The Rise of AI Demands Project-Based Learning

By Katie Vander Ark & Tom Vander Ark

Artificial Intelligence (AI) is on the rise. Life with smart machines is rapidly affecting the way we live and work. A visual signal is the number of companies mentioning it.

Five recent interviews about the rise of AI point to the importance of self-directed learning–lifelong, often project-based, and, when possible, with a diverse team.

Humbly Curious

Kevin Jones, a cancer researcher, describes his work as “taking a bath in uncertainty and unknowns and exceptions and outliers.” School administrators can relate. Dr. Jones suggests the two most important values, given the level of uncertainty in his line of work, are humility and curiosity.

In a recent interview Jones said, “If I am humble and curious when a patient asks me a question and I don’t know the answer, I’ll ask a colleague who may have a similar albeit distinct patient…Those patients will start to talk to each other…[and] it’s through this kind of humbly curious communication that we begin to try and learn new things.” He believes that the curiosity and collaboration drives them all to continue to learn from one another.

We may not always have the answers, but by remaining humble and curious in the classroom, we “all become scientists” as Jones suggests.

Max Mix Teams

“Artificial intelligence and machine learning are taking over jobs that don’t require as much creativity,” said Joi Ito, MIT Media Lab. That’s why he advocates for the 4Ps: projects, peers, passion and play. “We know project-based learning is more effective than texbook-based learning,” said Ito. He added that interest-driven learning is more motivating and better retained. He reflected that “school is almost the opposite of these four,” noting that peer learning is often called cheating and play is relegated to recess (if that’s still around).

The work of the Media Lab is interdisciplinary or multidisciplinary. Ito thinks (like New Tech Network) interdisciplinary projects would be a good way to organize school.

The Media Lab team finds the benefit in building diverse teams–not just race and gender, but professional framework and experience–is that people will require different frames for problem-solving and design. Diverse teams are particularly important for creative problem-solving.

Joi Ito, MIT Media Lab said, “Artificial intelligence and machine learning is changing every year. We need an education system that is dynamic, that changes every year–and it’s got to be lifelong learning. While AI offers great opportunity, notes Ito, “there is tremendous risk associated with an education system that is not keeping up with tools that empower people.”

Thinking Differently

After the release of a well-written report from the White House on the implications of AI, Joi Ito discussed AI with President Obama. He said that AI is already requiring people to think differently about their work and learning. He suggested we need to pay the caring professions (teaching and nursing) more, consider new social constructs (like a basic income). Obama made a great case that it’s time to #AskAboutAI.

Messing Around

Interest-based learning may look like messing around to adults, but the result of a three-year ethnographic investigation by Joi’s sister Mizuko Ito makes the case for more interest-based learning.

Hanging Out, Messing Around, Geeking Out explores informal learning and peer influences. Ito and colleagues found that learning is more social and cultural than influenced by delivery. Her research reinforced Joi’s interest in passion-driven learning.

Augmented Intelligence

Fareed Zakaria interviewed Ginni Rometty this year at the 2017 Davos Summit. Rometty explained that the IBM supercomputer Watson has been a part of the rise of computing, the rise of data, and mobility. She explained it is helping them to be responsible leaders in the field, especially in regards to healthcare, transportation and education.

Rather than programing computers, we can feed them millions of data point–like everything written in a particular language or on a particular disease–and AI can learn the language and the science.

Rometty prefers to describe this experience with the machines as augmented human intelligence as opposed to artificial intelligence. “For the foreseeable future, AI will augment human intelligence,” said Rometty.

Early applications of Watson in education recommend the next best step in a learning progression. Soon it will guide interest-based learning–it may recognize a potential area of interest before you do.

Takeaways

1. Interdisciplinary project-based learning is motivating, effective and relevant to workplace challenges. At least some learning should be interest-driven.
2. Schools need to be as adaptive as workplaces in terms of ends and means. Setting aside time to explore a forecast framework can be valuable.
3. Civic capacity will also need to be more adaptive: policy lags in regards to AI. Lawyers need to learn more about technology and scientists need to learn more about ethical and legal issues.
4. ”Bathing in uncertainty and complexity” teaches humility and curiosity. School administrators should host a community conversation about how the world has changed.

For more, see:

• Design Thinking as Pedagogy For Students and Educators
• AskAboutAI: Informing Parents, Teachers and Policymakers About Life with Smart Machines
• Tell Kids to Get Good At Stuff Smart Machines Can’t Do (Yet)
• Living With Smart Machines

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