The impact of Artificial Intelligence continues to be felt across industries. A McKinsey report after analysing some AI use cases stated that'the impact of artificial intelligence will most likely be substantial in marketing and sales as well as supply-chain management and manufacturing'. The same report argues that AI has the potential to create trillions of dollars of value across the economy if business leaders work to understand what it can and cannot do. Looking at this critically, one would wonder how Africa's manufacturing industries would be able to compete with other continents that are massively adding AI-powered tools and solutions to their production lines? China, for example, has more or less made artificial intelligence a major priority, investing heavily so as to ensure the country stays ahead.
Artificial Intelligence (AI) has become a trend that is here to stay at least in the foreseeable future. Many countries have started embracing this technology; notable among them is China. This article explores how China has harnessed AI in the fields of e-commerce, finance and health from a layman's perspective. AI has improved our lives in many ways, but there are still some controversial issues concerning its use. The first thing that comes to mind in the way China has been transformed by AI technology can be traced back to the year 2013.
The Foundation for the Defense of Democracies issues an alarming report about Beijing's expanding tentacles in international agencies; Eric Shawn has the Fox News exclusive. Two astronauts on Sunday made the first spacewalk outside China's new orbital station to set up cameras and other equipment using a 15-meter-long (50-foot-long) robotic arm. Liu Boming and Tang Hongbo were shown by state TV climbing out of the airlock as Earth rolled past below them. The third crew member, commander Nie Haisheng, stayed inside. Liu and Tang spent nearly seven hours outside the station, the Chinese space agency said.
And while algorithms can catch problematic content, they can promote it, too, because they've been designed to boost user engagement and respond to how people react. The systems could be used to amplify scams, fuel harassment campaigns or spit out long pieces of text, such as fake news stories, that would appear to have been written by a human hand. They could also be abused for censorship: A university research team in China, where the government bans anything it deems "subversive" speech, said in April that its text-censoring AI could filter out "sensitive information from online news media" with more than 90 percent accuracy.
The digital media, identified as computational propaganda provides a pathway for propaganda to expand its reach without limit. State-backed propaganda aims to shape the audiences' cognition toward entities in favor of a certain political party or authority. Furthermore, it has become part of modern information warfare used in order to gain an advantage over opponents. Most of the current studies focus on using machine learning, quantitative, and qualitative methods to distinguish if a certain piece of information on social media is propaganda. Mainly conducted on English content, but very little research addresses Chinese Mandarin content. From propaganda detection, we want to go one step further to provide more fine-grained information on propaganda techniques that are applied. In this research, we aim to bridge the information gap by providing a multi-labeled propaganda techniques dataset in Mandarin based on a state-backed information operation dataset provided by Twitter. In addition to presenting the dataset, we apply a multi-label text classification using fine-tuned BERT. Potentially this could help future research in detecting state-backed propaganda online especially in a cross-lingual context and cross platforms identity consolidation.
A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in network analysis. Despite the classical spectral clustering and statistical inference methods, we notice a significant development of deep learning techniques for community detection in recent years with their advantages in handling high dimensional network data. Hence, a comprehensive overview of community detection's latest progress through deep learning is timely to both academics and practitioners. This survey devises and proposes a new taxonomy covering different categories of the state-of-the-art methods, including deep learning-based models upon deep neural networks, deep nonnegative matrix factorization and deep sparse filtering. The main category, i.e., deep neural networks, is further divided into convolutional networks, graph attention networks, generative adversarial networks and autoencoders. The survey also summarizes the popular benchmark data sets, model evaluation metrics, and open-source implementations to address experimentation settings. We then discuss the practical applications of community detection in various domains and point to implementation scenarios. Finally, we outline future directions by suggesting challenging topics in this fast-growing deep learning field.
This paper aims to provide an overview of the ethical concerns in artificial intelligence (AI) and the framework that is needed to mitigate those risks, and to suggest a practical path to ensure the development and use of AI at the United Nations (UN) aligns with our ethical values. The overview discusses how AI is an increasingly powerful tool with potential for good, albeit one with a high risk of negative side-effects that go against fundamental human rights and UN values. It explains the need for ethical principles for AI aligned with principles for data governance, as data and AI are tightly interwoven. It explores different ethical frameworks that exist and tools such as assessment lists. It recommends that the UN develop a framework consisting of ethical principles, architectural standards, assessment methods, tools and methodologies, and a policy to govern the implementation and adherence to this framework, accompanied by an education program for staff.