Everyday Chaos: Technology, Complexity, and How We’re Thriving in a New World of Possibility by David Weinberger.
David holds a PhD in Philosophy from the University of Toronto. He is widely published including Wired, Scientific American, Harvard Business Review, The Atlantic, and The Chronicle of Higher Education.
He is Co-Director of Harvard Library’s Innovation Lab; Writer-in-residence at a Google AI lab; Senior researcher at Harvard’s Berkman Klein Center for Internet & Society; Fellow at Harvard’s Shorenstein Center on Media, Politics and Public Policy; and a Franklin Fellow at the US State Department.
David previously authored The Cluetrain Manifesto, Everything is Miscellaneous, and Too Big to Know. Having read these books, David’s writing both inspirational and spot on regarding how internet technologies are shifting the global world. My only regret is not reading this book the day it hit newsstands. And based upon his previous works, will not make that mistake moving forward.
Everyday Chaos is focusing on artificial intelligence, big data, modern science, and a very dynamic internet. Rolling into a somewhat staggering force, these technologies are certainly revealing how complex the world is today. Perhaps the most important message, we now find ourselves facing a digital transformation more unpredictable even by those who created the technologies.
Understanding a staggering force
The downstream impact clearly reveals how everyday tasks, from eating breakfast and running a business can be an ethical exploration via data. Yet, David is outlining how we can take full advantage of the “Everyday Chaos” to actually confront and better understand how to embrace all elements in our world.
Let’s understand the details
Nevertheless, the promise of these technologies, including machine learning must be reviewed, and not taken for granted. Machine Learning is certainly one of the more robust AI disciplines. Yet, as Machine Learning will indeed reveal data insights across a wide range of markets we all must clearly understand “how” Machine Learning generated those results. This even includes a transparent understanding of the data models leveraged in creating Machine Learning outcomes.
In just the instance of Machine Learning for medical imaging, it can be both groundbreaking and dangerous. The ability of an AI service to process amounts of data so immense it would overwhelm teams of talented data science professionals. However, it is within big data that physicians and oncologist can learn previously unknown data regarding X-Rays, or MRI scans. Then consider how this type of AI service can be deployed to rural areas across our country. These insights should not be limited to just metropolitan areas anymore.
At the same time, David is revealing how well understood system strategies including A/B testing, Minimum Viable Products, open platforms, and user-modifiable video games can have a downstream impact upon social movements. Again, Machine Learning will reveal predictions. This permits planning and preparation on a scale never before available.
Do not overlook this book
In conclusion, David has yet delivered an incredible book allowing us to certainly understand how the world works today. If you choose not to read this book, you do so at the peril of yourself and your organization.