Work Automation

From mechanical looms to the combustion engine to the first computers, new technologies have always provoked panic about workers being replaced by machines. For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk.

Staying true to his trademark journalistic approach, Andrés Oppenheimer takes his listeners on yet another journey, this time across the globe, in a thought-provoking search to understand what the future holds for today's jobs in the foreseeable age of automation.

This short, accessible book seeks to explore the future of work through the views and opinions of a range of expertise, encompassing economic, historical, technological, ethical, and anthropological aspects of the debate.

If you’re a first-time robot user, how can you get started? How do you get from your initial idea to a productive, working robot? And if you’ve already got a few robotic deployments under your belt, how can you scale up your robotics efforts throughout your factory - or across multiple factories? The answers can be found in Lean Robotics: A methodology for simplifying robotic cell deployments. Lean robotics is a systematic way to complete the robotic cell deployment cycle, from design to integration and operation.

What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Drawing upon real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.

As we enter the fourth great leap forward in technology with robots and AI, we face the first services revolution. The power balance will again shift massively to companies as new technologies drive productivity increases in the service industry, much as the last three industrial revolutions transformed manufacturing. What lessons can we learn from the past three industrial revolutions and the current state of the labor market?

Your organization has made the decision to adopt automation and artificial intelligence technologies. Now, you face difficult and stubborn questions about how to implement that decision: How, when, and where should we apply automation in our organization? Is it a stark choice between humans versus machines? How do we stay on top of these technological trends as work and automation continue to evolve? Work and human capital experts Ravin Jesuthasan and John Boudreau present leaders with a new set of tools to answer these daunting questions.

The rapid growth of technology and automation has changed the way we seek our work and find fulfillment - money, meaning, and freedom. Those who don't adapt are being trapped in the downward spiral of career stagnation, working harder and earning less, or losing their jobs altogether.

Artificial intelligence is driving workforce disruption on a scale not seen since the Industrial Revolution. Automation was once associated with mass layoffs in heavy industry like auto and steel, but computers are getting smarter and are beginning to replace traditionally 'white collar' roles like law, consulting, banking and finance. Yet some curious findings are emerging from the world's leading research labs.

One in three American workers is now a freelancer. This “gig economy” - one that provides neither the guarantee of steady hours nor benefits - emerged out of the digital era and has revolutionized the way we do business. High-profile tech start-ups such as Uber and Airbnb are constantly making headlines for the disruption they cause to the industries they overturn. But what are the effects of this disruption, from Wall Street down to Main Street? What challenges do employees and job seekers face at every level of professional experience?

To understand machine learning, you need to understand what it means and how it affects you. Machine learning is a method the utilizes data analysis to provide an automatic system of analysis for model building that involves analytics. This is a specific branch of artificial intelligence based solely on ideas that say that through a system, you can begin to learn the data that is needed for pattern identification and decision-making that will include minimal amounts of human interaction and intervention.