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AI Will Create Millions More Jobs Than It Will Destroy. Here’s How

In the past few years, artificial intelligence has advanced so quickly that it now seems hardly a month goes by without a newsworthy AI breakthrough. In areas as wide-ranging as speech translation, medical diagnosis, and gameplay, we have seen computers outperform humans in startling ways.

This has sparked a discussion about how AI will impact employment. Some fear that as AI improves, it will supplant workers, creating an ever-growing pool of unemployable humans who cannot compete economically with machines.

This concern, while understandable, is unfounded. In fact, AI will be the greatest job engine the world has ever seen.

IBM CEO Ginni Rometty Delivers Opening Keynote at CES 2019 on What’s Next in Artificial Intelligence, Blockchain and Quantum Computing

ARMONK, N.Y., Jan. 4, 2019 /PRNewswire/ — IBM (NYSE: IBM) Chairman, President and CEO Ginni Rometty will deliver the opening keynote at CES 2019 on Tuesday, Jan. 8. CES is the largest and one of the most influential technology events in the world.

Rometty will show how technologies like artificial intelligence, blockchain and cloud are reshaping the world of business, and, in turn, our daily lives. She also will talk about what’s coming next in these pioneering technologies – and how new data will revolutionize how we live, work and play. Rometty shares perspective on the future of technology in the Consumer Technology Association magazine It Is Innovation (i3) CES edition: https://www.nxtbook.com/nxtbooks/manifest/i3_20190102

Rometty will be joined onstage by Ed Bastian, CEO of Delta Air Lines; Charles Redfield, executive vice president of Food for Walmart; and Vijay Swarup, vice president of R&D for ExxonMobil.

Clever AI Hid Data From Its Creators to Cheat at Tasks They Gave It

Recent research from Stanford and Google has made the worst nightmare of some concerned with artificial intelligence (AI) all the more real. A machine learning agent was caught cheating by hiding information in “a nearly imperceptible, high-frequency signal.”

Clever, but also creepy.

The agent was instructed to turn aerial images into street maps and back again as part of research to improve Google’s process of turning satellite images into the widely used and relied upon Google Maps. The process involves CycleGAN, “a neural network that learns to transform images of type X and Y into one another, as efficiently yet accurately as possible.” Though the agent was performing this task quite well, it quickly became apparent that it was performing the task too well.