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Literature Review: Artificial Intelligence Problems for the 2020s
A briefing from the European Parliament  provides accessible introductions to some of the key techniques that come under the Artificial Intelligence banner, grouped into three sections to give a sense the chronology of its development. The first describes early techniques, described as ‘symbolic AI’ while the second focuses on the ‘data driven’ approaches that currently dominate, and the third looks towards possible future developments. By explaining what is ‘deep’ about deep learning and showing that AI is more maths than magic, the briefing aims to equip the reader with the understanding they need to engage in clear-headed reflection about AI’s opportunities and challenges.
In 2019, community groups, researchers, policymakers, and workers demanded a halt to risky and dangerous AI. AI Now’s 2019 report  spotlights these growing movements, examining the coalitions involved and the research, arguments, and tactics used. We also examine the specific harms these coalitions are resisting, from AI-enabled management of workers, to algorithmic determinations of benefits and social services, to surveillance and tracking of immigrants and underrepresented communities. What becomes clear is that across diverse domains and contexts, AI is widening inequality, placing information and control in the hands of those who already have power and further disempowering those who don’t.
The development and implementation of AI is not without its share of controversy, and the debate about the risks and rewards of this unique and revolutionary technology tend toward extremes, with many observers predicting that AI will destroy jobs and even eventually threaten humans . It is clear from the data that the United States and China lead in AI investment, with China dominating global AI funding. Chinese AI companies raised a total of $31.7 billion in the first half of 2018, almost 75 percent of the global total of $43.5 billion. As a result of strong and direct government support, China looks poised to lead the AI space in several sectors including healthcare and autonomous driving.
According to The State of AI: 2019 Report , the landscape for entrepreneurs is changing. Europe’s 1,600 AI startups are maturing, bringing creative destruction to new industries, and navigating new opportunities and challenges. While the UK is the powerhouse of European AI, Germany and France may extend their influence. AI will have profound implications for companies and societies. AI will reshape sector value chains, enable new business models and accelerate cycles of creative destruction. While offering societies numerous benefits, AI poses risks of job displacement, increased inequality and the erosion of trust.
Agreed by all members of the AI for Good UN Partners, the 2019 version of the Compendium “UN Activities on Artificial Intelligence”  has been updated, including the collection of 2-pager report from 36 UN agencies, providing further details on UN agencies experiments with AI to improve their response to global challenges. It outlines how AI is being used to fight hunger, ensure food security, mitigate climate change, advance health for all, and facilitate the transition to smart sustainable cities. It also offers insights into the challenges associated with AI, addressing ethical and human right implications, and so invites all stakeholders, including government, industry, academia and civil society, to consider how best to work together to ensure AI serves as a positive force for humanity.
For the purpose of entrusting all sentient beings with powerful AI tools to learn, deploy and scale AI in order to enhance their prosperity, to settle planetary-scale problems and to inspire those who, with AI, will shape the 21st Century, Montreal.ai introduces this VIP AI 101 CheatSheet for All . Montreal.ai is preparing a global network of education centers to pioneer an impactful understanding of AI and to foster a vector for safe humanitarian Artificial General Intelligence (AGI).
Starting from such general references, this booklet identifies ten relevant areas from very recent contributions put forward at academic level in the form journal articles, conference proceedings and students theses. Ten freely accessible internet references have been selected for each area and direct links are provided at the end of each chapter for own consultation. Our selected references do not intend to mirror ranking indexes nor establish novel classifications. On the contrary, they are meant to represent peer-reviewed, diverse and scientifically-sound case studies for vertical dissemination aimed at non-specialist readers. They will also be able to scoop even more references through the bibliography that is reported at the end of each selected reference.
Without further ado, these are the “Ten Problems for Artificial Intelligence in the 2020s” that we are going to introduce in this booklet:
- computer games,
- intelligent optimization,
- human intervention,
- ethical issues,
- software development,
- open source,
- operations research.
Each problem has its own dedicated chapter made of an introductory section, a short presentation of the ten selected references and a conclusions section.
The final chapter of this booklet will report the conclusions from each chapter again in order to provide a complete executive summary.
GENERAL REFERENCES CITED
 P. Boucher, “How artificial intelligence works”, 2019, European Parliamentary Research Service, PE 634.420, online at https://www.europarl.europa.eu/at-your-service/files/be-heard/religious-and-non-confessional-dialogue/events/en-20190319-how-artificial-intelligence-works.pdf
 K. Crawford et al., “AI Now 2019 Report”, New York: AI Now Institute, 2019, online at https://ainowinstitute.org/AI_Now_2019_Report.html
 X. Mou, “Artificial Intelligence: Investment Trends and Selected Industry Uses”, 2019, IFC – a member of the World Bank Group, Note 71, Sept 2019, online at https://www.ifc.org/wps/wcm/connect/7898d957-69b5-4727-9226-277e8ae28711/EMCompass-Note-71-AI-Investment-Trends.pdf?MOD=AJPERES&CVID=mR5Jvd6
 D. Kelnar, “The State of AI 2019: Divergence”, 2019, MMC Ventures and Barclays UK Ventures, online at https://www.mmcventures.com/wp-content/uploads/2019/02/The-State-of-AI-2019-Divergence.pdf
 H. Zhao et al., “United Nations Activities on Artificial Intelligence (AI) 2019”, 2019, International Telecommunication Union, ISBN 978-92-61-29601-8, online at https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2019-1-PDF-E.pdf
 V. Boucher, “VIP AI 101 Cheatsheet”, Montreal.ai Academy, preprint 25 Nov 2019, online at http://www.montreal.ai/ai4all.pdf Tesla stock, Boston Dynamics, reinforcement learning, natural language processing, machine learning
booklet updated on 5 Jun 2020, now on sale as version 1.1