How to Blend Journalistic Expertise with Artificial Intelligence for Research and Verifying News Stories

The use of AI technology can help to automate news verification workflows, while significantly innovating journalism practices. However, most existing systems are designed in isolation without interactive collaboration with journalists. ‘DMINR’ project aims to bring humans-at-the-center of AI loop for developing a powerful tool that is sympathetic to the way journalists work. In this paper, we attempt to understand how AI can shape journalists’ practices and, crucially, be shaped by them; we aim to design human-centred AI tool that works in synergy with journalists’ practices and strike a useful balance between human and machine intelligence. In this paper, we conducted a Co-design workshop to inform the design of the ‘DMINR’ system. Based on the findings, we outline the main challenges for designing AI systems in the context of journalism, that can serve as a resource for Human-AI interaction design

Analysis of Snow Cover in the Sibillini Mountains in Central Italy

Research on solid precipitation and snow cover, especially in mountainous areas, suffers from problems related to the lack of on-site observations and the low reliability of measurements, which is often due to instruments that are not suitable for the environmental conditions. In this context, the study area is the Monti Sibillini National Park, and it is no exception, as it is a mountainous area located in central Italy, where the measurements are scarce and fragmented. The purpose of this research is to provide a characterization of the snow cover with regard to maximum annual snow depth, average snow depth during the snowy period, and days with snow cover on the ground in the Monti Sibillini National Park area, by means of ground weather stations, and also analyzing any trends over the last 30 years. For this research, in order to obtain reliable snow cover data, only data from weather stations equipped with a sonar system and manual weather stations, where the surveyor goes to the site each morning and checks the thickness of the snowpack and records, it were collected. The data were collected from 1 November to 30 April each year for 30 years, from 1991 to 2020; six weather stations were taken into account, while four more were added as of 1 January 2010. The longer period was used to assess possible ongoing trends, which proved to be very heterogeneous in the results, predominantly negative in the case of days with snow cover on the ground, while trends were predominantly positive for maximum annual snow depth and distributed between positive and negative for the average annual snow depth. The shorter period, 2010–2022, on the other hand, ensured the presence of a larger number of weather stations and was used to assess the correlation and presence of clusters between the various weather stations and, consequently, in the study area. Furthermore, in this way, an up-to-date nivometric classification of the study area was obtained (in terms of days with snow on the ground, maximum height of snowpack, and average height of snowpack), filling a gap where there had been no nivometric study in the aforementioned area. The interpolations were processed using geostatistical techniques such as co-kriging with altitude as an independent variable, allowing fairly precise spatialization, analyzing the results of cross-validation. This analysis could be a useful tool for hydrological modeling of the area, as well as having a clear use related to tourism and vegetation, which is extremely influenced by the nivometric variables in its phenology. In addition, this analysis could also be considered a starting point for the calibration of more recent satellite products dedicated to snow cover detection, in order to further improve the compiled climate characterizatio

Journalists as Design Partners for AI

We report on a project exploring the development of an AI-enabled system for researching and verifying news articles. In particular, we underscore the value of journalists in the role of designers in a wider multi-disciplinary team including AI experts and interaction designers. We unpack our learnings by presenting three sensitizing concepts for Human-Centred AI technologies in the context of journalism. We contribute these concepts to provoke discussion and inspiration for design work

AI should embody our values: Investigating journalistic values to inform AI technology design

In the current climate of shrinking newsrooms and revenues, journalists face increasing pressures exerted by the industry’s for-profit focus and the expectation of intensified output. While AI-enabled journalism has great potential to help alleviate journalists’ pressures, it might also disrupt journalistic norms and, at worst, interfere with their duty to inform the public. For AI systems to be as useful as possible, designers should understand journalists’ professional values and incorporate them into their designs. We report findings from interviews with journalists to understand their perceptions of how professional values that are important to them (such as truth, impartiality and originality) might be supported and/or undermined by AI technologies. Based on these findings, we provide design insight and guidelines for incorporating values into the design of AI systems. We argue HCI design can achieve the strongest possible value alignment by moving beyond merely supporting important values, to truly embodying them

