This paper introduces a collaborative, human-centered taxonomy of AI, algorithmic and automation harms. We argue that existing taxonomies, while valuable, can be narrow, unclear, typically cater to practitioners and government, and often overlook the needs of the wider public. Drawing on existing taxonomies and a large repository of documented incidents, we propose a taxonomy that is clear and understandable to a broad set of audiences, as well as being flexible, extensible, and interoperable. Through iterative refinement with topic experts and crowdsourced annotation testing, we propose a taxonomy that can serve as a powerful tool for civil society organisations, educators, policymakers, product teams and the general public. By fostering a greater understanding of the real-world harms of AI and related technologies, we aim to increase understanding, empower NGOs and individuals to identify and report violations, inform policy discussions, and encourage responsible technology development and deployment.

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 Is #AI Science or Engineering? AI combines science and engineering in order to build machines capable of intelligent behaviour. It brings together work from the fields of philosophy, psychology, and computer science, and contributes to and has drawn on brain science and linguistics. AI Science and Engineering is a transdisciplinary science and engineering of Technology Systems, Platforms, Machines, Computers, Computer-Controlled Robots, or Software Powerful to Interact Effectively, Sustainably and Intelligently with the World. AI Engineering is a field of research and practice that combines the principles of systems engineering, software engineering, computer science, and human-centered design to create AI systems in accordance with human needs for mission outcomes.

KUALA LUMPUR: Highways operator Prolintas has achieved another milestone by developing and integrating artificial intelligence (AI) and machine learning as part of their highway management. The highway concessionaire has been using the Smart Surveillance System (S3) and Prolintas Integrated Maintenance Escalations (Prime) which are based on smart technology system. This system upgrade has put Prolintas as the first in the country to utilise such advanced technology system in highway management operations. Prolintas group chief executive officer Datuk Mohammad Azlan Abdullah said the system upgrade was aimed to improve the level of highway efficiency. "By using S3, we will be able to do highway surface monitoring, faulty assets detection, road accidents, foreign object, stagnant water areas and animal presence. "Apart from that, it will also be able to do live video streaming (of the highway), real-time integrated notification and reporting.

Think of AI and you'll almost invariably be thinking of a cloud-based compute system where queries are captured at source and sent to the cloud for processing, after which the result of that processing is sent back to the source. But there's a different side to AI that's starting to gain more exposure, localised embedded AI. There's been a lot of talk over the past year about neural processors, especially in the smartphone arena, and we should only expect the buzz around these embedded AI platforms to increase. So what are we expecting these embedded AI systems to do, and how will they differ from the far more powerful cloud-based systems? We sat down with David Harold, VP marketing and communications Imagination Technologies, while at CES to talk embedded AI and the impact it will have on the coming years.

Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world's inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today? Some 979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists answered this question in a canvassing of experts conducted in the summer of 2018. The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. They spoke of the wide-ranging possibilities; that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. They said "smart" systems in communities, in vehicles, in buildings and utilities, on farms and in business processes will save time, money and lives and offer opportunities for individuals to enjoy a more-customized future. Many focused their optimistic remarks on health care and the many possible applications of AI in diagnosing and treating patients or helping senior citizens live fuller and healthier lives.

The potential of artificial intelligence to transform the workplace is no longer the stuff of science fiction. It's a today reality that companies--and especially their executive teams and Human Resources (HR) leaders--are meeting head-on. Gone are the days of installing technology systems that served as fixed tools over a fixed lifecycle.iStock Dynamic technology innovations including machine learning and artificial intelligence are already changing the way companies operate, and redefining the very concept of work in the process. And while major technology breakthroughs that fundamentally reshape the workplace have a history of driving net job gains and improved employee satisfaction over the long term, the path is often complicated by short-term concerns or wake-me-when-it's-over inertia.

I believe 2018 will be the year in which businesses of all sizes engage with the hype and get to grips with the difference between tech for tech's sake and understanding how it can be used to augment human capability. This is the year to overcome the tech fear.

The State Council has issued a guideline on developing artificial intelligence (AI), setting a goal of becoming a global innovation center in this field by 2030. The total output value of artificial intelligence industries should surpass 1 trillion yuan ($147.80 billion). A mature theory and technology system should be formed. Developing AI is a "complicated and systematic project" according to the guideline. An open and coordinated AI innovation system should be constructed to develop not only the technology, but also products and market.

"The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself." Anyone who shops online or uses a music streaming service will have experienced recommendations. Their accuracy can be surprising at first glance, but these recommendations aren't made by accident. They are based on sophisticated machine learning techniques, pattern analysis and automated decision making. Systems like these rely on a technology infrastructure that can import, analyse and interpret huge volumes of data and take appropriate action without the need for human intervention.

"The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself." Anyone who shops online or uses a music streaming service will have experienced recommendations. Their accuracy can be surprising at first glance, but these recommendations aren't made by accident. They are based on sophisticated machine learning techniques, pattern analysis and automated decision making. Systems like these rely on a technology infrastructure that can import, analyse and interpret huge volumes of data and take appropriate action without the need for human intervention.