Publishing Disclaimer: In all of its publications and products, Military Review presents professional information. However, the views expressed therein are those of the authors and are not necessarily those of the Army University, the Department of the Army, or any other agency of the U.S. government.

---

 

Breaking Babel

Using AI to Enable Real-Time Translation in the Classroom and Beyond

 

Luke M. Herrington, PhD

 

Download the PDF

 

It should come as no surprise that diplomats and military operators routinely work with foreign nationals from allied and partnered nations, while intelligence analysts regularly access information produced by America’s adversaries. Foreign language skills and access to skilled interpreters are thus essential to American foreign policy and national security. This makes language acquisition a strategic investment. Not only does the ability to read, write, and speak another language minimize space for cultural misunderstandings that erode relationships across language barriers, but it also improves the Nation’s ability to compete in the global economy. Despite this, the Department of Defense slashed funding for 40 percent of its language programs in 2024 due to congressional budget cuts. Similarly, state universities across the United States have scaled back significantly on their own foreign language programs.¹

These trends, along with the emergence of commercial services like Duolingo and the increasing prevalence of machine translation through natural language processing (NLP) and generative artificial intelligence (AI), have some sounding the death knell for the foreign language degree. However, these reductions are probably at least as much a result of declining enrollment. The Modern Language Association recorded a 16.6 percent nationwide drop in students taking foreign languages from 2016 to 2021, well before the budget cuts or the release of ChatGPT in 2022.² Even so, these trends are helping to upend foreign language education.³ As the ability to communicate with service members from other nations is key to interoperability, they also risk degrading the warfighting and deterrence capabilities of the joint force. In other words, if they continue unabated, budget cuts and declining foreign language enrollments will undermine American national security and economic competitiveness.

Nevertheless, the situation need not be so dire. Some of the very forces driving these changes could be leveraged to make up for shortfalls in foreign language learning. Indeed, students, faculty, national security professionals, and others in fields related to foreign countries, cultures, or populations are well situated to take advantage of ongoing advances in NLP for the purpose of translation. NLP is the subdiscipline of computer science and AI that has given computers the ability to consume, interpret, and produce comprehensible human language, including the large language models (LLM) behind such chatbots as ChatGPT, Grok, and Gemini.⁴ It is also responsible for significant strides in machine translation that could empower many by making foreign languages more accessible. Students and scholars in professional military education (PME) are just some of those who stand to benefit most from the real-time translation capabilities now being offered through most web browsers and LLMs. National security and intelligence professionals, military and diplomatic historians, area studies scholars, political scientists in both international relations and comparative politics, and countless others who work in proximity to the world’s many language barriers (nongovernmental organizations working on human rights, social workers engaged with immigrant communities, etc.) all stand to benefit.

While most people today are probably acquainted more with recent advances associated with commercial products like Google Translate than they are with NLP more broadly, the field has a long history. The development of AI-generated translation has its origins in the Cold War. As far back as 1954, Central Intelligence Agency- and National Science Foundation-backed researchers from IBM and Georgetown University were engaged in machine translation experimentation. They succeeded in producing English-language translations of Russian text, which in turn motivated the Soviet Union to launch a similar project.⁵ For its part, Google Translate launched in 2006. Built on some fifty years of continued development, the free service was trained on a corpus of linguistic data provided by open-source records at the United Nations and European Parliament.⁶ No doubt to the chagrin of many a foreign language instructor, personal interpreter internet translation apps for smartphones followed a few years later.⁷ Yet, the most recent advances in NLP and machine translation are associated with the ongoing revolution in LLM-based chatbots, and it is here where the implications of AI-enabled translation, especially for the classroom and open-source intelligence gathering, are most evident.

Of course, the release of ChatGPT brought with it a significant clamor aimed at understanding the implications of generative AI for higher education. While many rightly focus on AI in writing and the concordant perils of plagiarism, attention—especially in PME—is increasingly turning to the beneficial uses of AI in the classroom and workplace.⁸ This article contributes to the latter discourse by arguing that AI can be leveraged in PME to enable real-time translation to the benefit of student learning (and with it, American national security). Indeed, based on my experiences at the U.S. Army School of Advanced Military Studies (SAMS), I assert that using AI to facilitate real-time translation in the classroom facilitates active and self-directed learning experiences in at least two ways. First, it can be used to equip students with the capacity to more effectively follow current events abroad. Second, a similar use case involves supplementing research with heretofore inaccessible primary source material.

