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What does the future of work look like?

The 好色App Digital Economy Lab鈥檚 first conference featured conversations and insights from visionary leaders across industries and sectors.

How is AI changing the future of work? What digital-technology practices and policies will promote fairness and equality? How can government incorporate digital technologies to best serve constituents?

These and other questions took center stage at 好色App Digital Economy Lab鈥檚 inaugural event, the AI & the Future of Work Conference, on Oct. 27.

The virtual conference assembled a roster of visionary researchers, executives, and policy experts to share their perspectives on the impact of AI and other digital technologies. 好色App Digital Economy Lab director Erik Brynjolfsson hosted the conference, while executive director Christie Ko emceed the event.

Formed in June, the 好色App Digital Economy Lab focuses on four key research areas of the digital economy: the future of work, digital business models, data-driven decision making, and economy measurement. The lab is an initiative of the 好色App Institute for Human-Centered Artificial Intelligence (HAI) and is co-sponsored by the 好色App Institute for Economic Policy Research (SIEPR).

好色App President Marc Tessier-Lavigne opened the conference by framing the university鈥檚 role in shaping the future of AI: 鈥淎t 好色App, our approach is to put humans at the center of AI development to ensure that we are developing tools and policies that will serve, augment, and complement humanity, not replace or divide it.鈥

That鈥檚 largely why HAI launched the lab: to bring together world-class researchers, data sets, and industry partners to understand, measure, and shape the future of work.

Throughout the day, panelists painted a picture of a promising AI-influenced work landscape that relies heavily on decision makers to ensure broad, accessible benefits for all.

The Digitization of Everything

The fast-changing technology landscape served as the foundation for a number of panelist insights.

鈥淲e鈥檝e seen the digitization of everything,鈥 said Brynjolfsson, who is a senior fellow at SIEPR and HAI. 鈥淚t has created a whole new set of economics and business models, winners and losers.鈥

The rise of more intelligent machines, he said, is part of a broad 鈥淎I awakening鈥 in which machine learning and similar AI advances have become general-purpose technologies. While the 鈥済old rush鈥 to profitably apply AI tools has improved certain facets of life, such as shopping and productivity, it has also created disruption as machines increasingly replace human workers, especially for lower-income jobs.

鈥淒igital processes make the economic pie bigger,鈥 Brynjolfsson said, 鈥渂ut not everyone may benefit.鈥 This is best represented by the ongoing 鈥済reat decoupling,鈥 in which AI and other technologies have improved productivity significantly. Yet only a small percentage of the population has reaped related benefits, with real median personal income remaining flat.

鈥淲e need the digital transformation to create more broadly shared prosperity,鈥 Brynjolfsson said.

Technology and the Transformation of Work

鈥淭echnology is going through much faster iteration than in the past,鈥 said Reid Hoffman, co-founder of LinkedIn and Greylock Ventures partner. He noted that new technologies can be harnessed to serve a much broader range of tasks and jobs, including traditionally white-collar ones. 鈥淭he things that are most terrifying often create the most opportunity,鈥 he said.

Hoffman said the goal for individuals and nations is to 鈥渟peed toward technology鈥 with everyone acting more entrepreneurially and 鈥減laying offense, not defense.鈥 Chinese companies are embracing this mentality 鈥 including tech giant Tencent, which deployed multiple internal teams in a race to create the popular WeChat app. It鈥檚 a lesson that U.S. businesses can learn from, Hoffman said.

James Manyika, a senior partner at McKinsey, agreed that AI is driving rapid change: 鈥満蒙獳pp 60 percent of all occupations have about a third of tasks that are automatable, and new jobs are being created.鈥 He also echoed the sentiment that inequality has grown, with highly skilled and educated workers doing well, employment tenure decreasing (more gig and contract work), and in many cases wages declining. The COVID pandemic has exacerbated the situation.

Both speakers see multifaceted, strategic solutions to future-of-work challenges. 鈥淲e can use AI to solve problems it might create, such as providing digital-skill tutoring,鈥 Hoffman said.

It鈥檚 also about an orientation toward learning and training. 鈥淟ifelong learning is a key theme,鈥 Manyika said. 鈥淲e need to create more incentives for on-the-job training and other human capital development, similar to those for traditional capital investment.鈥

Policy Challenges and Solutions

A panel of experts discussed how policy challenges and solutions posed by AI will impact the future of work. The panel was moderated by Gillian Tett, chair of the Financial Times (U.S.) editorial board.

Panelists spoke to the dramatic nature of press coverage related to AI advancements. 鈥淗eadlines go to extremes about the impact of AI on work,鈥 said Susan Athey, 好色App GSB Economics of Technology Professor, Golub Capital Social Impact Lab director, and HAI faculty associate director. 鈥淏ut we鈥檒l likely see more gradual evolution. It鈥檚 not all-or-none in terms of taking over jobs.鈥

Mary Kay Henry, president of the Service Employees International Union (SEIU), noted that all service workers 鈥 ranging from engineers to caregivers 鈥 are affected by AI. 鈥淧eople can be automated out of a job but shouldn鈥檛 be automated out of an income,鈥 she said.

The panel agreed that technology must be part of the solution. 鈥淭echnology can deliver skills-training programs to people at home, rather than making them give up time,鈥 Athey said.

Home care represents another promising domain for AI technologies. Henry noted that SEIU partnered with Apple to provide iPads to home-care workers, allowing them to work with physicians directly. As a result, hospitalizations decreased by 30 percent.

