AI for Good: Paths Forward
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A Comprehensive Workplace Environment Based on a Deep
International Journal on Advances in Software, vol 11 no 3 & 4, year 2018, http://www.iariajournals.org/software/ 358 A Comprehensive Workplace Environment based on a Deep Learning Architecture for Cognitive Systems Using a multi-tier layout comprising various cognitive channels, reflexes and reasoning Thorsten Gressling Veronika Thurner Munich University of Applied Sciences ARS Computer und Consulting GmbH Department of Computer Science and Mathematics Munich, Germany Munich, Germany e-mail: [email protected] e-mail: [email protected] Abstract—Many technical work places, such as laboratories or All these settings share a number of commonalities. For test beds, are the setting for well-defined processes requiring both one thing, within each of these working settings a human being high precision and extensive documentation, to ensure accuracy interacts extensively with technical devices, such as measuring and support accountability that often is required by law, science, instruments or sensors. For another thing, processing follows or both. In this type of scenario, it is desirable to delegate certain a well-defined routine, or even precisely specified interaction routine tasks, such as documentation or preparatory next steps, to protocols. Finally, to ensure that results are reproducible, some sort of automated assistant, in order to increase precision and reduce the required amount of manual labor in one fell the different steps and achieved results usually have to be swoop. At the same time, this automated assistant should be able documented extensively and in a precise way. to interact adequately with the human worker, to ensure that Especially in scenarios that execute a well-defined series of the human worker receives exactly the kind of support that is actions, it is desirable to delegate certain routine tasks, such required in a certain context. -
Build Your Trust Advantage, Leadership in the Era of Data
Global C-suite Study 20th Edition Build Your Trust Advantage Leadership in the era of data and AI everywhere This report is IBM’s fourth Global C-suite Study and the 20th Edition in the ongoing IBM CxO Study series developed by the IBM Institute for Business Value (IBV). We have now collected data and insights from more than 50,000 interviews dating back to 2003. This report was authored in collaboration with leading academics, futurists, and technology visionaries. In this report, we present our key findings of CxO insights, experiences, and sentiments based on analysis as described in the research methodology on page 44. Build Your Trust Advantage | 1 Build Your Trust Advantage Leadership in the era of data and AI everywhere Global C-suite Study 20th Edition Our latest study draws on input from 13,484 respondents across 6 C-suite roles, 20 industries, and 98 countries. 2,131 2,105 2,118 2,924 2,107 2,099 Chief Chief Chief Chief Chief Chief Executive Financial Human Information Marketing Operations Officers Officers Resources Officers Officers Officers Officers 3,363 Europe 1,910 Greater China 3,755 North America 858 Japan 915 Middle East and Africa 1,750 Asia Pacific 933 Latin America 2 | Global C-suite Study Table of contents Executive summary 3 Introduction 4 Chapter 1 Customers: How to win in the trust economy 8 Action guide 19 Chapter 2 Enterprises: How to build the human-tech partnership 20 Action guide 31 Chapter 3 Ecosystems: How to share data in the platform era 32 Action guide 41 Conclusion: Return on trust 42 Acknowledgments 43 Related IBV studies 43 Research methodology 44 Notes and sources 45 Build Your Trust Advantage | 3 Executive summary More than 13,000 C-suite executives worldwide their data scientists, to uncover insights from data. -
A.I. Technologies Applied to Naval CAD/CAM/CAE
A.I. Technologies Applied to Naval CAD/CAM/CAE Jesus A. Muñoz Herrero, SENER, Madrid/Spain, [email protected] Rodrigo Perez Fernandez, SENER, Madrid/Spain, [email protected] Abstract Artificial Intelligence is one of the most enabling technologies of digital transformation in the industry, but it is also one of the technologies that most rapidly spreads in our daily activity. Increasingly, elements and devices that integrate artificial intelligence features, appear in our everyday lives. These characteristics are different, depending on the devices that integrate them, or the aim they pursue. The methods and processes that are carried out in Marine Engineering cannot be left out of this technology, but the peculiarities of the profession and the people that take part in it must be taken into account. There are many aspects in which artificial intelligence can be applied in the field of our profession. The management and access to all the information necessary for the correct and efficient execution of a naval project is one of the aspects where this technology can have a very positive impact. Access all the rules, rules, design guides, good practices, lessons learned, etc., in a fast and intelligent way, understanding the natural language of the people, identifying the most appropriate to the process that is being carried out and above all. Learning as we go through the design, is one of the characteristics that will increase the application of this technology in the professional field. This article will describe the evolution of this technology and the current situation of it in the different areas of application. -