Current Events: The AI-Enabled Translation of Foreign Media

Students at SAMS, like students at other civilian and military institutions, must stay abreast of events unfolding abroad. While perusing media outside of the anglophone world—to remain informed of international affairs or to better understand foreign cultures—it is not uncommon for them to struggle with the inaccessibility of available information. Even multilingual students run into language barriers because classroom responsibilities require them to familiarize themselves with countries for which they lack language training. For example, students who may be quite skilled in Spanish, French, or Farsi are likely just as incapable of reading Chinese or listening to Arabic. Thus, where they may have no problem reading or listening to El País, Le Monde, or the Islamic Republic News Agency, China’s People’s Daily or parts of Al Jazeera will remain closed off to them. Of course, there are some seven thousand unique languages (and presumably an even greater number of unique dialects) in the world.⁹ Thus, even students with the time and motivation to learn additional languages will be incapable of learning them all.

SAMS students get around these language barriers in several ways. The first is the most straightforward: they turn to English-language content. Many foreign news sites intend their work for both domestic and international audiences, so they provide their own English translations. In democratic regimes with rigorous journalistic standards, this means they can access reliable information without incident. For authoritarian nations, where the freedom of the press is in doubt, relying on English translations is more difficult. Such sources raise questions about impartiality and objectivity. Consider the People’s Daily. Intended to shape both domestic and international attitudes, the Chinese publication is produced in as many as nineteen languages. However, People’s Daily is the official propaganda outlet for the Chinese Communist Party.¹⁰ As such, students who identify and consume English-language news stories published on People’s Daily Online must engage it cautiously while questioning whether it is a reliable narrator of Chinese current events.

Nation-states have long been cognizant of the problem of multiple audiences when promoting their strategic narratives at home and abroad.¹¹ The same goes for authoritarian nations like China.¹² Unfortunately, this means that even mindful students who land on People’s Daily’s English-language website or others like it can be blindsided in at least three ways. First, the content they read may be multivocal in nature. That is, while being intended for both an internal and external audience will lead to the full translation of some information when published, subtext may convey different latent meanings to each audience.¹³ I am presently unfamiliar with any extant research that may serve to educate students of military studies or international politics on the way authoritarian regimes leverage multivocality to send different signals to domestic and international audiences. Nevertheless, China has an asymmetric advantage in English-language proficiency compared to the United States’ own Chinese skills, and as research on extremism and political violence illustrates, the ability for a single message (or “polyvalent performance”) to simultaneously convey multiple meanings is how so-called “dog whistle politics” function.¹⁴

The second problem students may encounter is that many of these news sites will segregate content only intended for the nation’s internal audiences from material penned exclusively for its external audiences by altogether eschewing translation when editorial or political elites deem appropriate. Content may appear on the English version of the site that does not appear in the original language and vice versa. When this happens, locating English-language translations of noteworthy articles or broadcasts published in foreign language media outlets will be difficult (if not impossible).

The final problem is related. The same media outlets may occasionally include substantively different content for their domestic and international consumers even when the “same” stories have been translated into different languages.¹⁵ In other words, students must understand that English-language content is produced for Western audiences for a reason, while content intended for domestic readership may often be inaccessible without taking additional steps.

For intrepid SAMS students, these steps include using browser-based translation software (like that native to Mozilla’s Firefox or Google’s Chrome browsers). Accessing AI-generated English-language translations enables cross referencing and fact checking because students can read and compare stories intended only for domestic audiences with those produced for international audiences. This equips them to identify inconsistencies across versions. Likewise, it empowers them to identify content published exclusively in one language or another. Taken together, automatic browser-supported translation leads not only to more nuanced evaluations of current events unfolding abroad but also more holistic understanding of foreign media perspectives. Further, using browser-assisted translations enables students to unpack new perspectives, minimize exposure to disinformation, and break free from their own national parochialisms more effectively than relying entirely on official translations.

But what should students do when their browsers lack the ability to translate complex or uncommon languages? When material is not published in English and their browsers cannot translate it, many students at SAMS misperceive open-source material as inaccessible. For instance, Firefox does not yet support the translation of Chinese, so Firefox users at SAMS cannot read translations of Chinese-language articles published by People’s Daily. Yet, just as cautious students can minimize the risk of becoming overly reliant on the “party line” by thinking critically about official translations, so too can they avoid missing out altogether when browser-based translations are unavailable.

