Algorithmic Bias and the Pastoral: Gender Misrecognition in Light of Natural Knowledge

2020 ◽  
Vol 40 (2) ◽  
pp. 73-92
Author(s):  
Bradley J. Nelson
Keyword(s):  
Natural Knowledge ◽  
Algorithmic Bias

IMPLEMENTASI ALGORITMA LEVENSTEIN DALAM MENGKOMPRESI TEKS PADA APLIKASI RANGKUMAN PENGETAHUAN ALAM LENGKAP

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Winda Winda ◽  
Taronisokhi Zebua
Keyword(s):  
Compression Ratio ◽  
Mobile Application ◽  
Storage Space ◽  
Compression Technique ◽  
The Public ◽  
Natural Knowledge ◽  
Database Size ◽  
Text Database

The size of the data that is owned by an application today is very influential on the amount of space in the memory needed one of which is a mobile-based application. One mobile application that is widely used by students and the public at this time is the Complete Natural Knowledge Summary (Rangkuman Pengetahuan Alam Lengkap or RPAL) application. The RPAL application requires a large amount of material storage space in the mobile memory after it has been installed, so it can cause this application to be ineffective (slow). Compression of data can be used as a solution to reduce the size of the data so as to minimize the need for space in memory. The levestein algorithm is a compression technique algorithm that can be used to compress material stored in the RPAL application database, so that the database size is small. This study describes how to compress the RPAL application database records, so as to minimize the space needed on memory. Based on tests conducted on 128 characters of data (200 bits), the compression results obtained of 136 bits (17 characters) with a compression ratio is 68% and redundancy is 32%.Keywords: compression, levestein, aplication, RPAL, text, database, mobile

Assessing and addressing algorithmic bias in practice

interactions ◽  
2018 ◽  
Vol 25 (6) ◽  
pp. 58-63 ◽  
Author(s):  
Henriette Cramer ◽  
Jean Garcia-Gathright ◽  
Aaron Springer ◽  
Sravana Reddy
Keyword(s):  
Algorithmic Bias

What are the risks of Virtual Reality data? Learning Analytics, Algorithmic Bias and a Fantasy of Perfect Data

2021 ◽  
pp. 146144482110127
Author(s):  
Marcus Carter ◽  
Ben Egliston
Keyword(s):  
Virtual Reality ◽  
Learning Process ◽  
Learning Analytics ◽  
Soft Skills ◽  
Education Technology ◽  
Skills Training ◽  
Emerging Technology ◽  
Critical Issues ◽  
Vr Training ◽  
Algorithmic Bias

Virtual reality (VR) is an emerging technology with the potential to extract significantly more data about learners and the learning process. In this article, we present an analysis of how VR education technology companies frame, use and analyse this data. We found both an expansion and acceleration of what data are being collected about learners and how these data are being mobilised in potentially discriminatory and problematic ways. Beyond providing evidence for how VR represents an intensification of the datafication of education, we discuss three interrelated critical issues that are specific to VR: the fantasy that VR data is ‘perfect’, the datafication of soft-skills training, and the commercialisation and commodification of VR data. In the context of the issues identified, we caution the unregulated and uncritical application of learning analytics to the data that are collected from VR training.

Experimentalists in the Republic of Letters

2003 ◽  
Vol 16 (1-2) ◽  
pp. 89-120 ◽  
Author(s):  
H. Otto Sibum
Keyword(s):  
Scientific Revolution ◽  
Formative Period ◽  
Republic Of Letters ◽  
Experimental Knowledge ◽  
Natural Knowledge ◽  
Structural Problems ◽  
The Social ◽  
The Republic ◽  
Academic Recognition ◽  
Electro Magnetic

ArgumentWithin the Republic of Letters the art of experiment led to immense reorientation and an extensive redrawing of the enlightened map of natural knowledge. This paper will investigate the formative period of the exact sciences from the late eighteenth to the nineteenth century when the persona of the experimentalist as a scientific expert was shaped. The paper focuses on Moritz Hermann Jacobi’s experimental knowledge derived from his modeling of an electro-magnetic self-acting machine and the social and epistemological problems of its integration into traditional academic life. His struggle to achieve academic recognition and credibility for his experimental work reflects not just his individual quandary, but important structural problems of the historical development of experimental knowledge traditions and science in what has been called the “second scientific revolution.”

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