Ilearn Goals
Combining AI and collective intelligence to create a GPS for knowledge CRI Paris We experiment at frontiers of learning, life and digital From babies to lifelong learning LMD students Learning by doing Interdisciplinarity Sustainable Development goals A changing job market Too much! Fake news Recruting for skills on the digital job market Can we reinvent learning with artificial intelligence? What can you (almost) do with AI today? Deep Learning Classification Generation Who are these persons? www.thispersondoesnotexist.com Based on GAN (Generative Adversarial Networks) A.I. image generation From text to image From text to image Text generation Automatic Q&A generation from Wikipedia Debating with A.I. February 12th, 2019 IBM Project Debater vs. World Debating Champion Motion: “We should subsidise preschool” ● 15 mins to prepare arguments ● 4-minute opening statement ● 4-minute rebuttal ● 2-minute summary Predictive tools Pneumonia detection from thorax radiographies (2017) Deepfake A.I. lip reading Conversational interfaces May 2018 Google Duplex iLearn goals Map all learning resources available on the Internet Build learning profiles of our users Provide them maps of their own learnings Match learners with adapted resources Match learners with mentors or co-learners iLearn Knowledge maps + = + Collective Artificial intelligence intelligence Learning groups iLearn iLearn Tags an online Users improve document as a qualification Concepts extraction useful learning (concepts and resource difficulty) Artificial Collective Intelligence Intelligence -
United Nations Activities on Artificial Intelligence (AI) 2018
United Nations Activities on Artifi cial Intelligence (AI) United Nations Activities on Artificial Intelligence (AI) 2018 Table of Contents Foreword v Introduction vii Annex: Activities on Artificial Intelligence vii Comprehensive Nuclear-Test-Ban Treaty Organization 8 International Civil Aviation Organization 11 International Labour Organisation 13 International Telecommunication Union 15 United Nations Programme on HIV/AIDS 18 United Nations Conference on Trade and Development 19 United Nations Department of Economic and Social Affairs 21 United Nations Development Programme 22 United Nations Economic Commission for Europe 24 United Nations Environment Programme 26 United Nations Educational, Scientific and Cultural Organization 28 United Nations Population Fund 30 United Nations Global Pulse 32 United Nations High Commissioner for Refugees 34 United Nations Children’s Fund 35 United Nations Interregional Crime and Justice Research Institute 38 United Nations Institute for Disarmament Research 40 United Nations Industrial Development Organization 42 United Nations Office for Disaster Risk Reduction 44 United Nations Institute for Training and Research 46 United Nations Office for Disarmament Affairs 48 United Nations Office for Outer Space Affairs 50 United Nations University 52 World Food Programme 54 World Health Organization 56 World Intellectual Property Organization 58 World Bank Group 59 iii Foreword Recent progress in Artificial Intelligence has been im- mense and exponential. The technology is making its way out of research labs and into our everyday lives, prom- ising to help us tackle humanity’s greatest challenges. As the UN specialized agency for information and com- munication technologies, ITU believes in the power of AI for good, and organizes the “AI for Good” series since 2017. -
The AIGO: a Framework for Planning, Developing, and Deploying Artificial Intelligence in Intergovernmental Organizations
The AIGO: A Framework for Planning, Developing, and Deploying Artificial Intelligence in Intergovernmental Organizations Jannik Seger Nicolas Miailhe Simon Mueller JANUARY 2019 The AIGO: A Framework for Planning, Developing, and Deploying Artificial Intelligence in Intergovernmental Organizations JANUARY 2019 Jannik Seger | Nicolas Miailhe | Simon Mueller Artificial Intelligence (AI) has created significant value in prediction technology and illustrates the evolution from crucial areas such as healthcare, finance, energy, retrospective to AI-based, forward looking data analytics transportation, and environmental protection. The • Section IV details the value-creation potential of AI that productivity gains caused by AI hold the potential to bolster IGOs may realize by firmly integrating AI into their core growth and development over the next decades by making processes: improved insight generation, faster and decision-making processes and resource management of larger-scale evidence-based decision making, and complex systems more efficient. optimization of output delivery processes Similar to the steam engine or electricity, AI is a versatile • Section V provides a detailed, multi-step roadmap for an enabling technology with a diverse range of applications. effective implementation of AI in IGOs. It shows how to While the previous two paved the way for the creation of develop a strategic intent for AI, ensure senior specialized machines that could replace human physical executives’ support, lay the organizational foundations, labor for defined tasks, AI will eventually allow for the and ensure adequate data quality. IGO executives find development of self-optimizing information systems capable practical advice on how to prepare the cultural transition, of replacing human cognitive labor in specific settings and identify and prioritize use cases, and ensure a successful applications. -