Commercial AI services like ChatGPT, Department of War (DoW) resources like AskSage, and resources available to both the public and military like Gemini render browser-based limitations moot. In the age of generative AI, media written in other tongues need not remain closed off from the English reader. Students need only to prompt their preferred LLM to do the heavy lifting of translation on their behalf. Even audiovisual material is increasingly accessible. During the winter of 2025, SAMS students used Kapwing and ElevenLabs, respectively, to generate English-language subtitles and voiceovers for foreign language YouTube videos, making it possible to understand audiovisual news reports originally presented in languages for which they had no training.

Historical Records: AI-Enabled Primary Source Translation

If AI can enable news media translation, it stands to reason that other primary source records represent a second use case. In fact, AI is already employed for primary source translation in some quarters of the military. As part of its “In Their Own Words” project, the China Aerospace Studies Institute at Air University employs an automated translation process as part of its methodology, including, for example, in the translation of the 2020 edition of Science of Military Strategy.¹⁶ As a result, Western readers now have access to an important primary source on Chinese military doctrine.

Furthermore, AI can be used to translate primary sources for some of the same reasons as it can be used to translate current events. For example, the 1796 Treaty of Tripoli, which famously has a provision about the United States having been founded in no sense on Christianity, includes the relevant clause only in its English text.¹⁷ The official Arabic version of the treaty is reportedly substantively different, meaning American and Arab audiences were exposed to different messages with its publication. The same goes for similar treaties that followed.¹⁸ Why this occurred can be debated, but students interested in interpreting such texts for themselves are incapable of identifying such important distinctions without access to the Arabic primary source material.

Consider national security concerns over TikTok as another example. Prior to its divestment from ByteDance, apprehension about the wildly successful social media and content-sharing internet application used by half of the American public was often dismissed as the product of hawkish or anti-China special interest groups. Yet, Chinese-language writing makes it clear that security thinkers in the People’s Republic have given significant attention to the use of short-form content platforms for propaganda purposes. But how might TikTok users illiterate in Chinese have found this information for themselves? For a forthcoming article, a colleague of mine at SAMS, Dan Cox, and I used AskSage and Google Gemini to translate several Chinese-language articles for our background research. As a result, we learned for ourselves that Chinese national security thinkers are indeed very interested in the ways TikTok and similar social media and content creation platforms can be and have been used to promote Communist Party domestic messaging, People’s Liberation Army strategic narratives, and Chinese soft power more generally.¹⁹ The figure, which shows an example paragraph in the original Chinese translated using three different methods (i.e., browser-based translation, Gemini, and AskSage), illustrates the process we employed.

By reading the Chinese-language primary sources for ourselves, Cox and I were able to better understand how TikTok can be employed in Chinese information warfare, both against its own people and against the West. The same should be done for other primary sources like the Treaty of Tripoli because the ability to access foreign language primary sources has the same advantage as accessing primary source material published in one’s native tongue.²⁰ That is, readers can digest and interpret content for themselves without having to rely on intermediaries to explain the information. PME students (and other interested members of the public) who make no attempt to translate information for themselves run into the same problem as students relying on official translations encounter. That is, they must trust human translators as reliable mediators of information. To be sure, credible human interpreters will be better at detecting the important subtextual features of foreign language—things like tone, sarcasm, colloquialisms, metaphor—at least for the foreseeable future. Expert translators will even be able to detect some instances of multivocality. However, translations of important primary source documents may not always be available from credible interpreters.

Take Michael Pillsbury’s The Hundred-Year Marathon as a case in point.²¹ The book represents Pillsbury’s subjective interpretation of China’s plans to erode American hegemony and replace the liberal international order. More popular memoir than work of serious scholarship, he derives his conclusions from his experiences working in China as a member of the national security staff and from personal translations of several Chinese-language national security documents.²² However, Pillsbury’s translation skills have long been scrutinized. Soyoung Ho argues that Pillsbury has a lax relationship with both translation and primary sources. After citing himself early in his career, subsequent fact-checks were unable to substantiate his translations when examining his previous work. Beyond this, Pillsbury has been criticized for inserting ideas into his translations, abridging statements, and ignoring important contexts, all in linguistically inappropriate ways. Indeed, says Ho, Pillsbury is responsible for introducing the concept of the assassin’s mace to describe Chinese asymmetric weapons, but the idea in context is more accurately translated as “trump card.” This also extends beyond his scholarship; Pillsbury’s mistranslations once caused a diplomatic incident between Donald Rumsfeld and Hu Jintao.²³

