Each month, The Existential Risk Research Assessment (TERRA) uses a unique machine-learning model to predict those publications most relevant to existential risk or global catastrophic risk. The following are a selection of those papers identified this month.
Please note that we provide these citations and abstracts as a service to aid other researchers in paper discovery and that inclusion does not represent any kind of endorsement of this research by the Centre for the Study of Existential Risk or our researchers.
Humankind faces a growing spectrum of anthropogenic existential threats to human civilization and survival. This article therefore aims to develop a new framework for security policy – ‘existential security’ – that puts the survival of humanity at its core. It begins with a discussion of the definition and spectrum of ‘anthropogenic existential threats’, or those threats that have their origins in human agency and could cause, minimally, civilizational collapse, or maximally, human extinction. It argues that anthropogenic existential threats should be conceptualized as a matter of ‘security’, which follows a logic of protection from threats to the survival of some referent object. However, the existing frameworks for security policy – ‘human security’ and ‘national security’ – have serious limitations for addressing anthropogenic existential threats; application of the ‘national security’ frame could even exacerbate existential threats to humanity. Thus, the existential security frame is developed as an alternative for security policy, which takes ‘humankind’ as its referent object against anthropogenic existential threats to human civilization and survival.
The decarbonisation of energy provision is key to managing global greenhouse gas emissions and hence mitigating climate change. Digital technologies such as big data, machine learning, and the Internet of Things are receiving more and more attention as they can aid the decarbonisation process while requiring limited investments. The orchestration of these novel technologies, so-called cyber-physical systems (CPS), provides further, synergetic effects that increase efficiency of energy provision and industrial production, thereby optimising economic feasibility and environmental impact. This comprehensive review article assesses the current as well as the potential impact of digital technologies within CPS on the decarbonisation of energy systems. Ad hoc calculation for selected applications of CPS and its subsystems estimates not only the economic impact but also the emission reduction potential. This assessment clearly shows that digitalisation of energy systems using CPS completely alters the marginal abatement cost curve (MACC) and creates novel pathways for the transition to a low-carbon energy system. Moreover, the assessment concludes that when CPS are combined with artificial intelligence (AI), decarbonisation could potentially progress at an unforeseeable pace while introducing unpredictable and potentially existential risks. Therefore, the impact of intelligent CPS on systemic resilience and energy security is discussed and policy recommendations are deducted. The assessment shows that the potential benefits clearly outweigh the latent risks as long as these are managed by policy makers.
Effective altruism is an ethical framework for identifying the greatest potential benefits from investments. Here, we apply effective altruism concepts to maximize research benefits through identification of priority stakeholders, pathosystems, and research questions and technologies. Priority stakeholders for research benefits may include smallholder farmers who have not yet attained the minimal standards set out by the United Nations Sustainable Development Goals; these farmers would often have the most to gain from better crop disease management, if their management problems are tractable. In wildlands, prioritization has been based on the risk of extirpating keystone species, protecting ecosystem services, and preserving wild resources of importance to vulnerable people. Pathosystems may be prioritized based on yield and quality loss, and also factors such as whether other researchers would be unlikely to replace the research efforts if efforts were withdrawn, such as in the case of orphan crops and orphan pathosystems. Research products that help build sustainable and resilient systems can be particularly beneficial. The "value of information" from research can be evaluated in epidemic networks and landscapes, to identify priority locations for both benefits to individuals and to constrain regional epidemics. As decision-making becomes more consolidated and more networked in digital agricultural systems, the range of ethical considerations expands. Low-likelihood but high-damage scenarios such as generalist doomsday pathogens may be research priorities because of the extreme potential cost. Regional microbiomes constitute a commons, and avoiding the "tragedy of the microbiome commons" may depend on shifting research products from "common pool goods" to "public goods" or other categories. We provide suggestions for how individual researchers and funders may make altruism-driven research more effective.
Given the recent interest in the interface between travelers’ diarrhea (TD) management guidelines and antimicrobial resistance from both the patient and population perspectives, we have undertaken a review of the evidence with an aim towards practical and pragmatic recommendations. Recent Findings: Antimicrobial resistance continues to be an existential threat. Therefore, an update is needed on the pathogens that cause TD, the role of antibiotics, the potential changes in microbiome and acquisiton of multi-drug resistant (MDR) bacteria, and lastly the impact of MDR acquisition of the traveler on individual, community, and global health through a holistic framework. Summary: Important research gaps and opportunities in this area are identified, as well as practical guidance for the travel medicine community offered.
One way of carving up the broad 'AI ethics and society' research space that has emerged in recent years is to distinguish between 'near-term' and 'long-term' research. While such ways of breaking down the research space can be useful, we put forward several concerns about the near/long-term distinction gaining too much prominence in how research questions and priorities are framed. We highlight some ambiguities and inconsistencies in how the distinction is used, and argue that while there are differing priorities within this broad research community, these differences are not well-captured by the near/long-term distinction. We unpack the near/long-term distinction into four different dimensions, and propose some ways that researchers can communicate more clearly about their work and priorities using these dimensions.We suggest that moving towards a more nuanced conversation about research priorities can help establish new opportunities for collaboration, aid the development of more consistent and coherent research agendas, and enable identification of previously neglected research areas.
Accumulating evidence using crowdsourcing and machine learning: a living bibliography about existential risk and global catastrophic risk
Peer-reviewed paper by Gorm Shackelford, Luke Kemp, Catherine Rhodes, Lalitha Sundaram, Seán Ó hÉigeartaigh, Simon Beard, Haydn Belfield, Julius Weitzdörfer, Shahar Avin, Dag Sørebø, Elliot M. Jones, John B. Hume, David Price, David Pyle, Daniel Hurt, Theodore Stone, Harry Watkins, Lydia Collas, William Sutherland