Biometrics and the metaphysics of personal identity

Kind, Amy

doi:10.1049/bme2.12062

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…Besides, there is a legislative loophole in Annex 1 of the AI act as it does not cover im- Kind ((2021), p. 4) asks the reidentification question of what makes a person the same person over time. Psychological theorists, also known as psychological continuity theorists, go beyond focusing on an individual's memory to understand their psychology more comprehensively.…”

Section: Biometrics and Psychementioning

confidence: 99%

The Prohibited Artificial Intelligence Practice

Bulgakova

2023

Theor. and Pract. of Foren. Sci. and Crim.

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The research strives to provide a comprehensive understanding of the regulation of Artificial Intelligence (AI), known as the AI act of the European Union, with a specific focus on the regulatory challenges related to the prohibition of AI systems that deploy subliminal techniques. To achieve this, the author proposes the perspective of metaverse to enhance the user experience and biometric psychography to avoid reality eye-tracking-based models. However, the current AI act needs to be prepared to address biometrics, which merely repeats the GDPR, giving a hand to AI market growth. Regardless, the author offers four key contributions. Firstly, it shows up a course on the prohibition of AI systems contrasting to the pupillometry market that strive for an opposite course. Secondly, it clarifies the image of subliminal techniques beyond a person’s consciousness of Article 5 para 1 point (a) with reference to the ‘vulnerability’ urge as per point (b). Thirdly, the research compiles perspicuity of ‘psychological harm’ criterion through the assessment of case law practice. Finally, it proposes to fill the gaps in privacy especially when the AI system initially appears friendly but becomes tracking. To support this outcome, the manuscript refers to biometric psychography expanding the concept of biometric data for AI systems.

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Section: Biometrics and Psychementioning

confidence: 99%

The Prohibited Artificial Intelligence Practice

Bulgakova

2023

Theor. and Pract. of Foren. Sci. and Crim.

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“…The notion of biometric identity is considered not only by engineers but also in philosophical discourse. A recent study by Kind [ 9 ] listed the most pressing ones: privacy, bias, security in data collection, and adding new metaphysical issues concerning matters of personal identity.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application

Szczuko

Harasimiuk

Czyżewski

2022

Sensors

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An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.

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“…Dewasa ini, terobosan teknologi sedang berkembang sangat pesat untuk mempermudah segala aktivitas yang bermanfaat bagi manusia. Salah satunya adalah sistem pengenalan biometrik yang tentunya sangat mempermudah urusan seperti pengenalan identitas atau validasi identitas (Kind, 2023), tidak jarang perusahaan dan institusi lain yang 1410 Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), Vol. 10 No.…”

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Rancang Bangun Alat Pengenal Finger Vein Menggunakan Raspberry Pi dengan Metode Convolutional Neural Network (CNN)

Prasetio,

Jevandika,

Syauqy

2023

JTIIK

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Terobosan teknologi sistem pengenalan biometrik saat ini berkembang dengan pesat dan sangat mempermudah urusan seperti pengenalan identitas atau validasi identitas, serta tidak jarang perusahaan dan institusi lain yang umum menerapkan sistem pengenalan berbasis biometrik manusia seperti sidik jari, pola telapak tangan, wajah, ataupun iris mata. Sebuah sistem pengenalan biometrik memiliki kelebihan dan tentunya beberapa keterbatasan dalam hal performa dan kenyamanan. Pengenalan sidik jari dan telapak tangan mengharuskan pengguna untuk menyentuh permukaan sensor. Dengan cara ini, pengguna dapat merasa tidak nyaman dan risiko penyebaran virus atau bakteri sangat tinggi, juga akurasi pendeteksian dapat dipengaruhi oleh faktor-faktor seperti kulit berkeringat dan kering serta distorsi kulit. Oleh karena itu pada penelitian ini akan mengusung judul Rancang Bangun Alat Pengenal Finger Vein Menggunakan Raspberry Pi Dengan Metode Convolutional Neural Network (CNN). Penelitian ini menggunakan sistem berbasis Raspberry Pi 4 dengan bantuan IR LED dan webcam untuk proses akusisi data citra pembuluh darah jari, yang diharapkan mampu melakukan proses pengenalan Finger Vein lebih cepat, dan penggunaan metode Convolutional Neural Network yang sudah teruji untuk menghasilkan akurasi yang lebih baik dengan proses Deep Learning. Dari 30 data yang digunakan sebagai penguji sistem bersama perangkat lunak dan perangkat keras tertanam, akurasinya mencapai 96,66%. Abstract Breakthrough in biometric recognition system technology is currently growing rapidly and greatly facilitates matters such as identity recognition or identity validation, and it is not uncommon for companies and other institutions to implement human biometric-based recognition systems such as fingerprints, palm patterns, faces, or irises. A biometric recognition system has advantages and certainly some limitations in terms of performance and convenience. Fingerprint and palm recognition requires the user to touch the surface of the sensor. In this way, users can feel uncomfortable and the risk of spreading viruses or bacteria is very high, also the detection accuracy can be affected by factors such as sweaty and dry skin and skin distortion. Therefore, this study will carry the title Design a Finger Vein Recognition Tool Using Raspberry Pi with the Convolutional Neural Network (CNN) Method. This research uses a Raspberry Pi 4-based system with the help of IR LEDs and webcams for the acquisition process of finger blood vessel image data, which is expected to be able to carry out the Finger Vein recognition process faster, and the use of the proven Convolutional Neural Network method to produce better accuracy with the Deep Learning process. Of the 30 data used as system testers alongside embedded software and hardware, the accuracy reached 96.66%.

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Biometrics and the metaphysics of personal identity

Cited by 3 publications

References 13 publications

The Prohibited Artificial Intelligence Practice

The Prohibited Artificial Intelligence Practice

Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application

Rancang Bangun Alat Pengenal Finger Vein Menggunakan Raspberry Pi dengan Metode Convolutional Neural Network (CNN)

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