AI and the Automation of Warfare

Packer and Reeves also collaborated on the forthcoming co-authored book Prison House of the Circuit: Politics of Control from Analog to Digital (Packer, Nuñez de Villavicencio, Monea, Oswald, Maddalena, & Reeves, in press). [...]just two or three weeks ago, the U.N. released a report explaining that it's likely that the first instance of autonomous drones making their own decision to kill soldiers occurred in a skirmish in Libya in March 2020 (United Nations Security Council, 2021). [...]I think there's a general recognition by folks in the military, by journalists writing about this issue, by intellectuals, that there has been a shift in the past half century, 75 years, to a different kind of warfare. In terms of a paradigm, too, I'm also just interested because the American military, post-Vietnam, has described itself as subscribing to the idea of information warfare-using embedded journalists, managing the flows of information surrounding conflicts. Media doot only manipulate soldiers to fight better and citizens to support various military efforts but rather, the scale of warfare has reached a level of complication that without a vast logistical apparatus, war is going to be lost-that logistical terrain of war is going to be lost-and the "logistically dominant" force, nation, (or) group of allies will prevail.

Accelerated ageing is associated with increased COVID-19 severity and differences across ethnic groups may exist.

Background: While increased age is an established risk factor for COVID-19, there is great heterogeneity in outcomes within age groups. This is because chronological age does not reflect health, unlike biological age. We intend to investigate the association between accelerated ageing and COVID-19 outcomes through the lens of three measures, namely phenotypic age acceleration (PhenoAgeAccel), telomere length (Adjusted T/S Ratio) and facial ageing, and to examine whether there are differences across ethnic groups. Methods: Taking participants from the UK Biobank, we associated accelerated ageing with severe COVID-19 outcomes, defined as COVID-related hospitalisation or death. Separate logistic regressions models were created for age and the three accelerated ageing-related variables, adjusting for a variety of covariates in each model. Multivariable logistic regression models were also created within White, Black, Asian and Other ethnic groups to assess for potential differing associations. Forward likelihood ratio logistic regression models were created to evaluate importance of the variables and to assess for patterns of association across the total population and ethnic groups. Results: After adjusting for all covariates, the odds ratio (OR) and 95% confidence interval (95% CI) of COVID-19 severe outcomes for age was 1.080 (1.074-1.086). After further adjusting age for the accelerated ageing variables, the ORs were 1.029 (1.020-1.039) for PhenoAgeAccel and 0.847 (0.772-0.929) for Facial Ageing's "Younger Than You Are" while Adjusted T/S ratio and "Older Than You Are" were statistically insignificant. The OR for age remained similar across ethnic groups. Both PhenoAgeAccel and younger facial ages in the White population and PhenoAgeAccel in the Black population had ORs of 1.031 (1.021-1.042), 0.853 (0.774-0.939), and 1.049 (1.001-1.100), respectively. Both Adjusted T/S Ratio and older facial ages showed statistical insignificance in all ethnicities. In forward logistic regression, age and PhenoAgeAccel were the age-related variables selected most frequently in all models. Interpretation: Accelerated ageing is associated with increased COVID-19 severity. The mechanisms at work here are likely immunosenescence and inflamaging. This association indicates that anti-ageing treatment may improve COVID-19 outcome. The results within ethnic groups and that of telomere length were inconclusive, but point to a need for future, more focused research on the topic.