In reviews of his 2015 book, similar critiques emerge. Peter Mattis suggests that Pillsbury’s translations are vague and sloppy, while Arthur Waldron’s otherwise laudatory review cautions that Pillsbury may be an unreliable or even untrustworthy narrator.²⁴ Yet, it is Jude Blanchett that systematically dismantles Pillsbury’s approach to evidence and translation. In “The Devil Is in the Footnotes,” Blanchette argues that Pillsbury’s translations and citations are riddled with “errors, misdirection, and puzzling omissions,” with some of his claims even being directly contradicted by his own notes.²⁵ Despite criticizing Western China experts for their inability to work with primary source material, Pillsbury also leans heavily on secondary sources with uncited translations. Ultimately, Blanchette concludes, “books that challenge” dovish views on China are needed, especially from people like Pillsbury who have had deep interaction with the Chinese defense community, but Pillsbury’s is not that book; it “is too replete with errors to inform.”²⁶

Rush Doshi’s recent work restores some confidence in Pillsbury. Doshi’s The Long Game is a far more rigorous, well-designed scholarly analysis of Chinese primary sources that substantiates Pillsbury’s concerns, particularly with respect to the putative assassin’s mace program.²⁷ Yet, not only did it take six years from the time of The Hundred-Year Marathon to publish The Long Game, meaning students interested in exploring Pillsbury’s ideas would have had no way to substantiate his claims during that time, but even now, those interested in the sources reviewed by either Pillsbury or Doshi are also left in the middle of an unresolved debate. By translating material for themselves with AI, students could be empowered to fact-check such assertions in the face of controversy without having to wait for another language expert to do so for them.

This is exactly what the SAMS students using Kapwing’s captioning service and Elevenlabs’ dubbing service did in the winter of 2025. After claims that China had automated its cruise missile production went viral online, students translated the evidence ostensibly supporting the assertion.²⁸ A China Central Television video without an English-language analogue was said to provide evidence that China could build as many as one thousand missiles a day at a single factory, but neither the AI-generated dub nor the AI-generated subtitles for the video could substantiate the claim.²⁹ The factory could very well be capable of such output, but this was not a fact students could verify from either translation of the viral video clip.³⁰

Conclusion

AI-enabled translation enables better access to foreign perspectives as well as the identification of discrepancies across different versions of foreign language publications. It can thus help cultivate strategic empathy and promote better situational awareness of the operational environment. While the development of language proficiency is desirable, not everyone has the time or resources to become fluent in a second or subsequent language. Dyslexia, for example, makes foreign language acquisition difficult enough that waiving foreign language requirements is often considered a reasonable accommodation in both secondary and higher education.³¹ For students who are already multilingual, developing new language skills will eventually come with diminishing returns. After all, not only are there too many languages to learn in one lifetime, but language acquisition also becomes more difficult with age.³² Hence, as my experience at SAMS corroborates, even multilingual students can encounter insurmountable language barriers. Though the material in these instances may not always require immediate translation, accessing it would nonetheless benefit student learning. Translation only becomes more urgent for situations involving the operational force or other national security professionals in the field.

Regardless, anyone translating foreign languages with browser-based technology or the help of an LLM should be deliberate about addressing the limitations of AI-enabled translation. Students may, for example, fall prey to the problem of multivocality when leaning on AI, just as they might with official translations. Yet, they can guard against this by thinking critically about how translations can be intentionally misleading. Where content deliberately tailored to an international audience may be aimed at promoting a country’s strategic narratives or enhancing its soft power, content intended for a domestic audience can be intended to manipulate reader perceptions in ways that also benefit a propagandist. Students must remember this, especially when reading content published in or by an authoritarian nation.

There is less value when students interpret secondary information (i.e., someone else’s interpretation) than there is when students provide their own interpretations of primary source material. However, machine-generated translation like human translation is fundamentally an act of interpretation subject to bias and error.³³ Students might compensate by leveraging multiple translations. By comparing translations from different platforms, they can develop a more nuanced understanding of the primary source material with which they are working, as well as a stronger appreciation for the intricacies of translation itself.

