Tag: algorithms

Latest Read: The Alignment Problem

Post author By Don Kasprzak
Post date October 2, 2024

The Alignment Problem: Machine Learning and Human Values by Brian Christian.

Brian holds a BA in Computer Science and Philosophy from Brown University. And holds an MFA in Poetry from the University of Washington. He is a visiting scholar at the University of California, Berkeley. His focus is cognitive science and human-compatible AI.

He received the Eric and Wendy Schmidt Award for Excellence in Science Communication for his work on The Alignment Problem. Yes, I fully agree this is a wonderful book to read.

His previous books include The Most Human Human and Algorithms to Live By. Both address AI technology and the human experience. When AI services (ChatGPT, CoPilot, Dalle 3, etc.) attempt to execute tasks that result in errors, ethical and potential risks emerge. So, researchers call this the alignment problem.

At the book’s core, Brian is examining ethical and safety issues as machine learning technologies are both advancing into society more rapidly than projected. Perhaps the key element is the ability for machine learning services to execute tasks on behalf of humans across almost every aspect of our lives. This also markets from education, retail, supply chain, and energy to name just a few.

Tags algorithms, Artificial Intelligence, Bias, hallucinations, machine learning

Artificial Intelligence Education Reading

Latest Read: How to Stay Smart in a Smart World

Post author By Don Kasprzak
Post date December 9, 2023

How to Stay Smart in a Smart World: Why Human Intelligence Still Beats Algorithms by Gerd Gigerenzer.

Gerd holds a master of arts and a doctor of philosophy in psychology from the University of Munich. He received the postdoctoral degree of habilitation in 1982. Today Gerd is Director at the Max Planck Institute for Human Development and Director of the Harding Center for Risk Literacy in Berlin.

He is former Professor of Psychology at the University of Chicago and a Distinguished Visiting Professor at the University of Virginia. Gerd is a Fellow of the Berlin-Brandenburg Academy of Sciences and the German Academy of Sciences.

So, Gerd is providing a very compelling case for humans to stay in charge of our current world of algorithms. He is addressing with deep insights the fallacy of current state AI. He does certainly acknowledge the impactful use of AI yet provides an honest view that markets are shaped by companies promising AI as the holy savior of their organization’s marketplace.

In fact, the first part of his book “The Human Affair with AI” really provides a wake up call to all the hype driven by those companies and markets who stand to gain the most.

Tags algorithms, Artificial Intelligence, Gerd Gigerenzer, How to Stay Smart in a Smart World, privacy

Artificial Intelligence Education Innovation Reading

Latest Read: How Data Happened

Post author By Don Kasprzak
Post date October 7, 2023

How Data Happened: A History from the Age of Reason to the Age of Algorithms by Chris Wiggins and Matthew L. Jones.

Chris is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. He holds a Ph.D. from Princeton in theoretical physics, and in addition, is a founding member of the executive committee of the Data Science Institute, and of the Department of Systems Biology. Chris is also co-founder and co-organizer of hackNY.

Matthew Jones is a professor of History at Princeton. He holds a Master in philosophy from Cambridge University and Ph.D. from Harvard. While at Columbia, Matthew and Chris taught a class regarding data. Their work is tracing the history of data back to the 18th century. At that time European states began manipulating physical resources.

They see the rise of data and early statistical methods were indeed used to justify eugenics. In fact, this misled some in the late 1800s to believe data could quantify race differences. Unsurprisingly those same European countries used data to develop military and industrial applications.

Tags algorithms, Artificial Intelligence, Chris Wiggins, How Data Happened, Matthew Jones

Artificial Intelligence Education Innovation Reading

Latest Read: Spies, Lies, and Algorithms

Post author By Don Kasprzak
Post date September 30, 2023

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.

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.

Tags algorithms, Amy Zegart, Artificial Intelligence, digital transformation, espionage, leadership

Artificial Intelligence Education Innovation Reading

Latest Read: Machine Learning: The New AI

Post author By Don Kasprzak
Post date September 5, 2023

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.

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.

Tags algorithms, Artificial Intelligence, Ethem Alpaydin, machine learning, neural networks