Artificial intelligence for agricultural supply chain risk management: Constraints and potentials

Supply chains of staple crops, in developed and developing regions, are vulnerable to an array of disturbances and disruptions. These include biotic, abiotic and institutional risk factors. Artificial intelligence (AI) systems have the potential to mitigate some of these vulnerabilities across supply chains, and thereby improve the state of global food security. However, the particular properties of each supply chain phase, from "the farm to the fork," might suggest that some phases are more vulnerable to risks than others. Furthermore, the social circumstances and technological environment of each phase may indicate that several phases of the supply chains will be more receptive to AI adoption and deployment than others. This research paper seeks to test these assumptions to inform the integration of AI in agricultural supply chains. It employs a supply chain risk management approach (SCRM) and draws on a mix-methods research design. In the qualitative component of the research, interviews are conducted with agricultural supply chain and food security experts from the Food and Agricultural Organization of the UN (FAO), the World Bank, CGIAR, the World Food Program (WFP) and the University of Cambridge. In the quantitative component of the paper, seventy-two scientists and researchers in the domains of digital agriculture, big data in agriculture and agricultural supply chains are surveyed. The survey is used to generate assessments of the vulnerability of different phases of supply chains to biotic, abiotic and institutional risks, and the ease of AI adoption and deployment in these phases. The findings show that respondents expect the vulnerability to risks of all but one supply chain phases to increase over the next ten years. Importantly, where the integration of AI systems will be most desirable, in highly vulnerable supply chain phases in developing countries, the potential for AI integration is likely to be limited. To the best of our knowledge, the methodical examination of AI through the prism of agricultural SCRM, drawing on expert insights, has never been conducted. This paper carries out a first assessment of this kind and provides preliminary prioritizations to benefit agricultural SCRM as well as to guide further research on AI for global food security

A capital theory approach should guide national sustainability policies

The question of how to sustain human development in the current ecological and institutional landscape is arguably one of the utmost scientific and administratively challenging contemporary dilemmas. In response to this issue, the concept of Sustainable Development was proposed by the United Nations to inform policies for societal and human development. However, for national governments, the prevalent sustainability schemes summon more confusion than coherence. This is due to the frequent and inconsistent ways the concept of sustainability is put into practice, and consequently, difficulties in measuring and managing sustainability. The ability to evaluate how sustainable public projects are, will remain deficient if sustainability remains a notion open for interpretation. This perspective article maintains that the capital theory approach to sustainability stands out as the most rigorous framework on the topic. The capital theory is a state-centric system of ideas where national governments oversee a portfolio of capital stocks of four families: natural capital, economic capital, human capital, and social capital. It is the duty of the government to act on the capital flow between different stocks to allow sustainable long-term development. This perspective paper underscores several envisaged gains from the application of the capital theory approach in public policy. Considering these expected gains, policy makers should be encouraged to experiment with the approach

Lost in Transitions: Analyzing Sectoral Transitions in Postcolonial Developing Island States, Investigating Theoretical and Practical Gaps in Sustainability Transitions Theory

The theory of Sustainability Transitions, a current concept that has a relevance for both policy and academic thinking, attempts to explain fundamental structural changes in individual economic sectors and in societies at large. Yet, its application outside developed industrialized societies, where the theory originated, has been limited. More research is required on the applicability of transition approaches in developing states. This study attends to this constraint by examining the explanatory power of the main theoretical tenets of sustainability transitions in the contexts of the agricultural and extractive sectors of the postcolonial developing island states of Nauru, Jamaica and Sri Lanka, which extends the geographical and historical terrain of the theory. An empirical survey of 180 individuals, participant observations, archival research, a review of 536 books and articles, in 9 fieldwork missions and some 50 research sites, provides a canvas broad enough to test Sustainability Transitions epistemology and hypotheses with local communities of knowledge: its theoretical scope – levels and units of analysis, its transition causation mechanisms, its validity outside its origin-context in developed countries, and, by extension, to establish whether or not its universal assumptions are justified. Drawing on a comprehensive multi-sectoral analysis, this study illustrates that when deployed in the context of developing countries, specifically in postcolonial island states, the multi-level perspective is deficient. While the analytical framework is useful to some extent, it falls short to provide an inclusive explanation of what drives sectoral changes in developing island states and its epistemology is not fully-representative of sectoral and societal transitions in unindustrialized island societies. The theory does not adequately consider the role of government, or agency; it fails to define the notion of sustainability in applicable, operational terms; it overemphasizes the role of niches and radical innovation networks in sectoral change processes while underemphasizing the rigidity of dominant socio-technical regimes; it offers neither a normative model nor a valid descriptive model of sectoral transformations, and therefore, subscribes no instrument for policy analysis and policy design. Further research is essential to examine whether or not these theoretical limitations are observable in other developing states, and in such event, further refinements of sustainability transitions analytical tools should be warranted

Artificial intelligence for agricultural supply chain risk management: Preliminary prioritizations and constraints for the deployment of AI in food chains assessed by CGIAR scientists

This paper seeks to propose priorities and support the integration of artificial intelligence (AI) in agricultural supply chains for the next ten years (2020-2030), with the aim of reducing supply chain vulnerabilities and contribute to global food security. Qualitative interviews with food chains and food security specialists from the FAO, the World Bank, CGIAR, WFP and the University of Cambridge, and an exploratory quantitative survey of 72 CGIAR scientists and researchers are used to derive integrated assessments of the vulnerability of different phases of supply chains and the ease of AI adoption and deployment in these phases. The integrated assessments are structured across food chains in developed and developing regions. The research shows that respondents expect the vulnerability to risks of all but one supply chain phases to increase over the next ten years. Importantly, where the integration of AI will be most desirable, in highly vulnerable supply chain phases in developing countries, the potential for AI integration is estimate to be limited

Global catastrophic risk from lower magnitude volcanic eruptions.

