On an afternoon in early April, Tommi Jaakkola is pacing at the front of the vast auditorium that is 26-100. The chalkboards behind him are covered with equations. Jaakkola looks relaxed in a short-sleeved black shirt and jeans, and gestures to the board. "What is the answer here?" he asks the 500 MIT students before him. "If you answer, you get a chocolate. If nobody answers, I get one -- because I knew the answer and you didn't." The room erupts in laugher.
MIT research scientist Richard Fletcher directs the Mobile Technology Group at MIT D-Lab, which develops a variety of mobile sensors, analytic tools, and diagnostic algorithms to study problems in global health and behavior medicine. Utilizing mobile technologies -- which include smartphones, wearable sensors, and the so-called internet of things -- his group applies these technologies to real-world social problems with global implications. These issues involve a variety of areas, such as environmental monitoring and air pollution, agriculture, farming, and global health.
The many potential social and economic benefits from advances in AI-based technologies depend entirely on the environment in which these technologies evolve, says the Royal Society. According to a new report from the UK's science academy, urgent consideration needs to be given to the "careful stewardship" needed over the next ten years to ensure that the dividends from machine learning – the form of artificial intelligence that allows machines to learn from data – benefit all in UK society.
The Fourth Industrial Revolution has arrived. The first was the steam engine-driven Industrial Revolution; the second involved the innovations from Henry Ford's assembly line. Third, microelectronics and computer power appeared on factory floors. Now, manufacturing businesses are beginning to integrate robotics, automation and other data-driven technologies into their workflows.