AI and Machine Learning in 5G
No. 5, 2020 AI and Machine Learning in 5G Lessons from the ITU Challenge Stay current // // Stay informed ITU News has moved to a new platform. Discover MyITU your gateway to relevant ITU content, based on your interests. Keep informed with the latest ITU News. To receive the new weekly ITU Newsletter, Subscribe ITU News ITU News Regular articles Magazine Join ITU’s online communities on your favorite channel Editorial ITU News MAGAZINE No. 05, 2020 1 AI and machine learning in 5G — the ITU Challenge 2020 By Houlin Zhao, ITU Secretary‑General J In February this year, the we announced the approval International Telecommunication by our 193 Member States of Union (ITU) set the first ITU AI/ML in an ITU Radiocommunication 5G Challenge in motion — a global Sector (ITU–R) Recommendation: competition that will culminate in “Detailed specifications of the an online prize‑winning event on radio interfaces of IMT‑2020.” 15–17 December, 2020. IMT‑2020 specifications for the fifth Through the Challenge, ITU generation of mobile communica‑ Through the encourages and supports the grow‑ tions (5G) will be the backbone of ing community driving the integra‑ tomorrow’s digital economy, lead‑ Challenge, ITU tion of artificial intelligence (AI) and ing industry and society into the encourages machine learning (ML) in networks automated and intelligent world and supports and at the same time enhances the and promising to improve people’s community driving ITU standardiza‑ lives on a scale never seen before. the growing tion work for AI/ML. community In this edition of the ITU Magazine driving the The ITU Challenge enables the you will learn all about the ITU AI/ integration collaborative culture necessary for ML in 5G Challenge and also find success in emerging and future ample insight articles from industry of artificial networks such as 5G and creates and academia. -
Comments from More Cowbell Unlimited
June 10, 2019 Elham Tabassi National Institute of Standards and Technology 100 Bureau Drive, Stop 200 Gaithersburg, MD 20899 TM Enclosed: Technical Paper: FOCAL Information Warfare Defense Standard (v1.0 minus Appendix) Dear Ms. Tabassi, Thank you for the opportunity to submit comments in response to the National Institute of Standards and Technology’s (NIST) request for information on artificial intelligence (AI) standards. We assert that NIST should work collaboratively with Federal agencies and the private sector to develop a cross sector Information Warfare (IW) Defense Standard. The enclosed technical paper supports our assertion and TM describes our FOCAL IW Defense Standard , which is available for anyone to use. More Cowbell Unlimited, Inc. is a process mining and data science firm based in Portland OR. We are developing process technologies in support of national security and industry. Our mission is to help America remain a beacon of hope and strength on the world stage. Technological advancements are a double-edged sword. AI is a tool which promises great things for humanity, such reducing poverty and allowing creativity to flourish; however, there is a dark side which we believe must be the focal point of national security. Unsurprisingly, hunger for dominance and money are present in this discussion, too. Feeding large hordes of private information into an AI to create a “World Brain” is plausible and provides a vehicle to project power in various ways. One way to monetize and project power from this information is through advertisements. Another way--perhaps one we are already seeing-- is through IW. As the world becomes more reliant upon information, IW boosted with weaponized AI is a major threat. -
Leading Edge Technologies from the Slide Rule to the Cloud
Liquidtool Systems AG Leading Edge Technologies From the Slide Rule to the Cloud Rudolf Meyer 2021-03-24 Table of Contents 1 Introduction .............................................................................................................................. 2 2.1 Industry 0.0 – Industrial prerequisites ..................................................................... 3 2.2 Industry 1.0 – Industrial production .......................................................................... 3 2.3 Industry 2.0 – Industrial mass-production ............................................................. 4 2.4 Industry 3.0 – Industrial automation ........................................................................ 4 2.5 Industry 3.5 – Industrial globalization ...................................................................... 5 3 A closer look – Where do we stand now? ..................................................................... 6 3.1 Industry 4.0 – Industrial digitization ......................................................................... 7 3.2 Leading edge technologies for Industry 4.0 ....................................................... 10 4 Looking ahead – Industry 4.0, 5.0, 6.0, 7.0… ................................................................ 15 Impact on the labor market .............................................................................................. 15 Impending developments .................................................................................................16 4.1 Industry 5.0 -
