"Data is the new oil." Originally coined in 2006 by the British mathematician Clive Humby, this phrase is arguably more apt today than it was then, as smartphones rival automobiles for relevance and the technology giants know more about us than we would like to admit. Just as it does for the financial services industry, the hyper-digitization of the economy presents both opportunity and potential peril for financial regulators. On the upside, reams of information are newly within their reach, filled with signals about financial system risks that regulators spend their days trying to understand. The explosion of data sheds light on global money movement, economic trends, customer onboarding decisions, quality of loan underwriting, noncompliance with regulations, financial institutions' efforts to reach the underserved, and much more. Importantly, it also contains the answers to regulators' questions about the risks of new technology itself. Digitization of finance generates novel kinds of hazards and accelerates their development. Problems can flare up between scheduled regulatory examinations and can accumulate imperceptibly beneath the surface of information reflected in traditional reports. Thanks to digitization, regulators today have a chance to gather and analyze much more data and to see much of it in something close to real time. The potential for peril arises from the concern that the regulators' current technology framework lacks the capacity to synthesize the data. The irony is that this flood of information is too much for them to handle.
Asia's urban population has steadily increased over the last several years, bringing added environmental and infrastructure growing pains. Technology will be a key leveler to mitigate these issues and ensure that the region is well placed to capture the emerging opportunities. Already, communication networks serve as the backbone for smart grids conveying information as well as data transmission from the use of artificial intelligence (AI) and machine learning (ML). These technologies not only improve the overall quality of life for growing cities, but also overcome constraints on productivity. We've seen a plethora of examples where new tech has helped address these growing pains.
Over a million Indians move to the US each year, but finding a job can be a tough task. Priyanka Botny found herself in such a situation. Unwilling to give up, she decided on becoming an immigrant entrepreneur and started Playonomics -- an online experiential learning platform for employees to improve their emotional intelligence. Priyanka says often focusing on IT infrastructure takes away attention from employee wellbeing. "We help in bringing that intelligence to build emotional skills, along with digital transformation at organisations," Priyanka explains.
The goal of artificial intelligence (AI) is to imitate or outperform tasks that typically require human intelligence. Exciting as that might sound, there are several misconceptions about AI--especially when it comes to translating theory into practice. Unfortunately, these misconceptions are the result of years of misinformation, propaganda, and the influence of science fiction. Perhaps the most pervasive piece of misinformation--and one not without basis--is that AI is able to do anything a human can do. This comes with unrealistic expectations on what it can do as well as the accompanying fear that AI will lead to mass unemployment as low-skilled jobs are displaced by machines.
Technology has always been a double-edged sword. While it's been a major force for progress, it has also been abused and caused harm. From steam power to Fordism, history shows that technology is neither good nor bad – by itself. It can, of course, be both, depending on how it's used. Telecommunications, specifically the internet, and more recently AI, which is estimated to contribute more than €11 billion to the global economy by 2030, are no different.
The relevance of the video is that the browser identified the application being used by the IAI as Google Earth and, according to the OSC 2006 report, the Arabic-language caption reads Islamic Army in Iraq/The Military Engineering Unit – Preparations for Rocket Attack, the video was recorded in 5/1/2006, we provide, in Appendix A, a reproduction of the screenshot picture made available in the OSC report. Now, prior to the release of this video demonstration of the use of Google Earth to plan attacks, in accordance with the OSC 2006 report, in the OSC-monitored online forums, discussions took place on the use of Google Earth as a GEOINT tool for terrorist planning. On August 5, 2005 the user "Al-Illiktrony" posted a message to the Islamic Renewal Organization forum titled A Gift for the Mujahidin, a Program To Enable You to Watch Cities of the World Via Satellite, in this post the author dedicated Google Earth to the mujahidin brothers and to Shaykh Muhammad al-Mas'ari, the post was replied in the forum by "Al-Mushtaq al-Jannah" warning that Google programs retain complete information about their users. This is a relevant issue, however, there are two caveats, given the amount of Google Earth users, it may be difficult for Google to flag a jihadist using the functionality in time to prevent an attack plan, one possible solution would be for Google to flag computers based on searched websites and locations, for instance to flag computers that visit certain critical sites, but this is a problem when landmarks are used, furthermore, and this is the second caveat, one may not use one's own computer to produce the search or even mask the IP address. On October 3, 2005, as described in the OSC 2006 report, in a reply to a posting by Saddam Al-Arab on the Baghdad al-Rashid forum requesting the identification of a roughly sketched map, "Almuhannad" posted a link to a site that provided a free download of Google Earth, suggesting that the satellite imagery from Google's service could help identify the sketch.
