Artificial Intelligence, International Competition, and the Balance of Power (May 2018)

World leaders, CEOs, and academics have suggested that a revolution in artificial intelligence is upon us. Are they right, and what will advances in artificial intelligence mean for international competition and the balance of power? This article evaluates how developments in artificial intelligence (AI) — advanced, narrow applications in particular — are poised to influence military power and international politics. It describes how AI more closely resembles “enabling” technologies such as the combustion engine or electricity than a specific weapon. AI’s still-emerging developments make it harder to assess than many technological changes, especially since many of the organizational decisions about the adoption and uses of new technology that generally shape the impact of that technology are in their infancy. The article then explores the possibility that key drivers of AI development in the private sector could cause the rapid diffusion of military applications of AI, limiting first-mover advantages for innovators. Alternatively, given uncertainty about the technological trajectory of AI, it is also possible that military uses of AI will be harder to develop based on private-sector AI technologies than many expect, generating more potential first-mover advantages for existing powers such as China and the United States, as well as larger consequences for relative power if a country fails to adapt. Finally, the article discusses the extent to which U.S. military rhetoric about the importance of AI matches the reality of U.S. investments.LBJ School of Public Affair

Bending the Automation Bias Curve: A Study of Human and AI-based Decision Making in National Security Contexts

Uses of artificial intelligence (AI), especially those powered by machine learning approaches, are growing in sectors and societies around the world. How will AI adoption proceed, especially in the international security realm? Research on automation bias suggests that humans can often be overconfident in AI, whereas research on algorithm aversion shows that, as the stakes of a decision rise, humans become more cautious about trusting algorithms. We theorize about the relationship between background knowledge about AI, trust in AI, and how these interact with other factors to influence the probability of automation bias in the international security context. We test these in a preregistered task identification experiment across a representative sample of 9000 adults in 9 countries with varying levels of AI industries. The results strongly support the theory, especially concerning AI background knowledge. A version of the Dunning Kruger effect appears to be at play, whereby those with the lowest level of experience with AI are slightly more likely to be algorithm-averse, then automation bias occurs at lower levels of knowledge before leveling off as a respondent's AI background reaches the highest levels. Additional results show effects from the task's difficulty, overall AI trust, and whether a human or AI decision aid is described as highly competent or less competent

Nonstate Actors and the Diffusion of Innovations: The Case of Suicide Terrorism

Abstract Studies of terrorism in general and suicide terrorism in particular tend to view terrorist groups independently+ However, what if the propensity for a terrorist group to adopt suicide tactics depends in part on its external linkages and the relationship between the organizational capabilities required to adopt the innovation and the organizational capabilities of the group? This article shows that the organizational change requirements for adopting an innovation significantly influence the overall adoption pattern, along with interlinkages between groups+ Additionally, evaluating the universe of terrorist groups, not only those groups that adopted suicide terrorism but those that did not, shows that Pape's key variable of interest, occupation, does not significantly predict the adoption of suicide terrorism+ Thinking about suicide terrorism as a special case of diffusion in the military area-an innovation for nonstate groups-can help bring the study of suicide terrorism further into the mainstream and highlight how the phenomenon has not just differences, but similarities, to other innovations

Adopting AI: How Familiarity Breeds Both Trust and Contempt

Despite pronouncements about the inevitable diffusion of artificial intelligence and autonomous technologies, in practice it is human behavior, not technology in a vacuum, that dictates how technology seeps into -- and changes -- societies. In order to better understand how human preferences shape technological adoption and the spread of AI-enabled autonomous technologies, we look at representative adult samples of US public opinion in 2018 and 2020 on the use of four types of autonomous technologies: vehicles, surgery, weapons, and cyber defense. By focusing on these four diverse uses of AI-enabled autonomy that span transportation, medicine, and national security, we exploit the inherent variation between these AI-enabled autonomous use cases. We find that those with familiarity and expertise with AI and similar technologies were more likely to support all of the autonomous applications we tested (except weapons) than those with a limited understanding of the technology. Individuals that had already delegated the act of driving by using ride-share apps were also more positive about autonomous vehicles. However, familiarity cut both ways; individuals are also less likely to support AI-enabled technologies when applied directly to their life, especially if technology automates tasks they are already familiar with operating. Finally, opposition to AI-enabled military applications has slightly increased over time

Efficiency of a Brownian information machine

A Brownian information machine extracts work from a heat bath through a feedback process that exploits the information acquired in a measurement. For the paradigmatic case of a particle trapped in a harmonic potential, we determine how power and efficiency for two variants of such a machine operating cyclically depend on the cycle time and the precision of the positional measurements. Controlling only the center of the trap leads to a machine that has zero efficiency at maximum power whereas additional optimal control of the stiffness of the trap leads to an efficiency bounded between 1/2, which holds for maximum power, and 1 reached even for finite cycle time in the limit of perfect measurements.Comment: 9 pages, 2 figure