Experts Doubt Ethical AI Design Will Be Broadly Adopted As the Norm Within the Next Decade
FOR RELEASE June 16, 2021 Experts Doubt Ethical AI Design Will Be Broadly Adopted as the Norm Within the Next Decade A majority worries that the evolution of artificial intelligence by 2030 will continue to be primarily focused on optimizing profits and social control. They also cite the difficulty of achieving consensus about ethics. Many who expect progress say it is not likely within the next decade. Still, a portion celebrate coming AI breakthroughs that will improve life BY Lee Rainie, Janna Anderson and Emily A. Vogels FOR MEDIA OR OTHER INQUIRIES: Lee Rainie, Director, Internet and Technology Research Janna Anderson, Director, Elon University’s Imagining the Internet Center Haley Nolan, Communications Associate 202.419.4372 www.pewresearch.org RECOMMENDED CITATION Pew Research Center, June 16, 2021. “Experts Doubt Ethical AI Design Will Be Broadly Adopted as the Norm in the Next Decade” 1 PEW RESEARCH CENTER About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping America and the world. It does not take policy positions. It conducts public opinion polling, demographic research, content analysis and other data-driven social science research. The Center studies U.S. politics and policy; journalism and media; internet, science and technology; religion and public life; Hispanic trends; global attitudes and trends; and U.S. social and demographic trends. All of the center’s reports are available at www.pewresearch.org. Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. For this project, Pew Research Center worked with Elon University’s Imagining the Internet Center, which helped conceive the research and collect and analyze the data. -
Creating the Engine for Scientific Discovery
www.nature.com/npjsba PERSPECTIVE OPEN Nobel Turing Challenge: creating the engine for scientific discovery ✉ Hiroaki Kitano 1 Scientific discovery has long been one of the central driving forces in our civilization. It uncovered the principles of the world we live in, and enabled us to invent new technologies reshaping our society, cure diseases, explore unknown new frontiers, and hopefully lead us to build a sustainable society. Accelerating the speed of scientific discovery is therefore one of the most important endeavors. This requires an in-depth understanding of not only the subject areas but also the nature of scientific discoveries themselves. In other words, the “science of science” needs to be established, and has to be implemented using artificial intelligence (AI) systems to be practically executable. At the same time, what may be implemented by “AI Scientists” may not resemble the scientific process conducted by human scientist. It may be an alternative form of science that will break the limitation of current scientific practice largely hampered by human cognitive limitation and sociological constraints. It could give rise to a human-AI hybrid form of science that shall bring systems biology and other sciences into the next stage. The Nobel Turing Challenge aims to develop a highly autonomous AI system that can perform top-level science, indistinguishable from the quality of that performed by the best human scientists, where some of the discoveries may be worthy of Nobel Prize level recognition and beyond. npj Systems Biology and Applications (2021) 7:29 ; https://doi.org/10.1038/s41540-021-00189-3 1234567890():,; NOBEL TURING CHALLENGE AS AN ULTIMATE GRAND EURISKO6,8. -
Resource Guide on ARTIFICIAL INTELLIGENCE (AI) STRATEGIES
RESOURCERESOURCE GUIDE GUIDE ONON ARTIFICIAL RESOURCEARTIFICIAL INTELLIGENCEINTELLIGENCEGUIDE STRATEGIES STRATEGIES ON ARTIFICIAL INTELLIGENCE STRATEGIES Resource Guide ON ARTIFICIAL INTELLIGENCE (AI) STRATEGIES April 2021 1 Table of Contents Chapter 1: Introduction ........................................................................................................................................... 4 Chapter 2: Ethics of AI .............................................................................................................................................. 6 Introduction ............................................................................................................................................................. 6 Ethical implications of AI .......................................................................................................... 8 Call for an ethical approach to development and use of AI ................................................... 10 United Nations work on AI Ethics .................................................................................................................. 10 Key References .................................................................................................................................................... 11 International Organizations .................................................................................................... 11 National Governments .........................................................................................................