Category: Artificial Intelligence

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Artificial Intelligence Education Innovation Reading

Latest Read: Spies, Lies, and Algorithms

Spies, Lies, and Algorithms: The History and Future of American Intelligence by Amy Zegart. Amy holds a Ph.D. in Political Science from Stanford University. Dr. Zegart is an associate professor at UCLA’s School of Public Affairs.

Spies, Lies, and Algorithms: The History and Future of American Intelligence by Amy Zegart

Amy previously served on the Clinton administration’s National Security Council staff in 1993 and as a foreign policy advisor to the Bush-Cheney 2000 presidential campaign.

She has testified before the Senate Select Committee on Intelligence and has provided training to the Marine Corps, the Office of the Director of National Intelligence, and Lawrence Livermore National Laboratory.

So, it is no surprise US intelligence does not publicly address their embrace of AI for obvious reasons. Amy is documenting the use of technology including AI in the world of espionage. US intelligence has the challenge of confronting the James Bond 007 effect when confronting both public opinion and the growing role misinformation.

Amy is providing a historical view of US intelligence and their embrace of technology. She is also offering a future view of American espionage in a world of advanced AI. This is a very interesting read to discover an overview to US intelligence and the history of fatal biases and misunderstood analytics. Yet, Amy is outlining how today’s technology empowers both old 3rd world and new enemies. Technology has also empowered citizens to use web services to track nuclear threats. This was unheard of during the Cold War.

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Artificial Intelligence Education Innovation Reading

Latest Read: Artificial Intelligence in Practice

Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems by Bernard Marr. He holds degrees in business, engineering and information technology from the University of Cambridge and Cranfield School of Management.

Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems by Bernard Marr

Today, Bernard also enjoys teaching for Oxford University, Warwick Business School, the Irish Management Institute, and the and Institute of Chartered Accountants in England and Wales. He is also a contributor to Forbes. Bernard is focusing on strategy, business performance, digital transformations, and AI.

He has certainly advised many of the world’s most recognized brands including: Amazon, Google, Microsoft, Astra Zeneca, The Bank of England, BP, NVIDIA, Cisco, DHL, IBM, HPE, Ericsson, Jaguar Land Rover, Mars, The Ministry of Defense, NATO, The Home Office, NHS, Oracle, T-Mobile, Toyota, The Royal Air Force, Shell, The United Nations, Walgreens, and Walmart.

Bernard has written 20 books having been recognized with the 2022 Business Book of the Year award, the CMI Management Book of the Year award, the Axiom book award and the WHSmith best business book award. I enjoyed reading one of his previous books, Big Data: Using smart big data analytics and metrics to make better decisions and improve performance.

Artificial intelligence and machine learning are continuing to be cited as the most important trend in society today. However, rather than list where AI is deployed, it would be more important to understand how AI was deployed. Bernard is providing comprehensive overviews, including technical details as key learning summaries for each case study.

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Artificial Intelligence Education Innovation Reading

Latest Read: Competing in the Age of AI

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World by Marco Iansiti and Karim R. Lakhani

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World by Marco Iansiti and Karim R. Lakhani

Marco Iansiti is Professor of Business Administration at Harvard Business School. He is a co-director of the Laboratory for Information Science at Harvard and of the Digital Initiative at HBS. Marco holds a PhD and an AB in Physics from Harvard. He is an advisor at KeystoneAI.

Karim R. Lakhani is a Business Administration Professor at Harvard Business School. He is co-director of the Laboratory of Innovation Science at Harvard’s Institute of Quantitative Social Science. He is Chair of the Harvard Business School’s Analytics Program. Karim holds bachelor’s degree in Electrical Engineering and Management from McMaster University, a masters degree in Technology and Policy from MIT and a PhD in management from the MIT. He previously served as a Lecturer at MIT’s Sloan School of Management.

This is certainly one of the better books addressing AI and business innovation. A must read for any organization now confronting AI challenges regardless of their respective markets. In industry after industry, the core elements of data, analytics, and AI-driven processes have certainly transformed business.

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Artificial Intelligence Education Innovation Reading

Latest Read: Robot-Proof

Robot-Proof: Higher Education in the Age of Artificial Intelligence by Joseph E. Aoun. He holds a masters in Oriental Languages and Literature at the Université Saint-Joseph and a PhD in Linguistics at MIT. He joined the University of Southern California in 1982 as a Linguistics Professor. Currently he is serving as the 7th president of Northeastern University.

Robot-Proof: Higher Education in the Age of Artificial Intelligence by Joseph E. Aoun

The automation of jobs was certainly a threat to low-skilled workers in the 1980s. Today the advancement of Artificial Intelligence is certainly empowering systems and robots to confront knowledge workers in traditionally highly-skilled jobs with the same threat. In fact, this includes jobs that focused on high tech skills including interpreting medical images, legal research, and analyzing data.

So, how can higher education prepare students for a career as Artificial Intelligence is surging across markets? Dr. Aoun is advancing the idea that a way to educate current college students is to invent, create, and discover needs across society that Artificial Intelligence cannot currently address.

Therefore, he is introducing a position to create a mindset that he called humanics. This framework builds upon education models that prepare students to enter a workforce with robots and smart machines working alongside them. This includes computer literacy

Accordingly, he points to the development of IBM Watson in cancer research. This provided oncologists with faster diagnosis and efficient treatment plans. Then Watson moved from hospitals to the New York City Public School system. Watson has been advising teachers on effective teaching practices based upon Artificial Intelligence.

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Artificial Intelligence Education Innovation Reading

Latest Read: Machine Learning: The New AI

Machine Learning: The New AI by Ethem Alpaydin. A Fulbright scholar, Ethem holds a Ph.D. in Computer Engineering from Ecole Polytechnique Fédérale de Lausanne. He has held visiting research positions at University of California, Berkeley, and MIT.

Machine Learning: The New AI by Ethem Alpaydin

Ethem is delivering an exceptional overview of machine learning. If you want to understand the foundations of machine learning without any programming details, this is the perfect book. The math and statistics are delivered at a conceptual level. Anyone can follow along. He provides a solid foundation addressing algorithms, artificial intelligence, and neural networks. Again for anyone interested, this book is not technical. You will not be overwhelmed, but rather inspired to learn.

Today, Machine Learning (ML) certainly is the most popular subset of artificial intelligence. With ML certainly now a core AI service, we can more easily understand the growing range of ML apps we use everyday.

This includes product recommendations to voice recognition. Spread across just seven chapters, readers will come to understand ML, Statistics and Data Analytics. However chapter four: Neural Networks and Deep Learning is a strong delivery of ML’s core services. This is perhaps the most important chapter for readers new to ML. Ethem provides the much needed context that the foundations were first tested in 1946. This helps set a level playing field in following onto neural networks and the core of deep learning.

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