Peer-reviewed paper by Gorm Shackelford, Luke Kemp, Catherine Rhodes, Lalitha Sundaram, Seán Ó hÉigeartaigh, SJ 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
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. All previous updates can be found here. 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.
I argue that moral philosophers have either misunderstood the problem of moral demandingness or at least failed to recognize important dimensions of the problem that undermine many standard assumptions. It has been assumed that utilitarianism concretely directs us to maximize welfare within a generation by transferring resources to people currently living in extreme poverty. In fact, utilitarianism seems to imply that obligations to help people who are currently badly off are trumped by obligations to undertake actions targeted at improving the value of the long-term future. Reflecting on the demands of beneficence in respect of the value of the far future forces us to view key aspects of the problem of moral demandingness in a different light.
Catastrophic risk raises questions that are not only of practical importance, but also of great philosophical interest, such as how to define 'catastrophe' and what distinguishes catastrophic outcomes from non-catastrophic ones. Catastrophic risk also raises questions about how to rationally respond to such risks. How to rationally respond arguably partly depends on the severity of the uncertainty, for instance, whether quantitative probabilistic information is available, or whether only comparative likelihood information is available, or neither type of information. Finally, catastrophic risk raises important ethical questions about what to do when catastrophe avoidance conflicts with equity promotion.
The current COVID-19 pandemic has focused attention on the vulnerability of the human race in the face of communicable disease. But the pandemic also serves as a wake-up call to the cataclysmic impact that would befall the world if nuclear weapons were ever to be used again. Overwhelming pressure on health-services, considerable disruption to normal life, difficult choices regarding suspension of civil liberties, how to protect key workers and ensure society continues to function–these would all be magnified many times over in the event of a nuclear explosion. Thus, in addition to refocusing attention on the prevention and mitigation of global pandemics, the lessons of the current crisis are much more wide-ranging, and should lead to a renewal of public education, interest, and activism in reducing nuclear dangers.
This contribution argues that the concept of protean power opens a space to think about the limits of control and knowledge about catastrophic possibilities such as nuclear war. To do so, it offers the first distinctive definition of nuclear luck, which has long been acknowledged by policy and military leaders but remains unaccounted for in scholarship. It further shows that the nuclear realm is defined by two key unknowables. However, it argues that protean power perpetuates a survivability bias which has characterized scholarship so far, before suggesting ways to overcome that bias and modify scholarly ethos to acknowledge such catastrophic possibilities.
This paper aims to help policy makers with a characterization of the intrinsic value of biodiversity and its role as a critical foundation for sustainable development, human health, and well-being. Our objective is to highlight the urgent need to overcome economic, disciplinary, national, cultural, and regional barriers, in order to work out innovative measures to create a sustainable future and prevent the mutual extinction of humans and other species. We emphasize the pervasive neglect paid to the cross-dependency of planetary health, the health of individual human beings and other species. It is critical that social and natural sciences are taken into account as key contributors to forming policies related to biodiversity, conservation, and health management. We are reaching the target date of Nagoya treaty signatories to have accomplished measures to prevent biodiversity loss, providing a unique opportunity for policy makers to make necessary adjustments and refocus targets for the next decade. We propose recommendations for policy makers to explore novel avenues to halt the accelerated global loss of biodiversity. Beyond the critical ecological functions biodiversity performs, its enormous untapped repertoire of natural molecular diversity is needed for solving accelerating global healthcare challenges.
Forecasts by economists of the economic damage from climate change have been notably sanguine, compared to warnings by scientists about damage to the biosphere. This is because economists made their own predictions of damages, using three spurious methods: assuming that about 90% of GDP will be unaffected by climate change, because it happens indoors; using the relationship between temperature and GDP today as a proxy for the impact of global warming over time; and using surveys that diluted extreme warnings from scientists with optimistic expectations from economists. Nordhaus has misrepresented the scientific literature to justify the using a smooth function to describe the damage to GDP from climate change. Correcting for these errors makes it feasible that the economic damages from climate change are at least an order of magnitude worse than forecast by economists, and may be so great as to threaten the survival of human civilization.
Accumulating evidence using crowdsourcing and machine learning: a living bibliography about existential risk and global catastrophic risk