AI Ethics: Algorithmic Determinism or Self-Determination? The GPDR Approach

Milossi, Maria; Alexandropoulou-Egyptiadou, Eugenia; Psannis, Kostas E.

doi:10.1109/access.2021.3072782

Cited by 18 publications

(2 citation statements)

References 26 publications

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“…This model is designed to protect the right to "informational self-determination," enabling individuals to either approve or decline the processing of their data after being adequately informed. Nevertheless, this notification process might lose its significance when the data subject lacks awareness or control over current or future data processing [151]. The Article 29 Working Party's guidelines regarding consent under Regulation 2016/679 stipulate three essential requirements that must be fulfilled:…”

Section: A Patients Consent For Datamentioning

confidence: 99%

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond

Nasir,

Khan,

Bai

2024

IEEE Access

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In the past decade, the deployment of deep learning (Artificial Intelligence (AI)) methods has become pervasive across a spectrum of real-world applications, often in safety-critical contexts. This comprehensive research article rigorously investigates the ethical dimensions intricately linked to the rapid evolution of AI technologies, with a particular focus on the healthcare domain. Delving deeply, it explores a multitude of facets including transparency, adept data management, human oversight, educational imperatives, and international collaboration within the realm of AI advancement. Central to this article is the proposition of a conscientious AI framework, meticulously crafted to accentuate values of transparency, equity, answerability, and a human-centric orientation. The second contribution of the article is the in-depth and thorough discussion of the limitations inherent to AI systems. It astutely identifies potential biases and the intricate challenges of navigating multifaceted contexts. Lastly, the article unequivocally accentuates the pressing need for globally standardized AI ethics principles and frameworks. Simultaneously, it aptly illustrates the adaptability of the ethical framework proposed herein, positioned skillfully to surmount emergent challenges.

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Section: A Patients Consent For Datamentioning

confidence: 99%

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond

Nasir,

Khan,

Bai

2024

IEEE Access

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“…In this sense, the moral algorithm is a basic principle and the bottom line is to realize the functional security of artificial intelligence. Algorithmic ethics, as an extension of technical ethics, is completely different from technical ethics in this respect [ 5 , 6 ]. Similar differences are not only unique to algorithmic ethics but also common in new age new things ethics.…”

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning in Ethical Design of Autonomous Driving Crash Algorithms

Xiao

2022

Computational Intelligence and Neuroscience

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The age of algorithms is here, and it is really changing people’s lives. More and more ethical problems related to algorithms have attracted people’s attention, but the related ethical research is still far behind the research of algorithms. As more intelligent algorithms emerge in an endless stream, there will also be a lot of algorithmic ethical issues. On the other hand, with the continuous improvement of the development level of the automobile industry, people have a stronger demand for the safety and stability of modern transportation, and more and more autonomous driving technology has been promoted and applied in the market. At present, most of the studies on the longitudinal collision avoidance system of vehicles use collision warning or emergency braking to avoid collision. However, when the vehicle is in a special situation such as high speed and slippery road, emergency steering is more effective. In order to further improve the vehicle safety and ethical algorithm design points, this article revolves around vehicle lateral active collision avoidance control method research, the collision avoidance decision-making, and path planning and collision avoidance transverse vehicle longitudinal motion control is analyzed, and based on automated driving simulation experiment, the tests carried out to verify the designed control strategy. The experimental results show that the proposed method not only has a good effect of preventing automatic driving collision but also can meet the requirements of algorithm ethics. This research can effectively guide the research of algorithmic ethics in the field of autonomous driving and effectively reduce the occurrence of traffic accidents.

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The looming threat of digital determinism and discrimination: Commentary on “The feudal glove of talent-selection decisions in sport – Strengthening the link between subjective and objective assessments” by Bar-Eli et al. (2023)

Morgulev

2024

Asian Journal of Sport and Exercise Psychology

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AI Ethics: Algorithmic Determinism or Self-Determination? The GPDR Approach

Cited by 18 publications

References 26 publications

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond

Application of Machine Learning in Ethical Design of Autonomous Driving Crash Algorithms

The looming threat of digital determinism and discrimination: Commentary on “The feudal glove of talent-selection decisions in sport – Strengthening the link between subjective and objective assessments” by Bar-Eli et al. (2023)

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