Abstract This paper develops an account of trustworthy AI. Its central idea is that whether AIs are a matter they live up to their function-based obligations. We argue this serves advance the literature in couple important ways. First, it provide rationale for why range properties widely assumed scientific literature, as well policy, be required AI, such safety, justice, and explainability, (of...

in this paper a simple and effective expert system to predict random data fluctuation in short-term period is established. evaluation process includes introducing fourier series, markov chain model prediction and comparison (gray) combined with the model prediction gray- fourier- markov that the mixed results, to create an expert system predicted with artificial intelligence, made this model to...

Embedded artificial intelligence (AI) seamlessly integrates AI into everyday devices. By bringing closer to the data source, embedded empowers real-time decision making, enhanced efficiency, and new possibilities across diverse domains.

The reanimation of the pseudosciences physiognomy and phrenology at scale through computer vision machine learning is a matter urgent concern. This Article, which contributes to critical data studies, consumer protection law, biometric privacy anti-discrimination endeavors conceptualize problematize physiognomic artificial intelligence (AI) offer policy recommendations for state federal lawmake...

Abstract For their deployment in human societies to be safe, AI agents need aligned with value-laden cooperative life. One way of solving this “problem value alignment” is build moral machines. I argue that the goal building machines aims at wrong kind ideal, and instead, we an approach alignment takes seriously categorically different cognitive capabilities between agents, a condition call dee...

in distribution systems, in order to diminish power losses and keep voltage profiles within acceptable limits, network reconfiguration and capacitor placement are commonly used. in this paper, the hybrid shuffled frog leaping algorithm (hsfla) is used to optimize balanced and unbalanced radial distribution systems by means of a network reconfiguration and capacitor placement. high accuracy and ...