Domestic Institutions and Wartime Casualties 1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88090/1/j.1468-2478.2011.00679.x.pd

A Review of the External Validity of Clinical Trials with Beta-Blockers in Heart Failure

This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 License.Background: Beta-blockers (BBs) are the mainstay prognostic medication for all stages of chronic heart failure (CHF). There are many classes of BBs, each of which has varying levels of evidence to support its efficacy in CHF. However, most CHF patients have one or more comorbid conditions such as diabetes, renal impairment, and/or atrial fibrillation. Patient enrollment to randomized controlled trials (RCTs) often excludes those with certain comorbidities, particularly if the symptoms are severe. Consequently, the extent to which evidence drawn from RCTs is generalizable to CHF patients has not been well described. Clinical guidelines also underrepresent this point by providing generic advice for all patients. The aim of this review is to examine the evidence to support the use of BBs in CHF patients with common comorbid conditions. Methods: We searched MEDLINE, PubMed, and the reference lists of reviews for RCTs, post hoc analyses, systematic reviews, and meta-analyses that report on use of BBs in CHF along with patient demographics and comorbidities. Results: In total, 38 studies from 28 RCTs were identified, which provided data on six BBs against placebo or head to head with another BB agent in ischemic and nonischemic cardiomyopathies. Several studies explored BBs in older patients. Female patients and non-Caucasian race were underrepresented in trials. End points were cardiovascular hospitalization and mortality. Comorbid diabetes, renal impairment, or atrial fibrillation was detailed; however, no reference to disease spectrum or management goals as a focus could be seen in any of the studies. In this sense, enrollment may have limited more severe grades of these comorbidities. Conclusions: RCTs provide authoritative information for a spectrum of CHF presentations that support guidelines. RCTs may provide inadequate information for more heterogeneous CHF patient cohorts. Greater Phase IV research may be needed to fill this gap and inform guidelines for a more global patient population

The Psychology of Intelligence Analysis: Drivers of Prediction Accuracy in World Politics

This article extends psychological methods and concepts into a domain that is as profoundly consequential as it is poorly understood: intelligence analysis. We report findings from a geopolitical forecasting tournament that assessed the accuracy of more than 150,000 forecasts of 743 participants on 199 events occurring over 2 years. Participants were above average in intelligence and political knowledge relative to the general population. Individual differences in performance emerged, and forecasting skills were surprisingly consistent over time. Key predictors were (a) dispositional variables of cognitive ability, political knowledge, and open-mindedness; (b) situational variables of training in probabilistic reasoning and participation in collaborative teams that shared information and discussed rationales (Mellers, Ungar, et al., 2014); and (c) behavioral variables of deliberation time and frequency of belief updating. We developed a profile of the best forecasters; they were better at inductive reasoning, pattern detection, cognitive flexibility, and open-mindedness. They had greater understanding of geopolitics, training in probabilistic reasoning, and opportunities to succeed in cognitively enriched team environments. Last but not least, they viewed forecasting as a skill that required deliberate practice, sustained effort, and constant monitoring of current affairs

Model-dependence of the γZ\gamma Z dispersion correction to the parity-violating asymmetry in elastic epep scattering

We analyze the dispersion correction to elastic parity violating electron-proton scattering due to $\gamma Z$ exchange. In particular, we explore the theoretical uncertainties associated with modeling contributions of hadronic intermediate states. Taking into account constraints from low- and high-energy, parity-conserving electroproduction measurements, choosing different models for contributions from the non-resonant processes, and performing the corresponding flavor rotations to obtain the electroweak amplitude, we arrive at an estimate of the uncertainty in the total contribution to the parity-violating asymmetry. At the kinematics of the Q-Weak experiment, we obtain a correction to the asymmetry equivalent to a shift in the proton weak charge of $(0.0054\pm0.0020)$. This should be compared to the value of the proton's weak charge of \qwp=0.0713\pm0.0008 that includes SM contributions at tree level and one-loop radiative corrections. Therefore, we obtain a new Standard Model prediction for the parity-violating asymmetry in the kinematics of the Q-Weak experiment of $(0.0767\pm0.0008\pm0.0020_{\gamma Z})$. The latter error leads to a relative uncertainty of 2.8% in the determination of the proton's weak charge, and is dominated by the uncertainty in the isospin structure of the inclusive cross section. We argue that future parity-violating inelastic $ep$ asymmetry measurements at low-to-moderate $Q^2$ and $W^2$ could be exploited to reduce the uncertainty associated with the dispersion correction. Because the corresponding shift and error bar decrease monotonically with decreasing beam energy, a determination of the proton's weak charge with a lower-energy experiment or measurements of "isotope ratios" in atomic parity-violation could provide a useful cross check on any implications for physics beyond the Standard Model derived from the Q-Weak measurement.Comment: 25 pages, 17 figures, 4 tables; revised version accepted for publication in PR