This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital technologies, many individuals and institutions have articulated the need for a greater emphasis on ethics in digital technology. Yet as more groups embrace the concept of ethics, critical discourses have emerged questioning whose ethics are being centered, whether "ethics" is the appropriate frame for improving technology, and what it means to develop "ethical" technology in practice. This interdisciplinary issue takes up these questions, interrogating the relationships among ethics, technology, and society in action. This special issue engages with the normative and contested notions of ethics itself, how ethics has been integrated with technology across domains, and potential paths forward to support more just and egalitarian technology. Rather than starting from philosophical theories, the authors in this issue orient their articles around the real-world discourses and impacts of tech ethics--i.e., tech ethics in action.
AI is seen by many as an engine of productivity and economic growth. It can increase the efficiency with which things are done and vastly improve the decision-making process by analyzing large amounts of data. It can also spawn the creation of new products and services, markets, and industries, thereby boosting consumer demand and generating new revenue streams. However, AI may also have a highly disruptive effect on the economy and society. Some warn that it could lead to the creation of super firms – hubs of wealth and knowledge – that could have detrimental effects on the wider economy.
Petropoulos, Fotios, Apiletti, Daniele, Assimakopoulos, Vassilios, Babai, Mohamed Zied, Barrow, Devon K., Taieb, Souhaib Ben, Bergmeir, Christoph, Bessa, Ricardo J., Bijak, Jakub, Boylan, John E., Browell, Jethro, Carnevale, Claudio, Castle, Jennifer L., Cirillo, Pasquale, Clements, Michael P., Cordeiro, Clara, Oliveira, Fernando Luiz Cyrino, De Baets, Shari, Dokumentov, Alexander, Ellison, Joanne, Fiszeder, Piotr, Franses, Philip Hans, Frazier, David T., Gilliland, Michael, Gönül, M. Sinan, Goodwin, Paul, Grossi, Luigi, Grushka-Cockayne, Yael, Guidolin, Mariangela, Guidolin, Massimo, Gunter, Ulrich, Guo, Xiaojia, Guseo, Renato, Harvey, Nigel, Hendry, David F., Hollyman, Ross, Januschowski, Tim, Jeon, Jooyoung, Jose, Victor Richmond R., Kang, Yanfei, Koehler, Anne B., Kolassa, Stephan, Kourentzes, Nikolaos, Leva, Sonia, Li, Feng, Litsiou, Konstantia, Makridakis, Spyros, Martin, Gael M., Martinez, Andrew B., Meeran, Sheik, Modis, Theodore, Nikolopoulos, Konstantinos, Önkal, Dilek, Paccagnini, Alessia, Panagiotelis, Anastasios, Panapakidis, Ioannis, Pavía, Jose M., Pedio, Manuela, Pedregal, Diego J., Pinson, Pierre, Ramos, Patrícia, Rapach, David E., Reade, J. James, Rostami-Tabar, Bahman, Rubaszek, Michał, Sermpinis, Georgios, Shang, Han Lin, Spiliotis, Evangelos, Syntetos, Aris A., Talagala, Priyanga Dilini, Talagala, Thiyanga S., Tashman, Len, Thomakos, Dimitrios, Thorarinsdottir, Thordis, Todini, Ezio, Arenas, Juan Ramón Trapero, Wang, Xiaoqian, Winkler, Robert L., Yusupova, Alisa, Ziel, Florian
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.
AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner Why do we need a powerful man-machine superintelligence (digital superminds)? Humanity is no more able alone, without powerful machine intelligence, to solve the complex problems of modern complex world, as all sorts and types of global threats and risks to human health, rising unemployment, widening digital divides, youth disillusionment, and geopolitical fragmentation. What we need, it is a Real Superintelligence taking its superpower from the concept of reality, its noumena and phenomena, and deployed as a globally distributed human-machine superintelligence integrating billions of different human, artificial, and machine intelligences. Considering an accelerated change and fast space-time compression, the RSI Technology could be designed, developed, deployed and distributed as the fundamental general-purpose technology, integrating automated, machine, artificial, and natural human intelligences, within 5–7 years. There are several means by which science may achieve this breakthrough (and this is another reason for having confidence that the event will occur): - The development of computers that are "awake" and superhumanly intelligent.