A critical approach to Machine Learning forecast capabilities: creating a predictive biography in the age of the Internet of Behaviour (IoB)

IF 0.2 0 HUMANITIES, MULTIDISCIPLINARY Artnodes Pub Date : 2023-01-15 DOI:10.7238/artnodes.v0i31.405249
Diego Díaz, Clara Boj
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引用次数: 1

Abstract

Based on the notion of the Datacene, understood as the time when data directly affects the social, cultural, economic, political, and even affective structures of the present, in this article we propose how Big Data and Artificial Intelligence give rise to the Internet of Behaviour: a new technological paradigm that has incredible potential to forecast and induce human behaviour. Since ancient times, humans have wanted to predict and alter the future, but in the last ten years, this wish has begun to become a reality due to great advances in the field of social engineering, raising serious doubts regarding social control and the loss of freedom. In this context of analysis, we present two projects developed within the framework of Art, Science, Technology and Society. Data Biography shows the enormous number of digital traces that we generate daily and uses them to compose a person’s biography, composed of 365 printed books. Machine Biography, for its part, investigates how current artificial intelligence techniques can predict and induce future human behaviour, for which we have used various forecast and generative models trained with data from our own digital activity, in order to generate another set of books with our foreseeable activity for the year 2050. Both projects invite us to consider from a critical perspective the present and future of the social transformations produced by Big Data and AI.
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机器学习预测能力的关键方法:在行为互联网(IoB)时代创建预测传记
基于数据时代的概念,即数据直接影响当前社会、文化、经济、政治甚至情感结构的时代,在本文中,我们提出了大数据和人工智能如何产生行为互联网:一种新的技术范式,具有预测和诱导人类行为的惊人潜力。自古以来,人类就想预测和改变未来,但在过去的十年里,由于社会工程领域的巨大进步,这一愿望开始成为现实,引发了人们对社会控制和自由丧失的严重怀疑。在这一分析背景下,我们介绍了在艺术、科学、技术和社会框架内开发的两个项目。数据传记显示了我们每天生成的大量数字痕迹,并用它们来撰写一个人的传记,由365本印刷书籍组成。就《机器传记》而言,它研究了当前的人工智能技术如何预测和诱导未来的人类行为,为此,我们使用了各种预测和生成模型,这些模型是用我们自己的数字活动数据训练的,目的是为2050年的可预见活动生成另一套书籍。这两个项目都邀请我们从批判性的角度来思考大数据和人工智能带来的社会变革的现在和未来。
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来源期刊
Artnodes
Artnodes HUMANITIES, MULTIDISCIPLINARY-
CiteScore
0.70
自引率
0.00%
发文量
26
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