Wargame of Drones: Remotely Piloted Aircraft and Crisis Escalation

Lin-Greenberg, Erik

doi:10.1177/00220027221106960

Cited by 16 publications

(5 citation statements)

References 61 publications

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“…These studies adopt what Imai et al refer to as the “sequential ignorability assumption,” whereby both possible pretreatment confounders and treatment assignment are assumed to be statistically independent from the potential outcomes and mediators [ 67 ]. Additionally, we opt not to inductively derive possible mediators from respondents’ answers to open-ended questions, as other researchers have done [ 68 ], given the possibility of bias [ 69 ].…”

Section: Methodsmentioning

confidence: 99%

Exploring the artificial intelligence “Trust paradox”: Evidence from a survey experiment in the United States

et al. 2023

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Advances in Artificial Intelligence (AI) are poised to transform society, national defense, and the economy by increasing efficiency, precision, and safety. Yet, widespread adoption within society depends on public trust and willingness to use AI-enabled technologies. In this study, we propose the possibility of an AI “trust paradox,” in which individuals’ willingness to use AI-enabled technologies exceeds their level of trust in these capabilities. We conduct a two-part study to explore the trust paradox. First, we conduct a conjoint analysis, varying different attributes of AI-enabled technologies in different domains—including armed drones, general surgery, police surveillance, self-driving cars, and social media content moderation—to evaluate whether and under what conditions a trust paradox may exist. Second, we use causal mediation analysis in the context of a second survey experiment to help explain why individuals use AI-enabled technologies that they do not trust. We find strong support for the trust paradox, particularly in the area of AI-enabled police surveillance, where the levels of support for its use are both higher than other domains but also significantly exceed trust. We unpack these findings to show that several underlying beliefs help account for public attitudes of support, including the fear of missing out, optimism that future versions of the technology will be more trustworthy, a belief that the benefits of AI-enabled technologies outweigh the risks, and calculation that AI-enabled technologies yield efficiency gains. Our findings have important implications for the integration of AI-enabled technologies in multiple settings.

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Section: Methodsmentioning

confidence: 99%

Exploring the artificial intelligence “Trust paradox”: Evidence from a survey experiment in the United States

et al. 2023

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“…Pauly (2018) utilized wargames with strategic elites to examine attitudes toward nuclear weapons, finding restraint based on reputational risks (see also Goldblum et al, 2019 on the Project on Nuclear Gaming PonG). Lin-Greenberg (2022) also finds counterintuitive escalatory restraints involving the use of drones in wargames with national security experts.…”

Section: Wargaming Cyber Crisesmentioning

confidence: 99%

How cyber operations can reduce escalation pressures: Evidence from an experimental wargame study

Jensen,

Valeriano,

Whitt

2024

Journal of Peace Research

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Cyber operations ranging from deception and espionage to disruption and high-end degradation have become a central feature of modern statecraft in the digital age, yet we lack a clear understanding of how decision-makers employ and respond to cyber operations in times of crisis. Our research provides theoretical mechanisms and empirical evidence for understanding how decision-makers react to cyber triggers and utilize cyber responses during crises. Specifically, we argue that the availability of cyber response creates off-ramps for non-escalatory engagement. Based on experimental wargames involving rival states with power parity in militarized disputes and randomized cyber triggers and response options, we find the availability of cyber response options reduces escalatory behavior via a substitution mechanism. In the absence of cyber response options, however, participants pursue more conventional, escalatory actions, regardless of the triggering mechanism. Our findings underscore how enhancing the availability of cyber response options might reduce strategic escalation risks and offer the space to bargain during periods of conflict.

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“…Wrist (0) Thumb: CMC (1), MCP (2), IP (3), and Tip (4). Index Finger: MCP (5), PIP (6), DIP (7), and Tip (8). Middle Finger: MCP (9), PIP (0), DIP (11), and Tip (12).…”

Section: B the Proposed Modelmentioning

confidence: 99%

“…For instance, in agriculture, drones equipped with advanced sensors can monitor crop health [4], optimize water usage [5], and manage resources * Corresponding authors more sustainably [6]. Similarly, in emergency response, drones provide invaluable assistance in locating victims and assessing damage in disaster stricken areas, demonstrating their critical role in saving lives and managing crises [7].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Enhanced Hand Gesture Recognition for Efficient Drone use in Agriculture

Srinil,

Thongnim

2024

ijacsa

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The use of deep learning in unmanned aerial vehicles (UAVs), or drones, has greatly improved various technologies by making complex tasks easier, faster, and requiring less human help. This study looks into how artificial intelligence (AI) can be used in farming, especially through creating a system where drones can be controlled by hand gestures to support agricultural activities. By using a special type of AI called a Convolutional Neural Network (CNN) with an EfficientNet B3 model, this research developed a gesture recognition system. It was trained on 1,393 pictures of different hand signals taken under various light conditions and from three different people. The system was evaluated based on its training and testing performance, showing very high scores in terms of loss, accuracy, F1 score, and the Area Under the Curve (AUC), which means it can recognize gestures accurately and work well in different situations. This has big implications for farming, as it gives farmers an easy way to control drones for tasks like checking on crops and spraying them precisely, which also helps keep them safe. This study is an important step towards smarter farming practices. Moreover, the system's ability to perform well in different settings shows it could also be useful in other areas like construction, where drones need to operate precisely and flexibly.

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Wargame of Drones: Remotely Piloted Aircraft and Crisis Escalation

Cited by 16 publications

References 61 publications

Exploring the artificial intelligence “Trust paradox”: Evidence from a survey experiment in the United States

Exploring the artificial intelligence “Trust paradox”: Evidence from a survey experiment in the United States

How cyber operations can reduce escalation pressures: Evidence from an experimental wargame study

Deep Learning Enhanced Hand Gesture Recognition for Efficient Drone use in Agriculture

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