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Every workplace can be a place of continual learning

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Every workplace can be a place of continual learning


While businesses in every sector have been working toward a digital transformation for the past several years, covid-19 accelerated this shift across industries. New technologies are advancing at a pace that requires employers to continuously retrain their workforce to stay current. Organizations must become places of learning if they are to prepare workers for jobs of the future.

Joe Schaefer is Chief Transformation Officer at Strategic Education.

The World Economic Forum has published one estimate suggesting that technologies like artificial intelligence (AI) could displace 75 million jobs by 2022 but may also create 133 million new roles, and a study by IBM’s Institute for Business Value predicts as many as 120 million workers in the world’s 12 largest economies may need to be retrained in the next three years as a result of an increasing shift toward and embrace of automation and AI. This scale of retraining and workforce preparation requires a fundamental paradigm shift. For employers to thrive in this new digital area and stay one step ahead of competitors, they need to invest in the ongoing education of their employees. In turn, employees need to be encouraged and willing to continue to learn to advance at work.

While employers are beginning to recognize their role in reskilling and upskilling employees, they are not trained educators. For the workplace to successfully double as a place of higher learning, employers will need to build strong partnerships with higher education providers that offer flexible programs and incorporate innovative technologies to help support these working adult students as they achieve the next step in their career.

Here are three technologies that we have found support the success of busy, adult learners:

Virtual assistants. Time is a precious resource for those who are working and learning. Working students don’t have time being placed on hold or passed around to support staff to find answers to their administrative questions.

Virtual assistants in the online higher education setting can help students in a variety of areas, from their admission processes to class updates to assignment submission deadlines. They should be designed to also record interactions, create insights, capture analytics, and deliver a more personalized experience each time students engage with it.

Many of us have grown to rely on virtual assistants, such as Alexa or Google Home, to save us time and make our lives easier. Expanding their use to help facilitate ongoing learning makes a lot sense.

Predictive analytics. Predictive analytics is a powerful tool to help anticipate a student’s success in a course by drawing on the interplay between machine learning, AI, and other technologies to help adult learners persist. It allows higher education institutions to identify a learner who is struggling to complete assignments and perhaps at risk of dropping out of a program so that advisors, professors, and other support systems can intervene early with one-on-one support for the student. For employers partnering with higher education providers, this is a powerful tool to ensure their employees are on track to complete a program they have invested in.

These relatively simple nudges are important. Life can, and often does, get in the way of education for working adults, who may be juggling a family or other priorities at home, so reminders and offers of support go a long way in helping a student achieve their education goals.

Gamification techniques. Gamification places game mechanics—such as point systems and tracking, achievement levels, awards and prizes—into non-game situations. It is already part of our everyday lives, across many industries, like fitness class leaderboards and airline frequent flier programs. Studies have shown that gaming strategy motivates consistent participation and long-term engagement among users. For example, a study from Finland found that a simple gamification strategy of awarding badges to students in a post-secondary computer science course had a positive impact—a majority of students said that trying to achieve badges increased their motivation.

Higher education must embrace and invest in gamification technology to help promote good student behaviors and boost learning success.

Online learning can make student engagement challenging. Even before the pandemic hit and all coursework moved online, online instruction was scrutinized for its inability to keep students engaged and on track. Add these challenges on top of additional responsibilities for adult learners, such as work and caring for children, and engagement becomes even more challenging. Gamification is one way to help motivate adult learners and instill a sense of accountability and engagement, and it serves as a great foray into online learning for students new to this type of instruction, helping them get more comfortable with completing assignments online and nudging them to complete necessary tasks such as reading a syllabus or signing into the message boards.

Using technology to manage your training and benefits

If your employer offers tuition assistance or reimbursement programs as a perk, it likely has some sort of education management platform to manage the back-end operations like disbursal of benefits and program verification. But these platforms can oftentimes be clunky, with employers maneuvering between multiple interfaces for information regarding an employee’s education progress and spending, and employees figuring out which programs are covered under their tuition assistance benefits. Partnering with institutions that offer simple, easy to use platforms, like Workforce Edge, for tuition assistance programs may help encourage employees to take advantage of tuition benefits and make it easier for employers to better track their return on investment in these programs.

Work, a place of higher learning

As with any technology, it’s most important to keep the end user in mind. The busy, working adult is not the same as the 18-year-old who has just graduated high school and is ready to spend four years on campus. Training and reskilling programs for adult workers should be flexible, accessible, and engaging. With the right technology and educational partner, every employer can become a place of higher learning, helping their employees achieve career and economic mobility while staying one step ahead of their competition with a highly trained workforce.

For more information, visit workforceedge.com.

