This approach creates a bias as it mixes the part of the microbiome currently steering processes that provide actual ecosystem functions with the part not directly involved. Using experimental extensive grasslands under current and future climate, we used the bromodeoxyuridine (BrdU) immunocapture technique combined with pair-end Illumina sequencing to characterize both total and active microbiomes (including both bacteria and fungi) in the rhizosphere of Trifolium pratense. Rhizosphere function was assessed by measuring the activity of three microbial extracellular enzymes (β-glucosidase, N-acetyl-glucosaminidase, and acid phosphatase), which play central roles in the C, N, and P acquisition. We showed that the richness of overall and specific functional groups of active microbes in rhizosphere soil significantly correlated with the measured enzyme activities, while total microbial richness did not. Active microbes of the rhizosphere represented 42.8 and 32.1% of the total bacterial and fungal taxa, respectively, and were taxonomically and functionally diverse. Nitrogen fixing bacteria were highly active in this system with 71% of the total operational taxonomic units (OTUs) assigned to this group detected as active. We found the total and active microbiomes to display different responses to variations in soil physicochemical factors in the grassland, but with some degree of resistance to a manipulation mimicking future climate. Our findings provide critical insights into the role of active microbes in defining soil ecosystem functions in a grassland ecosystem. We demonstrate that the relationship between biodiversity-ecosystem functioning in soil may be stronger than previously thought

Gut microbiome is not associated with mild cognitive impairment in Parkinson's disease

Gut microbiome differences between people with Parkinson's disease (PD) and control subjects without Parkinsonism are widely reported, but potential alterations related to PD with mild cognitive impairment (MCI) have yet to be comprehensively explored. We compared gut microbial features of PD with MCI (n = 58) to cognitively unimpaired PD (n = 60) and control subjects (n = 90) with normal cognition. Our results did not support a specific microbiome signature related to MCI in PD