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1 Shimona Mohan & Dongyoun Cho, Gender and Lethal Autonomous Weapons Systems [1] (2024)

handle is hein.unl/gradllaus0001 and id is 1 raw text is: Male-Dominated Tech Gender Inequality in Diplomacy and A Wokc es:92% of 92 oiymkn:Women represent only 1/3 33% software professionals of diplomats participating in arms control and K worldwide are men. disarmament meetings such as CCW GGE on LAWS. Militarised Masculinities: Biased Systems: A 2021 review of 133 Al systems Women form a minority of military employed across sectors shows that 44% exhibit personnel in most countries, gender bias and 26% exhibit both gender and racial ranging from 0.3% to 20%. biases. ~2 Societal norms can be implicitly encoded in LAWS, which can result in biases at the systems' output stage based on gender, race, age, and other demographic qualifiers. Bias risks operational efficiency of Al systems and forms a pertinent issue in discussions around LAWS. Biases in Al are usually a result of anycombination of 3 oversights: 1 Incorrect, incomplete or unrepresentative datasets; 2 Machine learning models which introduce, reinforce or exacerbate bias in the data; and 3 Human developers and operators who may encode their own biases or overlook pre-existing biases in the data, processing or output of the systems. Evidence of bias in civilian applications of Al is easy to find. However, less research exists on how military applications of Al may reproduce inequalities. Potential consequences of gender biases in military Al systems like LAWS can be assessed from civilian xir of bias, such as: • Popular facial recognition technologies d certain faces due to their gender or race; iot detect • Women were not shortlisted for jobs due to Al-based recruitment tools passing over women candidates in favour of men; • Medical algorithms have been known to deny care to individuals based on gender, race and age. Gender biases in LAWS and related systems may in rmisjdentifyingwomen as non-human objects or miscategorizing civilian men as combatants. ;U1 There is no neutral category of a human, hence military applications of Al need to be transparent about how these systems respond to and reflect the diversity of humanity.

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