Today S Ai Easy Ethical Artificial Intelligence For All
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Artificial Intelligence for a Better Future
Author: Bernd Carsten Stahl
language: en
Publisher: Springer Nature
Release Date: 2021-03-17
This open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place.
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, such as climate change, resource scarcity and health crises.
Today's AI - Easy, Ethical Artificial Intelligence for All
TESTIMONIALS: "We want to use this approach." Top 10 UK University - "Feeling more confident about AI now." WPP MD - "Clever yet easily understood." Indy Agency MD - "Extremely relevant & timely." Top 3 Bank MD - "Important for all our members." RSA Director - "Even I get it now!" Google AI StartUp CFO - CONTENTS: 1. Intro: What's Important in AI Today?What Does AI Mean? What's Changed in AI? What's AI Good For? Who Needs Today's AI? So What's Ethical AI? Case Study: Microsoft & LinkedIn Aim to Democratise AI - Case Study: PWC and L'Oreal Find New Ways to Identify Successful Candidates - Conclusions 2. Today's AI For All 2.1 How to Prepare? The Big Issue? New Tools! 2.2 How to Prototype & Improve? Data Gathering Choosing AI Tools & Training Self Monitoring Case Study: Today's Simple AI(tm) Tools Case Study: Unilever HR Tests New Tools Next Steps Case Study: Adobe adds AI to Design 2.3 How to Roll Out? Big Changes - Complex AI - Simple AI 2.4 Our Conclusions: Let's Play & Learn! 2.5 What's the Near Future? Appendix 1 - Our Reviews of AI Toolsets 1.1 Wipro Holmes 1.2 Apache PredictionIO 1.3 IBM Watson 1.4 Google Cloud Machine Learning Engine 1.5 Azure Machine Learning Studio 1.6 Google Tensor Flow 1.7 Ayasdi 1.8 Infosys Nia 1.9 Meya 1.10 Nvidia Deep Learning 1.11 Rainbird 1.12 Receptiviti 1.13 Salesforce Einstein 1.14 Today's Simple AI(tm) Appendix 2 - AI Training Courses Reviewed 2.1 Today's Simple AI(tm) Training 2.2 Udacity Machine Learning Engineer Nanodegree 2.3 Artificial Intelligence MicroMasters 2.4 Google's ML Crash Course 2.5 IBM Open Badge Programme 2.6 MIT's Deep Learning for Cars 2.7 NVIDIA Deep Learning Specialization 2.8 Stanford University Machine Learning 2.9 Elements of AI 2.10 Fundamentals of Deep Learning for Computer Vision 2.11 Learning from Data 2.12 Grokking Deep Learning in Motion 2.13 CS188.1x: Artificial Intelligence