Students can likewise experiment with different approaches, including comparison of documents translated on a sentence-by-sentence and paragraph-by-paragraph basis with those translated at the article level. This method could compensate for technical limitations in current DoW systems. Where AskSage is built on the foundation of powerful commercial models like ChatGPT, another DoW platform called CamoGPT was trained primarily on English-language data.³⁴ Consequently, AskSage is better equipped to translate large bodies of foreign language text, but it too is more limited than its commercial counterparts due to the amount of data it truncates during the translation process. One approach that seems to improve AskSage functionality involves paragraph-level translation, as opposed to article-level translation. Trying to translate whole articles in a single go might be useful for context, but information is undoubtedly truncated to cope with the rapid devouring of tokens required to process vast amounts of textual data.³⁵

Mistakes and misunderstandings are still probable without comprehension of context or knowledge of other nuances in human communication, but the opportunity for miscommunication and misunderstanding is at least as large for students who do nothing. Making no attempt to translate written or even audiovisual foreign primary sources will leave students dependent on the perspectives of linguistic gatekeepers as information mediators, undermining original analysis and leading to other forms of bias. Ultimately, eschewing AI-enabled translation will further erode PME students’ and practitioners’ respective access to foreign language information. At the very best, doing nothing will leave many in the classroom, in the field, and beyond without access to important sources of open-source data capable of shedding light on the complexities of the modern operational environment. At the worst, reductions in the foreign language acquisition rate will undermine interoperability and have negative follow-on effects for America’s warfighting capabilities. Either way, eschewing AI-enabled translation would mean leaving PME—and the Nation’s security—firmly in the past.

Opinions, conclusions, and recommendations expressed or implied are solely those of the author and do not necessarily represent the School of Advanced Military Studies, the Command and General Staff College, the Department of War, or any other U.S. government agency; references to specific platforms and software are not intended as either endorsements or promotion. The author is grateful to Jacob A. Mauslein, PhD, and the SAMS classes of 2024 and 2025 for making this article possible.

