In early 2011, Ken Jennings looked like humanity's last hope. Watson, an artificial intelligence created by the tech giant IBM, had picked off lesser Jeopardy players before the show's all-time champ entered a three-day exhibition match. At the end of the first game, Watson--a machine the size of 10 refrigerators--had Jennings on the ropes, leading $35,734 to $4,800. On day three, Watson finished the job. "I for one welcome our new computer overlords," Jennings wrote on his video screen during Final Jeopardy. Watson was better than any previous AI at addressing a problem that had long stumped researchers: How do you get a computer to precisely understand a clue posed in idiomatic English and then spit out the correct answer (or, as in Jeopardy, the right question)?

"With great power, comes great responsibility" I remember hearing this dialogue in the Spider-Man movie where Uncle Ben schools a young Peter Parker on the travails of wielding power in life. In the context of Artificial Intelligence, this phrase could not be more relevant. Artificial Intelligence is widely being heralded as General Purpose Technology by many economists – one with a range of characteristics that make it poised to generate long-term productivity and economic growth. The onus of bailing out economies out of turmoil and provide a foundation for a new world order falls on AI, in these COVID times especially. This makes the debate around ethical AI is extremely pertinent today. How can AI be ethical?

A new artificial intelligence (AI)-powered asset monitor from IBM gives manufacturers the chance to move into the next phase of the Internet of Things (IoT) evolution. The hard part will be everything else: Making sense of the data, revamping existing processes, and retraining technicians and engineers. IBM's Maximo Asset Monitor adds AI capabilities to the Maximo Suite to help companies do the above and move into another phase of digital transformation. Kareem Yusuf, general manager of the IBM IoT business unit, said IBM's goal for the Maximo Asset Monitor is for companies to draw insights and take action based on data from the assets that they're managing in Maximo. "We want to help clients get new data or make existing data understandable," he said.

IBM thrives on the complicated, asset-intensive part of the enterprise IoT market, according to Kareem Yusuf, GM of the company's Watson IoT business unit. From helping seaports manage shipping traffic to keeping technical knowledge flowing within an organization, Yusuf said that the idea is to teach artificial intelligence to provide insights from the reams of data generated by such complex systems. Predictive maintenance is probably the headliner in terms of use cases around asset-intensive IoT, and Yusuf said that it's a much more complicated task than many people might think. It isn't simply a matter of monitoring, say, pressure levels in a pipe somewhere and throwing an alert when they move outside of norms. It's about aggregate information on failure rates and asset planning, that a company can have replacements and contingency plans ready for potential failures.