I build and use emerging technological innovations in business, and I also teach others how they might too! I’m a serial entrepreneur and a Professor at the Wharton School of the University of Pennsylvania. As an entrepreneur, I co-founded and developed the core IP for Yodle Inc, a venture-backed firm that was acquired by Web.com. I’m now the founder of Jumpcut Media – a startup using data and Web3 technologies to democratize opportunities in Film and TV. In all this work, I'm often trying to assess how emerging technologies may affect business and society in the long run and how I can apply them to create new products and services.
I wrote
A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control
In this book, Professor Clayton Christensen explores the puzzle of why seemingly well-run companies fail. He shares many examples of companies that are well-managed, listen to their customers, act on market trends, and invest in R&D – i.e. appear to do all the right things – and yet fail. The Innovator’s Dilemma lays out why established companies often fail at disruptive technologies and how to tackle the inherent challenges. Disruptive technologies are technologies that underperform existing products in mainstream markets and have features that a few fringe customers value. They are often ignored by well-run companies precisely because their customers don’t care for them. But these technologies can improve quite dramatically and catch these companies off guard.
The author backs his theory with several examples of technologies that meet his definition of disruptive technologies (digital photography, PCs, etc.). While other theorists have pushed back on Christensen’s theory in recent years, I still consider the book as a must-read for anyone trying to understand innovation strategy.
Named one of 100 Leadership & Success Books to Read in a Lifetime by Amazon Editors A Wall Street Journal and Businessweek bestseller. Named by Fast Company as one of the most influential leadership books in its Leadership Hall of Fame. An innovation classic. From Steve Jobs to Jeff Bezos, Clay Christensen's work continues to underpin today's most innovative leaders and organizations. The bestselling classic on disruptive innovation, by renowned author Clayton M. Christensen. His work is cited by the world's best-known thought leaders, from Steve Jobs to Malcolm Gladwell. In this classic bestseller--one of the most influential business books…
This book by Steven Blank is a bible for anyone trying to understand how to build lean startups. The classic mistake that most entrepreneurs make is to go build a product soon after they develop a hypothesis about what customers want. By building products before customer discovery (i.e. verify customer needs and a scalable sales model), many products miss the mark and fail. The book explains how a lean start-up can figure out what customers want before proceeding to build products. This emphasis on a customer-centered approach rather than a product-centered approach can be the difference when it comes to finding product-market fit. A must-read for any founder!
The bestselling classic that launched 10,000 startups and new corporate ventures - The Four Steps to the Epiphany is one of the most influential and practical business books of all time. The Four Steps to the Epiphany launched the Lean Startup approach to new ventures. It was the first book to offer that startups are not smaller versions of large companies and that new ventures are different than existing ones. Startups search for business models while existing companies execute them.
The book offers the practical and proven four-step Customer Development process for search and offers insight into what makes some…
When we're children, we're asked what we want to be when we grow up. But what if there isn't just one career for us in our lifetime? What if we can have a squiggly line career that spans professions and industries?
This book lays out one of the most useful big-picture ways to put AI to use: as a predictive tool. The central point of the book is that from a business/economic standpoint, AI increases accuracy and reduces the cost of making data-driven predictions. The benefit of reducing the cost of predicting in business is enormous and this book lays that out clearly. And the rest of it is focused on how that will affect the world around us. I recommend this book highly to any manager who is thinking through what AI means for their firm. The writing style is clear – not excessively technical. A great read for everyone!
"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.
But in Prediction Machines, three eminent economists recast the rise of AI…
This book provides an excellent description of the various kinds of machine learning approaches and asks the question of whether there will be a Master Algorithm, one single (universal) algorithm that learns all kinds of tasks from data. The author, Pedro Domingos, introduces the different approaches to building intelligence and the research tribes exploring them – Symbolists (with its foundations in Philosophy and Logic), Connectionists (foundations in Neuro/Cognitive Science), Evolutionaries (foundations in Evolutionary Biology), Bayesians (statistical foundations), and Analogizers (Psychology). He also introduces some of his own ideas on what the master machine learning algorithm might look like. It’s a really useful primer for those who are not deeply immersed in machine learning but it’s written for readers with at least a basic engineering and computer science background.
Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.Machine learning is the automation of discovery,the scientific method on steroids,that enables intelligent robots and…
Benghazi: A New History is a look back at the enigmatic 2012 attack on the US mission in Benghazi, Libya, its long-tail causes, and devastating (and largely unexamined) consequences for US domestic politics and foreign policy. It contains information not found elsewhere, and is backed up by 40 pages of…
One of the biggest questions surrounding AI is the impact it will have on jobs. Just as manufacturing jobs are affected by mechanical automation, many white- and blue-collar jobs are going to be affected by AI-driven automation in the future. The question is whether AI will be like all technologies in the past (which have created more jobs than they have destroyed) or whether it is unique in its ability to automate and displace human jobs at a faster pace than the jobs it creates. Many commentators have asked the question and there are dozens of books exploring how AI will affect jobs.
Among all the books out there on the impact of AI-driven automation, this is one of my favorites. While offering a fundamentally optimistic take, the authors also warn the reader that our education systems will need to change and people will need to upskill themselves and public policy will need to keep up in order for us to successfully manage the transition. If you are under 40 years of age or have children who will be entering the workforce in the future, you should read this to understand how to adapt to AI.
In recent years, computers have learned to diagnose diseases, drive cars, write clean prose and win game shows. Advances like these have created unprecedented economic bounty but in their wake median income has stagnated and employment levels have fallen. Erik Brynjolfsson and Andrew McAfee reveal the technological forces driving this reinvention of the economy and chart a path towards future prosperity. Businesses and individuals, they argue, must learn to race with machines. Drawing on years of research, Brynjolfsson and McAfee identify the best strategies and policies for doing so. A fundamentally optimistic book, The Second Machine Age will radically alter…
If you read the news, you have probably heard the term algorithms: computer code that seems to control much of what we do on the internet, landing us in all sorts of jams. Elections are swayed by newsfeed algorithms, markets are manipulated by trading algorithms, women and minorities are discriminated against by resume screening algorithms – individuals are left at the mercy of machines. This book offers a way to understand the implications in our personal and professional lives and how we might offset the challenges they pose.
While this subject gets a lot of attention in popular journalism, I feel the public lacks the right mental models to understand algorithms and AI. As a result, the conversation is often fear-oriented, at the expense of being solution-oriented. This is my attempt to address these problems and start a conversation on what the solution should look like.
The constellation we know as Taurus goes all the way back to cave paintings of aurochs at Lascaux. This book traces the story of the bull in the sky, a journey through the history of what has become known as the sacred bull.