---

Notes

1. Kathryn Palmer, “Defense Department Cuts 13 of Its Language Flagship Programs,” Inside Higher Ed, 15 May 2024, https://www.insidehighered.com/news/global/study-abroad/2024/05/15/defense-department-cuts-13-its-language-flagship-programs; Jeff Peterson, “Opinion: Cuts to Language Education Programs Jeopardize Our Government and Society,” Deseret News, 8 February 2025, https://www.deseret.com/opinion/2025/02/08/language-education-programs-funding-cuts-harm-government-society/.
2. Natalia Lusin et al., Enrollments in Languages Other Than English in US Institutions of Higher Education, Fall 2001 (Modern Language Association, 2023), https://www.mla.org/content/download/191324/file/Enrollments-in-Languages-Other-Than-English-in-US-Institutions-of-Higher-Education-Fall-2021.pdf.
3. Lauren Coffley, “Lost in Translation? AI Adds Hope and Concern to Language Learning,” Inside Higher Ed, 6 June 2024, https://www.insidehighered.com/news/tech-innovation/artificial-intelligence/2024/06/06/ai-adds-hope-and-concern-foreign-language; Patrick Jack, “Is AI the Final Nail in the Coffin for Modern Languages?,” Times Higher Education, updated 18 July 2024, https://www.timeshighereducation.com/depth/ai-final-nail-coffin-modern-languages; Damon Beres, “How AI Is Reshaping Foreign-Language Education,” The Atlantic, 29 March 2024, https://www.theatlantic.com/newsletters/archive/2024/03/how-ai-is-reshaping-foreign-language-education/677930/; Louis Matsakis, “Opinion: Our Loss If AI Replaces Foreign-Language Education,” Government Technology, 3 April 2024, https://www.govtech.com/education/higher-ed/opinion-our-loss-if-ai-replaces-foreign-language-education; Lusin et al., Enrollments in Languages Other Than English; Ryan Quinn, “Foreign Language Enrollment Sees Steepest Decline on Record,” Inside Higher Ed, 16 November 2023, https://www.insidehighered.com/news/faculty-issues/curriculum/2023/11/16/foreign-language-enrollment-sees-steepest-decline-record.
4. Cole Stryker and Jim Holsworth, “What Is NLP (Natural Language Processing)?,” IBM, 11 August 2024, https://www.ibm.com/think/topics/natural-language-processing.
5. Mary Jo Nye, “Speaking in Tongues: Science’s Centuries-Long Hunt for a Common Language,” Distillations Magazine, 29 June 2016, https://www.sciencehistory.org/stories/magazine/speaking-in-tongues/.
6. Nick Schäferhoff, “The History of Google Translate (2004-Today): A Detailed Analysis,” Translation (blog), Translate Press, 9 July 2024, https://translatepress.com/history-of-google-translate/.
7. Schäferhoff, “History of Google Translate.”
8. Among others, see James D. Walsh, “Everyone Is Cheating Their Way Through College,” New York Magazine, 7 May 2025, https://nymag.com/intelligencer/article/openai-chatgpt-ai-cheating-education-college-students-school.html; Will Coldwell, “‘I Received a First but It Felt Tainted and Undeserved’: Inside the University AI Cheating Crisis,” Guardian, 15 December 2024, https://www.theguardian.com/technology/2024/dec/15/i-received-a-first-but-it-felt-tainted-and-undeserved-inside-the-university-ai-cheating-crisis; Adam T. Biggs, “Enhancing Professional Military Education with AI: Best Practices for Effective Implementation,” Journal of Military Learning 9, no. 2 (April 2025): 22–37, https://www.armyupress.army.mil/Journals/Journal-of-Military-Learning/Journal-of-Military-Learning-Archives/JML-April-2025/Enhancing-pme-with-ai/; Luke M. Herrington and Jacob A. Mauslein, “An Eye for AI: Integrating Generative AI Imagery in Graduate PME,” Journal of Military Learning 9 (September 2005): 46–67, https://www.armyupress.army.mil/Journals/Journal-of-Military-Learning/Journal-of-Military-Learning-Archives/JML-2025/An-Eye-for-AI/; Patrick Kelly and Hannah Smith, “How to Think About Integrating Generative AI in Professional Military Education,” Military Review Online Exclusive, 3 May 2024, 1–8, https://www.armyupress.army.mil/Portals/7/military-review/Archives/English/Online-Exclusive/2024/Integrating-Generative-AI/Kelly-and-Smith-Generative-AI-UA.pdf; James Lacey, “Peering into the Future of Artificial Intelligence in the Military Classroom,” War on the Rocks, 3 April 2025, https://warontherocks.com/2025/04/peering-into-the-future-of-artificial-intelligence-in-the-military-classroom/; Kelly Ihme and Matt Rasmussen, “Embracing the Inevitable: Integrating AI into Professional Military Education (PME),” Small Wars Journal, 7 May 2025, https://smallwarsjournal.com/2025/05/07/embracing-the-inevitable/; Kim Cates and Marc Banghart, “Improving After Action Review (AAR): Applications of Natural Language Processing and Machine Learning,” Journal of Military Learning 6, no. 1 (April 2022): 3–14, https://www.armyupress.army.mil/Journals/Journal-of-Military-Learning/Journal-of-Military-Learning-Archives/April-2022/Cates-Action-Review/; Jerry Champion, “How to Become the AI-Empowered Iron Major,” From the Green Notebook, 10 June 2025, https://fromthegreennotebook.com/2025/06/10/how-to-become-the-ai-empowered-iron-major/.