This content was produced by Strategic Education. It was not written by MIT Technology Review’s editorial staff.

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The Download: Introducing our TR35 list, and the death of the smart city

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JA22 cover


Spoiler alert: our annual Innovators Under 35 list isn’t actually about what a small group of smart young people have been up to (although that’s certainly part of it.) It’s really about where the world of technology is headed next.

As you read about the problems this year’s winners have set out to solve, you’ll also glimpse the near future of AI, biotech, materials, computing, and the fight against climate change.

To connect the dots, we asked five experts—all judges or former winners—to write short essays about where they see the most promise, and the biggest potential roadblocks, in their respective fields. We hope the list inspires you and gives you a sense of what to expect in the years ahead.

Read the full list here.

The Urbanism issue

The modern city is a surveillance device. It can track your movements via your license plate, your cell phone, and your face. But go to any city or suburb in the United States and there’s a different type of monitoring happening, one powered by networks of privately owned doorbell cameras, wildlife cameras, and even garden-variety security cameras. 

The latest print issue of MIT Technology Review examines why, independently of local governments, we have built our neighborhoods into panopticons: everyone watching everything, all the time. Here is a selection of some of the new stories in the edition, guaranteed to make you wonder whether smart cities really are so smart after all:

– How groups of online neighborhood watchmen are taking the law into their own hands.

– Why Toronto wants you to forget everything you know about smart cities.

– Bike theft is a huge problem. Specialized parking pods could be the answer.

– Public transport wants to kill off cash—but it won’t be as disruptive as you think.

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Toronto wants to kill the smart city forever

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Toronto wants to kill the smart city forever


Most Quayside watchers have a hard time believing that covid was the real reason for ending the project. Sidewalk Labs never really painted a compelling picture of the place it hoped to build. 

Quayside 2.0

The new Waterfront Toronto project has clearly learned from the past. Renderings of the new plans for Quayside—call it Quayside 2.0—released earlier this year show trees and greenery sprouting from every possible balcony and outcropping, with nary an autonomous vehicle or drone in site. The project’s highly accomplished design team—led by Alison Brooks, a Canadian architect based in London; the renowned Ghanaian-British architect David Adjaye; Matthew Hickey, a Mohawk architect from the Six Nations First Nation; and the Danish firm Henning Larsen—all speak of this new corner of Canada’s largest city not as a techno-utopia but as a bucolic retreat. 

In every way, Quayside 2.0 promotes the notion that an urban neighborhood can be a hybrid of the natural and the manmade. The project boldly suggests that we now want our cities to be green, both metaphorically and literally—the renderings are so loaded with trees that they suggest foliage is a new form of architectural ornament. In the promotional video for the project, Adjaye, known for his design of the Smithsonian Museum of African American History, cites the “importance of human life, plant life, and the natural world.” The pendulum has swung back toward Howard’s garden city: Quayside 2022 is a conspicuous disavowal not only of the 2017 proposal but of the smart city concept itself.

To some extent, this retreat to nature reflects the changing times, as society has gone from a place of techno-optimism (think: Steve Jobs introducing the iPhone) to a place of skepticism, scarred by data collection scandals, misinformation, online harassment, and outright techno-fraud. Sure, the tech industry has made life more productive over the past two decades, but has it made it better? Sidewalk never had an answer to this. 

 “To me it’s a wonderful ending because we didn’t end up with a big mistake,” says Jennifer Keesmaat, former chief planner for Toronto, who advised the Ministry of Infrastructure on how to set this next iteration up for success. She’s enthusiastic about the rethought plan for the area: “If you look at what we’re doing now on that site, it’s classic city building with a 21st-century twist, which means it’s a carbon-neutral community. It’s a totally electrified community. It’s a community that prioritizes affordable housing, because we have an affordable-housing crisis in our city. It’s a community that has a strong emphasis on green space and urban agriculture and urban farming. Are those things that are derived from Sidewalk’s proposal? Not really.”

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Rewriting what we thought was possible in biotech

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Rewriting what we thought was possible in biotech


What ML and AI in biotech broadly need to engage with are the holes that are unique to the study of health. Success stories like neural nets that learned to identify dogs in images were built with the help of high-quality image labeling that people were in a good position to provide. Even attempts to generate or translate human language are easily verified and audited by experts who speak a particular language. 

Instead, much of biology, health, and medicine is very much in the stage of fundamental discovery. How do neurodegenerative diseases work? What environmental factors really matter? What role does nutrition play in overall human health? We don’t know yet. In health and biotech, machine learning is taking on a different, more challenging, task—one that will require less engineering and more science.

Marzyeh Ghassemi is an assistant professor at MIT and a faculty member at the Vector Institute (and a 35 Innovators honoree in 2018).

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