Humanity Amplified: Understanding the AI World and Augmenting Our Students’ Intelligence with Human Deep Learning

by Stefan Bauschard, Sabba Quidwai

This book looks at the growing gap between the attention paid to the development of intelligence in machines and humans.

Chapter I. Prioritizing Machine Intelligence Over Human Intelligence
Chapter 2. Developing Intelligence in 1765-Present
Chapter 3. As Education Deep Learning and the Development of Intelligence in Machines
From Pong, to Go, to Diplomacy, to Chatbots, to Agents, to AGI and ASI
Chapter 4. Major AI Models, Tools, and Applications
Chapter 5. The Education System Under Challenges from AI and Beyond
Chapter 6. Using Academic Deep Learning to Support Human Development in an AI World
Chapter 7. Amplifying Human Capability and Collaborating with AIs
Chapter 8. Overcoming Education’s Challenges
Chapter 9. AI Policies & Guidance
Chapter 10. Practical Implementation
Chapter 11. Imagining the Future Beyond Adaptations and More Technology
Chapter 12. Leading Change in Industrialization 4.0/5.0
Chapter 13. A Renaissance Beyond Ethics, Babies, Friends, Lovers, Joy, and Future of the Humanit(ies)
Chapter 14. Conclusion and a Moon Shot

While computer scientists have made great strides in developing human intelligence capacities in machines using deep learning technologies, including the abilities of machines to learn on their own, a significant part of the education system has not kept up with developing the intelligence capabilities in people that will enable them to succeed in the 21st century. Instead of fully embracing pedagogical methods that place primary emphasis on building skills that nurture our humanity, such as empathy, collaboration, critical thinking, communication, creativity, and self-learning through experiential, interdisciplinary approaches, a substantial portion of the educational system continues to heavily rely on traditional instructional methods and goals.

The book emphasizes the need to prioritize academic programs that promote human deep learning as well as methods that integrate human deep learning approaches and AI tools. It suggests that this kind of human-computer interaction (HCI) will amplify all capacities of human intelligence, ensuring that people thrive even though machines will likely surpass human intellectual capabilities in all or nearly all domains over the next few decades or less, possibly by the time today’s first graders graduate from high school. We also make the case that schools should support developing many essential human attributes such as courage, kindness, love, and patience in students, traits that are not only difficult to develop in machines but that will be required to thrive regardless of any progress made in developing human intelligence and other capabilities in machines. Our approach does require a change to the underlying grammar of education, but without it, we risk employing AI tools to simply hyperscale approaches to education developed in the early twentieth century.

It includes an overview of the radical and continued advances in AI that we are currently experiencing, including imminent developments such as autonomous AI agents that will be able to make their own choices and undertake their own actions when given goals. We conclude with a practical roadmap for schools to immediately begin implementing changes so that all students can succeed in the AI world. Such changes will require educators to embrace significant change, overcome entrenched grammars, and attract funding, but it is no different than the struggle deep learning computer scientists endured for opponents who thought computers had to be fed hand-crafted instructions that would help models make decisions rather than allowing them to largely learn on their own.

995 pages, Kindle Edition

Published May 10, 2024