9. Steven Anderson, Languages: A Very Short Introduction (Oxford University Press, 2012).
10. Guoguang Wu, “Command Communication: The Politics of Editorial Formulation in the People’s Daily,” China Quarterly 137 (March 1994): 194–211; Bertie Lyhne-Gold, “The Many Faces of the People’s Daily,” China Media Project, 6 January 2025, https://chinamediaproject.org/2025/01/06/the-many-faces-of-the-peoples-daily/; Daniel Mattingly et al., “Chinese State Media Persuades a Global Audience that the ‘China Model’ Is Superior: Evidence from a 19-Country Experiment,” American Journal of Political Science 69, no. 3 (July 2025): 1029–46, https://doi.org/10.1111/ajps.12887; Sarah Cook et al., Beijing’s Global Media Influence: Authoritarian Expansion and the Power of Democratic Resilience (Freedom House, 2022), https://freedomhouse.org/sites/default/files/2022-09/BGMI_final_digital_090722.pdf; Hongyu and Du Mingming, “People’s Daily Online Launches Vietnamese, Urdu, Hindi Language Versions,” People’s Daily, 11 April 2025, https://en.people.cn/n3/2025/0411/c98649-20300684.html; also see Thinking Chinese, “Chinese and English Versions of China’s Leading News Papers—Two Styles of Journalism,” archived 21 March 2012 at https://web.archive.org/web/20120321090509/http://thinkingchinese.com/index.php?page_id=346.
11. Bryant Wedge, “International Propaganda and Statecraft,” Annals of American Academy of Political and Social Science 398, no. 1 (November 1971): 36–43, https://doi.org/10.1177/000271627139800105; Robert Jervis, The Logic of Images in International Relations (Columbia University Press, 1970).
12. Andrew Chubb and Frances Yaping Wang, “Authoritarian Propaganda Campaigns on Foreign Affairs: Four Birds, One Stone, and the South China Sea Arbitration,” International Studies Quarterly 67, no. 3 (September 2023): 1–14, https://doi.org/10.1093/isq/sqad047; Xiaoyu Pu, Rebranding China: Contested Status Signaling in the Changing Global Order (Stanford University Press, 2019).
13. Charles Tilly, The Politics of Collective Violence (Cambridge University Press, 2003); John H. Flemming and John M. Darley, “Mixed Messages: The Multiple Audience Problem and Strategic Communication,” Social Cognition 9, no. 1 (March 1991): 25–46, https://doi.org/10.1521/soco.1991.9.1.25.
14. Peter Loftus et al., “A War by Words: Language and Cultural Understanding in the Age of Information Warfare,” Journal of Indo-Pacific Affairs, 24 November 2020, https://www.airuniversity.af.edu/JIPA/Display/Article/2425627/a-war-by-words-language-and-cultural-understanding-in-the-age-of-information-wa/; Tilly, Politics of Collective Violence, 176; also see Olga V. Chyzh et al., “The Effects of Dog-Whistle Politics on Political Violence,” unpublished manuscript, 1 January 2019, 1–31, https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1058&context=pols_pubs; Bethany L. Albertson, “Dog-Whistle Politics: Multivocal Communication and Religious Appeals,” Political Behavior 37 (2015): 3–26, https://doi.org/10.1007/s11109-013-9265-x.
15. School of Advanced Military Studies students discovered this after comparing the dramatically different lengths of some Chinese-language articles with their official English-language translations in the winter of 2024.
16. China Aerospace Studies Institute, “In Their Own Words: 2020 Science of Military Strategy,” Journal of Indo-Pacific Affairs, 26 January 2022, https://www.airuniversity.af.edu/JIPA/Display/Article/2913216/in-their-own-words-2020-science-of-military-strategy/.
17. Yale University Avalon Project, “Treaty of Peace and Friendship, Signed at Tripoli November 4, 1796,” The Barbary Treaties 1786–1816, accessed 9 January 2026, https://avalon.law.yale.edu/18th_century/bar1796t.asp.
18. Although platforms like ChatGPT can translate Arabic, the Arabic-language version of the text is not publicly available in machine-readable text. This implies that an inability to find foreign language sources will remain a challenge, but as archives digitize more content over time, this problem will diminish. For the English-language version of the treaty, see Yale University Avalon Project, “Treaty of Peace and Friendship”; for secondary commentary on the translation differences, see Denise A. Spellberg, Thomas Jefferson’s Qur’an: Islam and the Founders (Vintage Books, 2013).
19. Luke M. Herrington and Dan G. Cox, “Too Little, Too Late? The Securitization of TikTok and the Future of Chinese Information Warfare,” chap. 2 in Strategic Competition in the Indo-Pacific Region: “Pacing Threat,” and “Great Power Competition,” or Competition of Alliances? (working title), ed. Mahir Ibrahimov (Army University Press, forthcoming).
20. “History in the Raw,” National Archives Educator Resources, updated 15 August 2016, https://www.archives.gov/education/history-in-the-raw.html; also see Melvin E. Page and Brian J. Maxson, A Short Guide to Writing About History (Waveland Press, 2023).
