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Pushing innovation boundaries: AI and human-machine interaction
Apr 16, 2019

“It's not just out of curiosity that people are going to robotics,” Bryant President Ronald K. Machtley told a group of faculty, administrators, and staff gathered for a community conversation about how the technological revolution is recreating industry, the workforce, and education. China plans “to spend $1 trillion by 2030 on artificial intelligence (AI)," he said. They are ramping it up because they see what's going to happen,” and they’re not the only ones, Machtley noted. 

In this, their second TEA Talk about the impact of the Fourth Industrial Revolution, President Machtley and Finance Professor Hakan Saraoglu, Ph.D., discussed “Developing Human Capital in the Fourth Industrial Revolution,” and how game-changing breakthroughs in artificial intelligence, quantum computing, robotics and other fields will reshape the world. The transition, they suggested, has started – and we need to be prepared.

“I think in the next 10 to 15 years, AI is the technology that is going to be like electricity, going into everything we do.”

Futurists say that 85 percent of the jobs of the future have not yet been created and by 2022, there will be 75 million jobs lost and 133 million jobs created. “But,” Machtley added, “54 percent of those [jobs created] require new skills. And that's only three years from now.”

The changes brought about by the Fourth Industrial Revolution are already coming into effect, Machtley noted. Larry Page, the founder of Google, now says that the industry giant is not a search company, but an artificial intelligence company; Amazon’s 100,000 robots have a profound impact on commerce. By PwC’s estimates, artificial intelligence will represent a $15.7-trillion addition to our economy by 2030. “Their surveys show every business is starting this year to ramp it up,” he said.

Although AI is in the early stages of commercialization, Machtley said, 20 percent of companies have stated that they are starting to employ it in their work.  “I think in the next 10 to 15 years, AI is the technology that is going to be like electricity, going into everything we do,” Machtley said. He cannot predict exactly what role the machines of 2030 will play, but Machtley is certain that human beings will continue to be involved.

“How can we use AI to humanity’s benefit without taking the human out of the loop?"

Therein lies the challenge, suggests Saraglou. “To be disrupted ourselves, we have to be drawing a feedback loop of constantly monitoring the environment and coming up with ideas that will actually benefit from the disruption,” he said.

That means addressing key questions about both technology and humanity. “How can we use AI to humanity’s benefit without taking the human out of the loop? Without AI becoming an existential threat?” Saraoglu asked, pointing out that wide circles of difference makers and innovators around the world currently debate those questions. He believes that Bryant can best prepare graduates to make the most of the Fourth Industrial Revolution by focusing on human-machine interaction.

Taking the lead in preparing graduates

In light of the “future impact of rapid advances in artificial intelligence, robotics, block chain, the internet of things, and other emerging technologies,” Machtley has previously said, “it is clear that higher education must take the lead in preparing graduates for the many challenges and opportunities these developments will create.”

Bryant’s new interdisciplinary Data Science programs are an important piece of that puzzle, ensuring that "all of our graduates, regardless of their majors, possess the essential literacy required to understand how this emerging field can add value in a wide range of applications,” Machtley said. Students who major in Data Science, he noted, “will develop fluency in such disciplines as coding, the development of algorithmic functions, and data analytics – all of which will be critical to progress in the Fourth Industrial Revolution.”

“Higher education must take the lead in preparing graduates for the many challenges and opportunities these developments will create.”

Saraoglu, who studied to be a multidisciplinary engineer with an emphasis on computer programming, said that another key to success is developing a growth mindset that recognizes that learning something new is never the end of the process but simply “the beginning of what else to learn.”

The University can undertake a number of specific initiatives to inform its evolving curriculum, Saraoglu suggested, including:

  • encouraging multidisciplinary faculty collaboration and research projects; some relating to machine learning and data science have already begun;
  • establishing student-faculty collaboration projects where students take data, use programming to create useful information, analyze the information, and explain its significance through storytelling;
  • engaging in public-private partnership projects;
  • facilitating collaborations and machine-learning applications across disciplines;
  • exploring the digital humanities.

 

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