Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems

King, Owen C.

doi:10.1007/978-3-030-01800-9_14

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…Namun dengan segala hormat, kita dapat mengatakan bahwa teknik ini sekadar merupakan "pertanggungjawaban syarat" (modular responsibility) dan bukan "pertanggungjawaban dasariah" (ingrained responsibility). Godaan untuk lebih condong ke arah pertanggungjawaban modular sangat kuat sehingga mengalahkan pertanggungjawaban dasariah yang mestinya wajib diupayakan (King, 2019).…”

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Epistemologi Kecerdasan Buatan (Ai) Dan Pentingnya Ilmu Etika Dalam Pendidikan Interdisipliner

Pabubung¹

2021

JFI

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Artificial intelligence (AI) is an “umbrella term” used to describe simulations carried out by machines or devices, which are connected to an ocean of data, which resembles human intelligence. There is no doubt that AI has had a positive impact on many aspects of human life: economy, education, government, defense, and security. However, AI is like two sides of a coin which also has negative impacts. The multidimensional impacts caused by AI lead to a question about how to keep pace with AI progress while staying through the desired path. To answer this question, philosophy always begins with an epistemological analysis. By departing from facts and epistemological analysis about AI, the author came to believe in the importance of the role of interdisciplinary education. By using qualitative methods through literature analysis on AI as a material object, and philosophy, especially epistemology as a formal object, this essay offers the importance of AI and Ethics as a compounded lecture material in the era and disruption of AI. As a time-responsive educational institution, every university needs to consider the necessity for lecture materials on the basics of AI and Ethics for every student.

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Section: Hasil Dan Pembahasanunclassified

Epistemologi Kecerdasan Buatan (Ai) Dan Pentingnya Ilmu Etika Dalam Pendidikan Interdisipliner

Pabubung¹

2021

JFI

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“…Presumptuousness has been characterized this way byKing (2019), in the context of ethical issues in the development of computerized image recognition systems.5 Should we consider this as an infringement of the person's autonomy? It is difficult to say a little bit about autonomy without saying a lot.…”

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Presumptuous aim attribution, conformity, and the ethics of artificial social cognition

King

2019

Ethics Inf Technol

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Imagine you are casually browsing an online bookstore, looking for an interesting novel. Suppose the store predicts you will want to buy a particular novel: the one most chosen by people of your same age, gender, location, and occupational status. The store recommends the book, it appeals to you, and so you choose it. Central to this scenario is an automated prediction of what you desire. This article raises moral concerns about such predictions. More generally, this article examines the ethics of artificial social cognition—the ethical dimensions of attribution of mental states to humans by artificial systems. The focus is presumptuous aim attributions, which are defined here as aim attributions based crucially on the premise that the person in question will have aims like superficially similar people. Several everyday examples demonstrate that this sort of presumptuousness is already a familiar moral concern. The scope of this moral concern is extended by new technologies. In particular, recommender systems based on collaborative filtering are now commonly used to automatically recommend products and information to humans. Examination of these systems demonstrates that they naturally attribute aims presumptuously. This article presents two reservations about the widespread adoption of such systems. First, the severity of our antecedent moral concern about presumptuousness increases when aim attribution processes are automated and accelerated. Second, a foreseeable consequence of reliance on these systems is an unwarranted inducement of interpersonal conformity.

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Design and Optimization of Image Recognition and Classification Algorithm Based on Machine Learning

Dan,

2023

Learning and Analytics in Intelligent Systems

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Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems

Cited by 6 publications

References 15 publications

Epistemologi Kecerdasan Buatan (Ai) Dan Pentingnya Ilmu Etika Dalam Pendidikan Interdisipliner

Epistemologi Kecerdasan Buatan (Ai) Dan Pentingnya Ilmu Etika Dalam Pendidikan Interdisipliner

Presumptuous aim attribution, conformity, and the ethics of artificial social cognition

Design and Optimization of Image Recognition and Classification Algorithm Based on Machine Learning

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