隐藏的世界

Intech Pub Date : 2020-12-01 DOI:10.2307/j.ctv39x8cr.5
J. Rosenbaum
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引用次数: 1

摘要

这个艺术项目通过训练机器生成基于希腊和罗马雕像的艺术作品来审视非二元和跨性别身份。雕像在本质上是二元性的,它吸引了男性和女性气质的巅峰概念,但是我们这些介于两者之间的人,跨性别者,不符合性别的人,非二元性的人以及双性人呢?图像识别算法很难将那些不属于二元性别的人、那些不被认为是顺性别的人、以及那些以中性或颠覆性方式呈现的人进行分类。随着图像识别变得越来越普遍,我们需要为每个不符合仅有的两个盒子中的一个的人提供一个过去和一个未来。我们需要开放分类,允许人们自我认同,或者抛弃机械地将人们划分为性别的概念。作为一个空间装置,《隐藏的世界》还探索了互动增强现实身体在物理世界和数字世界之间的空间中的体现。我使用了一个分类器和一些由机器生成的刻意抽象的人物作品,来探索在这个过程中,性别被分配到哪里,当你没有被整齐地分类时是什么样子,以及当性别被错误划分时的脱节感。生成的字幕围绕着性别翻转,随着人物的分解,每一部分都提交给叙事作者,你会看到一组不同的代词,你所看到的和你所听到的之间脱节了。我将探讨我们对古典艺术的假设;它可以告诉我们如何代表未来的性别少数群体,以及艺术如何说明这些重要机器学习系统训练中存在的差距。
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Hidden Worlds
This art project examines non-binary and transgender identity through training machines to generate art based on Greek and Roman statuary. The statuary is binary in nature and appeals to the concept of pinnacles of masculinity and femininity but what of those of us who fall between, what of transgender bodies, gender non-conforming and non-binary bodies and intersex bodies?  Image recognition algorithms have a difficult time classifying people who fall outside the binary, those who don’t pass as cisgender and those who present in neutral or subversive ways. As image recognition becomes more prevalent, we need to have a past and a future for everyone who doesn’t fit neatly into one of the only two boxes on offer. We need to open up the categories, allow people to self-identify or to scrap the concept of gendering people mechanically all together. As a spatial installation, Hidden Worlds also explores the embodiment of interactive augmented reality bodies in the space between physical and digital worlds. I have worked with a classifier and some deliberately abstract figure works, generated by machine, to explore where gender is assigned in the process and what it looks like when you aren’t neatly classified, and the disconnect that is felt when misgendered. The generated captions have flipped around gender and as the figure resolves and each section is submitted to the narrative writer you see a different set of pronouns, a disconnection between what you see and what you hear. I will explore the assumptions we make about classical art; the way it can inform how we represent gender minorities going forward and how art can illustrate the gaps that exist in the training of these important machine learning systems.
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