Globalisation supports the clustering of critical infrastructure systems, sometimes in proximity to lower-magnitude (VEI 3–6) volcanic centres. In this emerging risk landscape, moderate volcanic eruptions might have cascading, catastrophic effects. Risk assessments ought to be considered in this light.Templeton World Foundatio

Photosynthetically Controlled Spirulina, but Not Solar Spirulina, Inhibits TNF-α Secretion: Potential Implications for COVID-19-Related Cytokine Storm Therapy.

An array of infections, including the novel coronavirus (SARS-CoV-2), trigger macrophage activation syndrome (MAS) and subsequently hypercytokinemia, commonly referred to as a cytokine storm (CS). It is postulated that CS is mainly responsible for critical COVID-19 cases, including acute respiratory distress syndrome (ARDS). Recognizing the therapeutic potential of Spirulina blue-green algae (Arthrospira platensis), in this in vitro stimulation study, LPS-activated macrophages and monocytes were treated with aqueous extracts of Spirulina, cultivated in either natural or controlled light conditions. We report that an extract of photosynthetically controlled Spirulina (LED Spirulina), at a concentration of 0.1 µg/mL, decreases macrophage and monocyte-induced TNF-α secretion levels by over 70% and 40%, respectively. We propose prompt in vivo studies in animal models and human subjects to determine the putative effectiveness of a natural, algae-based treatment for viral CS and ARDS, and explore the potential of a novel anti-TNF-α therapy

Photosynthetically Controlled Spirulina, but Not Solar Spirulina, Inhibits TNF-α Secretion: Potential Implications for COVID-19-Related Cytokine Storm Therapy.

An array of infections, including the novel coronavirus (SARS-CoV-2), trigger macrophage activation syndrome (MAS) and subsequently hypercytokinemia, commonly referred to as a cytokine storm (CS). It is postulated that CS is mainly responsible for critical COVID-19 cases, including acute respiratory distress syndrome (ARDS). Recognizing the therapeutic potential of Spirulina blue-green algae (Arthrospira platensis), in this in vitro stimulation study, LPS-activated macrophages and monocytes were treated with aqueous extracts of Spirulina, cultivated in either natural or controlled light conditions. We report that an extract of photosynthetically controlled Spirulina (LED Spirulina), at a concentration of 0.1 µg/mL, decreases macrophage and monocyte-induced TNF-α secretion levels by over 70% and 40%, respectively. We propose prompt in vivo studies in animal models and human subjects to determine the putative effectiveness of a natural, algae-based treatment for viral CS and ARDS, and explore the potential of a novel anti-TNF-α therapy

Tacit networks, crucial care: Informal networks and disaster response in Nepal’s 2015 Gorkha earthquake

It is often reiterated that a better understanding of local networks and needs is key to risk reduction. Nevertheless, the crucial role of informal social networks and actors in the catering for human needs in disaster circumstances remains largely under-explored. If we have to rethink the ‘work’ that informality does for our understanding of urban areas, its contribution to resilience, and take it seriously in the ‘full spectrum of risk’ in urban and peri-urban centres, better and more balanced methods are needed. This paper attends to this gap. Examining the mechanisms of aid provision in the aftermath of the 2015 Gorkha Earthquake in Nepal, it details an experimental set of quantitative research methods to explore the role of informal social networks in the provision of critical human needs in natural disasters. Relying on a sample of 160 households across four districts and 16 villages in the built environment affected by the Gorkha earthquake, the paper reveals that, overall, a wide disparity exists in the comparative importance of organisations in the provision of aid and resources. Much crucial after-disaster care is catered for by a mix of relatives, temples, friends, neighbours and local clubs. It highlights the importance of informal networks in understanding, and theorising, governance (of disaster and of the ‘urban’ more in general), and calls for greater attention to its role. It is time, it argues, to revalue informal disaster governance networks as a crucial, not tacit, component of disaster response

AI reflections in 2020

We invited authors of selected Comments and Perspectives published in Nature Machine Intelligence in the latter half of 2019 and first half of 2020 to describe how their topic has developed, what their thoughts are about the challenges of 2020, and what they look forward to in 2021.Postprint (author's final draft

Scoping potential routes to UK civil unrest via the food system: Results of a structured expert elicitation

We report the results of a structured expert elicitation to identify the most likely typesof potential food system disruption scenarios for the UK, focusing on routes to civil unrest. Wetake a backcasting approach by defining as an end-point a societal event in which 1 in 2000 peoplehave been injured in the UK, which 40% of experts rated as “Possible (20–50%)”, “More likely thannot (50–80%)” or “Very likely (>80%)” over the coming decade. Over a timeframe of 50 years, thisincreased to 80% of experts. The experts considered two food system scenarios and ranked theirplausibility of contributing to the given societal scenario. For a timescale of 10 years, the majorityidentified a food distribution problem as the most likely. Over a timescale of 50 years, the expertswere more evenly split between the two scenarios, but over half thought the most likely route tocivil unrest would be a lack of total food in the UK. However, the experts stressed that the variouscauses of food system disruption are interconnected and can create cascading risks, highlighting theimportance of a systems approach. We encourage food system stakeholders to use these results intheir risk planning and recommend future work to support prevention, preparedness, response andrecovery planning