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Artificial intelligence in society.
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Paris :
OECD Publishing,
2019.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Artificial intelligence in society. |
| 264 | 1 | |a Paris : |b OECD Publishing, |c 2019. | |
| 300 | |a 1 online resource (148 pages) : |b illustrations | ||
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| 504 | |a Includes bibliographical references. | ||
| 520 | 3 | |a The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. Yet, as AI applications are adopted around the world, their use can raise questions and challenges related to human values, fairness, human determination, privacy, safety and accountability, among others. This report helps build a shared understanding of AI in the present and near-term by mapping the AI technical, economic, use case and policy landscape and identifying major public policy considerations. It is also intended to help co-ordination and consistency with discussions in other national and international fora. | |
| 505 | 0 | |a Intro -- Preface -- Foreword -- Acronyms, abbreviations and currencies -- Executive summary -- Machine learning, big data and computing power have enabled recent AI progress -- AI systems predict, recommend or decide an outcome to influence the environment -- AI can improve productivity and help solve complex problems -- AI investment and business development are growing rapidly -- AI applications abound, from transport to science to health -- Trustworthy AI is key to reaping AI's benefits -- AI is a growing policy priority for all stakeholders -- 1. The technical landscape | |
| 505 | 8 | |a A short history of artificial intelligence -- Where we are today -- What is AI? -- Conceptual view of an AI system -- Environment -- AI system -- AI model, model building and model interpretation -- AI system illustrations -- Credit-scoring system -- Assistant for the visually impaired -- AlphaGo Zero -- Autonomous driving system -- The AI system lifecycle -- AI research -- Cluster 1: ML applications -- Cluster 1: Policy relevance -- Cluster 2: ML techniques -- Cluster 2: Policy relevance -- Cluster 3: Ways of improving ML/optimisations -- Cluster 3: Policy relevance | |
| 505 | 8 | |a Cluster 4: Considering the societal context -- Cluster 4: Policy relevance -- References -- Notes -- 2. The economic landscape -- Economic characteristics of artificial intelligence -- Artificial intelligence enables more readily available prediction -- Machine prediction is a substitute for human prediction -- Data, action and judgment complement machine prediction -- Implementing AI in organisations requires complementary investments and process changes -- Private equity investments in AI start-ups -- AI now represents over 12% of private equity investments in start-ups | |
| 505 | 8 | |a The United States and China account for most AI start-up investments -- The volume of AI deals grew until 2017, but so did their size -- Investment patterns vary across countries and regions -- Autonomous vehicle start-ups are receiving significant funding -- Broader trends in development and diffusion of AI -- References -- Note -- 3. AI applications -- AI in transportation with autonomous vehicles -- Economic and social impact of AVs -- Market evolution -- Technology evolution -- Policy issues -- Safety and regulation -- Data -- Security and privacy -- Workforce disruption -- Infrastructure | |
| 505 | 8 | |a AI in agriculture -- Challenges to AI adoption in agriculture -- Potential ways to encourage adoption of AI in agriculture -- AI in financial services -- Credit scoring -- Financial technology lending -- Deploying AI for cost reduction in financial services -- Legal compliance -- Fraud detection -- Algorithmic trading -- AI in marketing and advertising -- AI in science -- Recent drivers of AI in science -- The diversity of AI applications in science -- AI can also combine with robotic systems to execute closed-loop scientific research -- Policy considerations -- AI in health -- Background | |
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| 650 | 0 | |a Artificial intelligence |x Social aspects. | |
| 650 | 6 | |a Intelligence artificielle |x Aspect social. | |
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