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AI Weekly: UN recommendations point to need for AI ethics guidelines


"The world needs rules for artificial intelligence to benefit humanity. The recommendation[s] on the ethics of AI is a major answer," UNESCO chief …

The 9 Principles of Ethical AI in Healthcare Industry


It is noticed that AI systems are not neutral and not providing valid outcomes. AI in Healthcare can raise ethical issues and can harm patients by not giving intended outcomes. Therefore it is necessary to use Ethical AI in the health industry. Akira AI provides Ethical AI systems that are taking care of ethical issues and values. The 9 principles that are responsible for ethical AI in healthcare and provide a framework to help technologists while designing, developing, or maintaining systems.

China's Military Has a New Enemy (No, Not America)


One word: AI – Many of the world's leaders in the field of science and technology, including the late Stephen Hawking, Telsa founder Elon Musk, Apple co-founder Steve Wozniak and Microsoft founder Bill Gates, have all expressed concern in recent years over the risks of artificial intelligence (AI) – most notably its potential use in autonomous weapons. Along with many in academia and human rights groups, the science and tech visionaries have warned that in the wrong hands there is a serious danger posed by AI. One concern is that these weapons could be designed to be extremely difficult to simply "turn off," as the Future of Life Institute noted in its report on the development of autonomous weapon platforms. That could result in a scenario straight out of science fiction where humans lose control of their dangerous creations. While it may not mean a world-ending scenario presented in The Terminator, even losing control of a few AI weapons temporarily could result in unnecessary mass causalities or worse.

AI must have its own goals to be truly intelligent


Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. Is it the capacity to solve complicated mathematical problems at very fast speeds? The power to beat world champions in chess and go? The ability to detect thousands of different objects in images? Those are all manifestations of intelligence. And thanks to advances in artificial intelligence, we have been able to replicate them in computers, to different degrees of success.

INSPIRE-5Gplus insights on TinyML for IoT presented at MLIS 2021


At the 3rd International Conference on Machine Learning and Intelligent Systems (MLIS 2021), which was held online from 8th to 11th November 2021, Dr. Ramón Sánchez Iborra from INSPIRE-5Gplus partner University of Murcia gave an invited talk on the latest insights of the project in the area of Tiny Machine Learning (TinyML). TinyML is an embedded software technology that integrates reduced and optimized machine learning applications for making computing at the edge less expensive and more effective. The talk entitled "TinyML: A groundbreaking shift for the Internet of Things" explored how the dawn of the TinyML paradigm has brought a new wave of capabilities to new and already deployed Internet of Things (IoT) infrastructures. Concretely, TinyML permits to embed powerful ML mechanisms within resource-limited end-devices, hence evolving these elements into truly intelligent units. Besides, the conjunction of TinyML and edge-computing architectures paves the way for the development of distributed-intelligence systems.

Top 5 techniques for Explainable AI


Imagine you are a medical professional and you are using AI for stroke prediction. The AI has predicted stroke for one of your patients. When you will tell this to your patient, he is going to panic. There are two obvious questions, which he will ask.

La veille de la cybersécurité


Artificial intelligence is present in everyday life, from booking flights and applying for loans to steering driverless cars. It is also used in specialized fields such as cancer screening or to help create inclusive environments for the disabled. According to UNESCO, AI is also supporting the decision-making of governments and the private sector, as well as helping combat global problems such as climate change and world hunger. However, the agency warns that the technology'is bringing unprecedented challenges'. "We see increased gender and ethnic bias, significant threats to privacy, dignity and agency, dangers of mass surveillance, and increased use of unreliable AI technologies in law enforcement, to name a few. Until now, there were no universal standards to provide an answer to these issues", UNESCO explained in a statement.

5 Best Machine Learning & AI Books of All Time


The world of AI can be intimidating due to the terminology and different machine learning algorithms that are available. After having read over 50 of the most highly recommended books on machine learning, I have compiled my personal list of must read books. The books that were chosen are based on the types of ideas that are introduced, and how well different concepts such as deep learning, reinforcement learning, and genetic algorithms are presented. Most importantly the list is based on the books that best pave the path forward for futurists and researchers towards building provably responsible, and explainable AI. "Life 3.0" has an ambitious goal and that is to explore the possibilities of of how we will co-exist with AI in the future. Artificial General Intelligence (AGI) is the eventual and inevitable consequence of the intelligence explosion argument made by British mathematician Irving Good back in 1965.

Future Of AI In Healthcare Industry


Robot-assisted surgery is considered "minimally invasive" so patients won't need to heal from large incisions. Via artificial intelligence, robots can use data from past operations to inform new surgical techniques. Automated surgery is also fast becoming a ubiquitous reality. Virtual nurses will be available 24/7, they can answer the questions, monitor patients and provide quick answers. Virtual nurse assistants can even provide wellness checks through voice and AI.