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The AI Carbon Footprint and Responsibilities of AI Scientists [PDF]

open access: yesPhilosophies, 2022
This article examines ethical implications of the growing AI carbon footprint, focusing on the fair distribution of prospective responsibilities among groups of involved actors. First, major groups of involved actors are identified, including AI scientists, AI industry, and AI infrastructure providers, from datacenters to electrical energy suppliers ...
openaire   +4 more sources

Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects

open access: yes, 2023
Many sets of ethics principles for responsible AI have been proposed to allay concerns about misuse and abuse of AI/ML systems. The underlying aspects of such sets of principles include privacy, accuracy, fairness, robustness, explainability, and ...
Sanderson, Conrad   +2 more
core   +1 more source

Algorithmic red teaming approaches to secure LLMs

open access: yesMachine Learning with Applications
Algorithmic red teaming for Large Language Models (LLMs) is a crucial practice for proactively ensuring their safety and robustness. This process involves using an LLM as an adversary to test the vulnerabilities of a target LLM, which is essential for ...
Shaurya Jauhari
doaj   +1 more source

Approaches for retraining sEMG classifiers for upper-limb prostheses

open access: yesFrontiers in Neurorobotics
IntroductionAbandonment rates for myoelectric upper limb prostheses can reach 44%, negatively affecting quality of life and increasing the risk of injury due to compensatory movements.
Tom Donnelly   +7 more
doaj   +1 more source

Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

open access: yes, 2023
Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system’s entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both from a technical ...
Díaz Rodríguez, Natalia   +15 more
core   +1 more source

Hyperosmotic stress induces PARP1‐mediated HPF1‐dependent mono(ADP‐ribosyl)ation

open access: yesFEBS Letters, EarlyView.
Sorbitol‐induced hyperosmotic stress rapidly induces reversible mono(ADP‐ribosyl)ation (MARylation) on PARP1 without the signs of genotoxic signaling. We show that PARP1 autoMARylation is HPF1 dependent and forms hydroxylamine‐resistant O‐glycosidic linkages.
Anna Georgina Kopasz   +11 more
wiley   +1 more source

Drivers and influence of social conformity on decision making in human-AI teams

open access: yesScientific Reports
Advances in AI are transforming decision making teams. A fundamental open question is whether AI agents elicit social conformity effects comparable to human peers.
Huixin Zhong   +5 more
doaj   +1 more source

AI testing, evaluation, verification and validation for accessibility: a comprehensive framework

open access: yesFrontiers in Digital Health
As artificial intelligence (AI) systems continue to remain prevalent in society, ensuring their accessibility for all users, including those with disabilities, is of great importance.
Gabriella Waters, Gabriella Waters
doaj   +1 more source

The ubiquitin ligase RNF115 is required for the clearance of damaged lysosomes

open access: yesFEBS Letters, EarlyView.
Upon lysosomal rupture, an E3 ubiquitin ligase RNF115 translocates from the cytosol to the damaged lysosomal membrane. Moreover, RNF115 depletion impairs the clearance of damaged lysosomes, identifying it as a key regulator of lysosomal quality control.
Sae Nakanaga   +3 more
wiley   +1 more source

Responsible AI for Text Classification: A Neutrosophic Approach Combining Classical Models and BERT [PDF]

open access: yesNeutrosophic Sets and Systems
Recent advances in natural language processing have seen remarkable improvements in text classification tasks, largely driven by transformer-based architecture such as BERT.
Nabil M. Abdel-Aziz   +2 more
doaj   +1 more source

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