Making newsworthy news: The integral role of creativity and verification in the Human Information Behaviour that drives news story creation

Creativity and verification are intrinsic to high quality journalism, but their role is often poorly visible in news story creation. Journalists face relentless commercial pressures that threaten to compromise story quality, in a digital era where their ethical obligation not to mislead the public has never been more important. It is therefore crucial to investigate how journalists can be supported to produce stories that are original, impactful, and factually accurate, under tight deadlines. We present findings from 14 semi-structured interviews, where we asked journalists to discuss the creation of a recent news story to understand the process and associated Human Information Behaviour (HIB). Six overarching behaviours were identified: discovering, collecting, organising, interrogating, contextualising, and publishing. Creativity and verification were embedded throughout news story creation and integral to journalists’ HIB, highlighting their ubiquity. They often manifested at a micro level; in small-scale but vital activities that drove and facilitated story creation. Their ubiquitous role highlights the importance of creativity and verification support being woven into functionality that facilitates information acquisition and use in digital information tools for journalists

A Question of Design: Strategies for Embedding AI-Driven Tools into Journalistic Work Routines

With the promise of AI, the use of emerging technologies in journalism has gained momentum. However, the question of how such technologies can be interwoven with newsroom practices, values, routines, and socio-cultural experiences is often neglected. This article investigates the ways in which AI-driven tools are permeating newswork and design strategies for blending technological capabilities with editorial requirements. We followed a multi-method approach to investigate the deployment of AI in news production at two London newsrooms: (1) a design ethnography at the BBC with journalists and technologists, and (2) interviews with journalists at The Times. Our findings show that while journalists are generally open to try AI-driven technologies that benefit their work, technologists struggle to integrate them into journalistic workflows. The consensus was that human judgement is required to make complex decisions in journalism and that journalistic values should be prioritised in AI tool design. We claim that AI tools need to fit with professional practices and values in journalism in order to be fully accepted as an editorial tool. Embedding new technologies into journalistic workflows requires therefore a close collaboration between journalists and technologists, and a sociotechnical design that blends in work routines and values

Seascape connectivity of European anchovy in the Central Mediterranean Sea revealed by weighted Lagrangian backtracking and bio-energetic modelling

Ecological connectivity is one of the most important processes that shape marine populations and ecosystems, determining their distribution, persistence, and productivity. Here we use the synergy of Lagrangian back-trajectories, otolith-derived ages of larvae, and satellite-based chlorophyll-a to identify spawning areas of European anchovy from ichthyoplanktonic data, collected in the Strait of Sicily (Central Mediterranean Sea), i.e., the crucial channel in between the European and African continents. We obtain new evidence of ecosystem connectivity between North Africa and recruitment regions off the southern European coasts. We assess this result by using bio-energetic modeling, which predicts species-specific responses to environmental changes by producing quantitative information on functional traits. Our work gives support to a collaborative and harmonized use of Geographical Sub-Areas, currently identified by the General Fisheries Commission for the Mediterranean. It also confirms the need to incorporate climate and environmental variability effects into future marine resources management plans, strategies, and directives

I'm the same, I'm the same, I'm trying to change: Investigating the role of human information behavior in view change

Information is powerful; it can influence peoples' views and, in turn, their behavior. Much recent research and discussion on the role information plays in view change has focused on filter bubbles, echo chambers and misinformation and how they might influence what people think and how they act. However, no prior work has focused specifically on understanding the human information behavior (HIB) that drives and facilitates view change. We report findings from interviews with 18 people who recently changed views on issues they considered important. We found a tight symbiotic relationship between HIB and view change; passive information encountering sparked change, often spurring follow‐up active seeking and verification which progressed the change to a “point of no return,” supported making the change and reinforced the decision to change. When shared, information that contributed to the change sometimes sparked changes in others (as did expressing or debating the change), serving as an information encounter that perpetuated a cycle of HIB and view change. This understanding of the integral role of HIB in view change can inform policy and systems design to promote view change autonomy and a broader research agenda of understanding HIB to support democratic principles and values