21. Michael Pillsbury, The Hundred-Year Marathon: China’s Secret Strategy to Replace America as the Global Superpower (Henry Holt, 2015).
22. Pillsbury, Hundred-Year Marathon.
23. Soyoung Ho, “Panda Slugger,” Washington Monthly 38, no. 7 (July-August 2006): 26–31, archived 19 July 2006 at https://web.archive.org/web/20060719121708/https://washingtonmonthly.com/features/2006/0607.ho1.html.
24. Peter Mattis, “A Shaky Case for Chinese Deception,” War on the Rocks, 19 February 2015, https://warontherocks.com/2015/02/a-shaky-case-for-chinese-deception-a-review-of-the-hundred-year-marathon/; Arthur Waldron, “A Bit of a Maverick,” review of The Hundred-Year Marathon: China’s Secret Strategy to Replace America as the Global Superpower, by Michael Pillsbury, Naval War College Review 68, no. 3 (2015): 148–51, https://digital-commons.usnwc.edu/cgi/viewcontent.cgi?article=1227&context=nwc-review.
25. Jude Blanchette, “The Devil Is in the Footnotes: On Reading Michael Pillsbury’s The Hundred-Year Marathon,” 21st Century China Program, accessed 9 January 2026, https://china.ucsd.edu/_files/The-Hundred-Year-Marathon.pdf.
26. Blanchette, “The Devil Is in the Footnotes.”
27. Rush Doshi, The Long Game: China’s Grand Strategy to Displace American Order (Oxford University Press, 2021).
28. For example, see David Goldman, “America Has No Ukraine Plan B Except More War,” Asia Times, 25 March 2024, https://asiatimes.com/2024/03/america-has-no-ukraine-plan-b-except-more-war/#; Clash Report (@clashreport), “Chinese automated cruise missile production line. The video report says the factory has the capacity to produce the components for 1,000 missiles/day if running 24/7,” X (formerly Twitter), 1 April 2024, https://x.com/clashreport/status/1774741155172770106.
29. “中国央视公开巡航导弹自动化生产工厂 China’s CCTV Reveals Automated Cruise Missile Production Factory,” posted 1 November 2023 by 台湾海峡填海造陆工程队 [Taiwan Strait Land Reclamation Engineering Team; @xxxxxxxGTR], YouTube, 3:27, https://www.youtube.com/watch?v=TWSGVLvf5cw. English title translation provided by @xxxxxxxGTR; user profile name translated by AskSage.
30. However, an analysis on Reddit identifies the original clip as a scene from a documentary on “flying swords,” detailing the history of Chinese missile development. The video could provide additional context capable of substantiating the original claims, but at last check, it appears to have been removed from the web. See u/dirtyid, “This is reference to last segment of CCTV7 documentary from last winter …,” r/LessCredibleDefence (Reddit), 6 April 2024, https://www.reddit.com/r/LessCredibleDefence/comments/1bx1clu/comment/kyah3fn/; also see CCTV7’s “《砺剑》飞航铸剑” [“Forging the sword”: Aviation and missile development], posted 19 October 2023 by Bilibili, 26:22, archived 6 September 2025 at https://web.archive.org/web/20250906211957/https://www.bilibili.com/video/BV1634y1g7KR/. Title translated by AskSage.
31. “At Risk Students and the Study of Foreign Language in School,” International Dyslexia Association, accessed 9 January 2026, https://dyslexiaida.org/at-risk-students-and-the-study-of-foreign-language-in-school/.
32. Anne Trafton, “Cognitive Scientists Define Critical Period for Learning Language,” MIT News, 1 May 2018, https://news.mit.edu/2018/cognitive-scientists-define-critical-period-learning-language-0501.
33. For example, algorithmic bias refers to the propensity for AI to take on the attributes of its human programmers or discriminate based on training data, while errors like “hallucination” reflect its ability to fabricate (mis)information based on spurious statistical associations. See Ben Dickson, “Artificial Intelligence Has a Bias Problem, and It’s Our Fault,” PCMag, 14 June 2018, https://www.pcmag.com/news/artificial-intelligence-has-a-bias-problem-and-its-our-fault; Gary N. Smith, “An AI That Can ‘Write’ Is Feeding Delusions About How Smart Artificial Intelligence Really Is,” Salon, 1 January 2023, https://www.salon.com/2023/01/01/an-ai-that-can-write-is-feeding-delusions-about-how-smart-artificial-intelligence-really-is/.
34. However, CamoGPT does have some limited translation capabilities. Response to “Can you translate a Chinese-language article into English?,” CamoGPT, U.S. Army, 10 September 2025, https://camogpt.ai.army.mil/camogpt.
35. IBM, “Tokens and Tokenization,” IBM Watsonx, updated 20 November 2025, https://www.ibm.com/docs/en/watsonx/saas?topic=solutions-tokens. In natural language processing, tokens can be thought of as the units of data—groups of characters like syllables or words—that carry semantic meaning for a large language model (LLM). LLMs are subject to data processing limits on the number of tokens they can read and generate as meaningful output. Thus, in many cases, the more tokens that are consumed by LLM input, the fewer tokens the AI may be able to use as it produces output.

 

 

 

 

Back to Top

March-April 2026