Hi readers! Welcome back to our blog, this week we will be discussing our final topic which is “Military”. Today, I will be discussing how Artificial Intelligence is used to develop Facial Recognition in the military. Facial recognition technology analyses images in a digitally to identify, verify, or categorise them according to their purpose (Milossi, M. 2021). In current years, it has become an emerging technology that most of us are familiar with due to our everyday smartphone usage. Many smartphones have replaced passwords with ‘Face ID’ when unlocking your phone, downloading apps, or making payments directly from your phone. Instead of entering your password, a quick glace at your phone is enough for your smartphone to recognise your face through cutting edge technology and Artificial Intelligence (AI) (Ecott, S, 2017). Image Source: https://blog.dormakaba.com/what-is-facial-recognition-and-how-does-it-work/ (Faresse, M. 2020) Facial recognition has led to many more advancements other than just convenience and security within our smartphones. The military is currently using facial recognition to identify individuals on the battlefield, but existing technology typically relies on standard cameras which are prone to error. To improve accuracy, the US military aims to create long-range facial recognition which can detect faces even in the dark. They're investing over $4.5 million in developing facial recognition technology that uses infrared cameras to detect the heat radiated by your face (Gershgorn, D, 2020). Bodies with standard earth temperatures primarily radiate between 3 µm and 15 µm. Due to the weak radiation emitted by the sun, moon, stars, and other artificial sources, the thermal radiation generated by objects over 3µm dominates the radiation reflected by these sources in this spectral range (Elhefnawy, A. N). AI can then process the pattern of the heat being emitted to identify specific people (Gershgorn, D, 2020). This device is expected to provide high optical performance and mechanical compactness. It should have as small a dimension and weight as possible from a mechanical standpoint in effort to reduce manufacturing and production costs (Elhefnawy, A.N). This technology would work in low-light conditions and across vast distances which can significantly improve the military’s capability to detect individuals. (Gershgorn, D, 2020). Image Source: https://emerj.com/ai-sector-overviews/facial-recognition-in-the-military-current-applications/ (Abadicio, M. 2020) Although Facial Recognition has many capabilities, there are many ethical issues surrounding the topic. Facial Recognition uses AI but it is only as smart as the data used to train it (Lohr, S. 2018). The issue of determining which photographs in datasets will be used to train facial recognition systems has sparked lot of controversy, particularly concerning image source consent and diversity (Selinger, E., & Leong, B. 2021). Inaccuracy is more likely to occur within darker skin tones, demonstrating how real-world bias can infiltrate AI. If the data in the system used to train the AI is contains predominantly white male images, then the AI will be less accurate at detecting black women. According to a research study, one frequently used facial-recognition data set was assessed to contain more than 75% male images and more than 80% white images (Lohr, S. 2018). Many critics have pointed out that not everyone is equally vulnerable to being damaged by false identifications, and not everyone feels the same sense of uneasiness while using or being subjected to a facial recognition system (Selinger, E., & Leong, B. 2021). Image Source: https://www.eff.org/deeplinks/2019/12/activists-worldwide-face-against-face-recognition-2019-year-review (Rodriguez, K. 2019) Overall, Facial recognition has both benefits and risks but if used correctly, Artificial Intelligence it can extensively improve accuracy when identifying individuals on the battlefield. Aside from facial recognition, AI factors into many other aspects of the military which we will later be discussing this week so stay tuned for that!
Reference List Ecott, S. (2017). iPhone X: The end of privacy?. New Media & Digital Culture MA, University of Amsterdam. Elhefnawy, A. N. Refractive IR Objective Optical Design Operating in LWIR band For Military Observation Applications. Engpaper Journal. Gershgorn, D. (2020). The Military Is Building Long-Range Facial Recognition That Works in the Dark. Available at: https://onezero.medium.com/the-military-is-building-long-range-facial-recognition-that-works-in-the-dark-4f752fa713e6 [Accessed 28 March 2022] Lohr, S. (2018). Facial recognition is accurate, if you're a white guy. In Ethics of Data and Analytics (pp. 143-147). Auerbach Publications. Milossi, M. (2021, September). Remote biometric identification systems and ethical challenges: The case of facial recognition. In 2021 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) (pp. 1-6). IEEE. Selinger, E., & Leong, B. (2021). The ethics of facial recognition technology. Forthcoming in The Oxford Handbook of Digital Ethics ed. Carissa Véliz.
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