Genome-Wide Association Mapping for Yield and Related Traits Under Drought Stressed and Non-stressed Environments in Wheat

Understanding the genetics of drought tolerance in hard red spring wheat (HRSW) in northern USA is a prerequisite for developing drought-tolerant cultivars for this region. An association mapping (AM) study for drought tolerance in spring wheat in northern USA was undertaken using 361 wheat genotypes and Infinium 90K single-nucleotide polymorphism (SNP) assay. The genotypes were evaluated in nine different locations of North Dakota (ND) for plant height (PH), days to heading (DH), yield (YLD), test weight (TW), and thousand kernel weight (TKW) under rain-fed conditions. Rainfall data and soil type of the locations were used to assess drought conditions. A mixed linear model (MLM), which accounts for population structure and kinship (PC+K), was used for marker–trait association. A total of 69 consistent QTL involved with drought tolerance-related traits were identified, with p ≤ 0.001. Chromosomes 1A, 3A, 3B, 4B, 4D, 5B, 6A, and 6B were identified to harbor major QTL for drought tolerance. Six potential novel QTL were identified on chromosomes 3D, 4A, 5B, 7A, and 7B. The novel QTL were identified for DH, PH, and TKW. The findings of this study can be used in marker-assisted selection (MAS) for drought-tolerance breeding in spring wheat

New genomic resources for switchgrass: a BAC library and comparative analysis of homoeologous genomic regions harboring bioenergy traits

<p>Abstract</p> <p>Background</p> <p>Switchgrass, a C4 species and a warm-season grass native to the prairies of North America, has been targeted for development into an herbaceous biomass fuel crop. Genetic improvement of switchgrass feedstock traits through marker-assisted breeding and biotechnology approaches calls for genomic tools development. Establishment of integrated physical and genetic maps for switchgrass will accelerate mapping of value added traits useful to breeding programs and to isolate important target genes using map based cloning. The reported polyploidy series in switchgrass ranges from diploid (2X = 18) to duodecaploid (12X = 108). Like in other large, repeat-rich plant genomes, this genomic complexity will hinder whole genome sequencing efforts. An extensive physical map providing enough information to resolve the homoeologous genomes would provide the necessary framework for accurate assembly of the switchgrass genome.</p> <p>Results</p> <p>A switchgrass BAC library constructed by partial digestion of nuclear DNA with <it>Eco</it>RI contains 147,456 clones covering the effective genome approximately 10 times based on a genome size of 3.2 Gigabases (~1.6 Gb effective). Restriction digestion and PFGE analysis of 234 randomly chosen BACs indicated that 95% of the clones contained inserts, ranging from 60 to 180 kb with an average of 120 kb. Comparative sequence analysis of two homoeologous genomic regions harboring orthologs of the rice <it>OsBRI1 </it>locus, a low-copy gene encoding a putative protein kinase and associated with biomass, revealed that orthologous clones from homoeologous chromosomes can be unambiguously distinguished from each other and correctly assembled to respective fingerprint contigs. Thus, the data obtained not only provide genomic resources for further analysis of switchgrass genome, but also improve efforts for an accurate genome sequencing strategy.</p> <p>Conclusions</p> <p>The construction of the first switchgrass BAC library and comparative analysis of homoeologous harboring <it>OsBRI1 </it>orthologs present a glimpse into the switchgrass genome structure and complexity. Data obtained demonstrate the feasibility of using HICF fingerprinting to resolve the homoeologous chromosomes of the two distinct genomes in switchgrass, providing a robust and accurate BAC-based physical platform for this species. The genomic resources and sequence data generated will lay the foundation for deciphering the switchgrass genome and lead the way for an accurate genome sequencing strategy.</p