Abstract
In arms control, verification is the essential mechanism that ensures compliance with a treaty or regulation. However, verification is not always an easy task, especially when the contracting parties are suspicious of each other. This text shows in a systematic way how AI can promote verification in the future and presents several projects currently in different stages of development. Starting with how AI-aided translation and analysis of text can support the work of inspectors, the chapter continues to look at the analysis of graphical data, other sensory data, and the possibilities to include multimodal data into the analysis. Many of the projects presented have already passed the proof-of-concept phase and could be deployed in the next few years. However, the text emphasizes the need to use AI only in a team with human inspectors and it calls for more collaboration between AI experts and arms control experts to fully exploit the potential that AI offers for verification.
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Personal conversation with people involved in actual inspection measures (November 2018).
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See for example Gastelum (2020) for the concept.
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https://www.darpa.mil/program/broad-operational-language-translation, retrieved 18 February 2022.
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https://slator.com/technology/darpa-doles-out-millions-to-academia-and-vendors-to-translate-any-language-by-2019/, retrieved 18 February, 2022.
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https://www.darpa.mil/program/multilingual-automatic-document-classification-analysis-and-translation, retrieved 18 February, 2022.
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According to DARPA, MADCAT has “developed optical character recognition and machine translation capabilities for 11 languages: Arabic, Chinese, Dari, Farsi, Hindi, Pashto, Spanish, Russian, Thai, Urdu and Korean”. https://www.darpa.mil/program/multilingual-automatic-document-classification-analysis-and-translation, retrieved February 18, 2022.
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For a good overview of different search algorithms, see Steward et al. (2018, p. 24f).
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https://medium.com/data-science-in-your-pocket/phonetics-based-fuzzy-string-matching-algorithms-8399aea04718, retrieved February 18, 2022.
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https://cloud.google.com/vision, retrieved January 19, 2021. Unfortunately, Google has since removed the option to try out the technology without registering.
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In one sample picture of my mother visiting Berlin in the 1960s her clothes were correctly, yet somewhat vaguely identified as “vintage” and “retro style”.
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https://vcdnp.org/emerging-satellites-for-non-proliferation-and-disarmament-verification/, retrieved February 18, 2022.
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I received similar comments assessing this from the anonymous reviewer as well as from Thomas Reinhold (personal communication, October 2021). See also Molinier et al. (2007).
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https://www.ctbto.org/verification-regime/background/overview-of-the-verification-regime/, retrieved 18 February, 2022.
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https://www.ctbto.org/verification-regime/monitoring-technologies-how-they-work/seismic-monitoring/, retrieved February 18, 2022.
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https://www.llnl.gov/news/researchers-developing-deep-learning-system-advance-nuclear-nonproliferation-analysis, retrieved January 15, 2020.
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Schörnig, N. (2022). Artificial Intelligence as an Arms Control Tool: Opportunities and Challenges. In: Reinhold, T., Schörnig, N. (eds) Armament, Arms Control and Artificial Intelligence. Studies in Peace and Security. Springer, Cham. https://doi.org/10.1007/978-3-031-11043-6_5
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