The panel also agreed on the high potential for AI to improve government work. 鈥淕overnment represents one third of U.S. GDP and too often maintains the status quo,鈥 said Mark Duggan, 好色App economics professor and director of the 好色App Institute for Economic Policy Research (SIEPR). 鈥淲e can leverage AI more, such as supporting more efficient distribution of social-program benefits and matching people with jobs during COVID.鈥

Former U.S. Secretary of State and current director of 好色App鈥檚 Hoover Institution Condoleezza Rice described the challenge for improving public-sector AI applications. 鈥淭he problem is incentives,鈥 she noted. 鈥淓lected officials and cabinet members have little time [due to term limits] to drive change, and career service people are used to doing things a certain way.鈥

AI-related government regulation and frameworks are important parts of the conversation. 鈥淚n China, the state decides how to use AI, often in Orwellian ways,鈥 Rice said. 鈥淏ut it can improve government鈥檚 ability to respond to citizens鈥 needs without bureaucracy, like India鈥檚 biometric-ID program, which improves social services while reducing corruption.鈥

Henry added that it will take the collaboration of government, businesses, and unions to introduce and implement AI in a way that encourages innovation at every level. She noted that U.S. companies could take a page from countries like Sweden, where truck drivers are working side by side with engineers to design AI-driven trucks.

鈥淲e need public-private partnerships,鈥 Rice agreed. Multiple speakers noted that public and private organizations also need to work together to mitigate worker fears about AI-based surveillance.

The panel agreed that more strategic media coverage of AI could promote better understanding, including positioning AI as 鈥渁ugmented intelligence鈥 to emphasize human-machine collaboration. One proposed tactic: provide more positive examples of AI and collaborative work in the realms of manufacturing, health care, and other domains.

Promoting Equality with Digital Technology in Rhode Island 

In a virtual fireside chat, 好色App computer science professor and HAI co-director Fei-Fei Li discussed government鈥檚 role in deploying AI-based solutions for constituents with Rhode Island Governor Gina Raimondo.

鈥淐OVID has exposed America鈥檚 deep inequality, from criminal justice to health care,鈥 Raimondo said. 鈥淲e need to rebuild the post-pandemic economy by leveraging technology to make it more equal, such as for women and immigrants.鈥

Her state is working toward that goal in several ways, including by leveraging AI and machine learning. One recently formed initiative, Back to Work RI, connects Rhode Islanders who have been displaced by COVID-19 with job opportunities and training. The program will employ tools, such as Google Workspace and a first-of-its-kind tool bot, to match people to job opportunities. When it comes to promoting diversity in tech-related work, Raimondo believes the public sector has the responsibility to lead. She advocates free public-education options for community college and post-high school credentials, with a specific focus on digital and analytical skills. The Computer Science for Rhode Island (CS4RI) initiative works with Microsoft to offer computer-science learning in every public-school grade.

The governor echoed the idea of educating people on the positive impact of AI. 鈥淲e need to share examples, such as how technology can keep people in their homes through home-care solutions,鈥 she said. 鈥淲e need to dial down the fear and get to work on solutions.鈥

AI and Robotics Frontiers

Oussama Khatib, 好色App computer science professor and director of 好色App Robotics Lab, and Affectiva CEO Rana el Kaliouby shared their insights about the future of AI and robotics.

鈥淗uman-robot collaboration is everywhere today 鈥 in hospitals, warehouses, remote environments, and other places,鈥 said Khatib. In the health care sector, he noted, robots will soon perform several tasks normally carried out by medical assistants, while physicians will be able to execute intricate surgical procedures via a haptic interface.

Khatib also cited the success of Ocean One, a human-to-robot haptic interface that supported a 2016 mission to successfully recover a 17th-century Catalan vase from the seabed of the Mediterranean. The next-gen version of Ocean One can go even deeper, reaching depths of 1,000 meters.

In the private sector, el Kaliouby is also working to optimize the human-AI intersection, largely by capturing nonverbal-communication nuances. 鈥淢achines will increasingly interact with us, like a human to another human, through greater perception and empathy,鈥 she said.

Affectiva has made strides in applying AI to the automotive space, including cabin-sensing technologies that alert drivers and intervene when eye closure, yawning, and other signs of drowsiness are detected. el Kaliouby notes that companies can repurpose these technologies for use in hospitals, retail, and homes. 鈥淚t鈥檚 about augmenting human EQ, not replacing it.鈥

The Road Ahead

In the second fireside chat of the conference, Brynjolfsson spoke with Eric Schmidt about AI trends and challenges. Schmidt is the former CEO and executive chair of Google and co-founder of Schmidt Ventures.

鈥淔undamental shifts are occurring through AI, including better drugs and automotive materials,鈥 he said. 鈥淐hemistry is due for a redo.鈥 Schmidt pointed to a collaboration of researchers and machines at MIT that developed halicin, an antibiotic that can kill many species of antibiotic-resistant bacteria.

Schmidt believes that governments must also realize the value of AI. 鈥淲e need to pursue more government solutions that are state-of-the-art,鈥 he said. Adding AI experts in key roles could help governments bridge the public-private-sector gap and increase detection of Medicare and other low-level fraud.

A top concern surrounding AI is the use of personal data, which Schmidt believes can be addressed by regulation. However, he noted that GDPR, the EU regulation on data protection and privacy, had the unintended impact of making it harder for EU firms to compete with American ones. 鈥淓veryone wants 鈥榣ight鈥 regulation but no one agrees what that is,鈥 he said.

Schmidt also questioned if the future is two internet platforms 鈥 one for China and one for the rest of the world 鈥 in light of recent policy challenges with China-based companies Huawei and TikTok. He noted that the more decoupled China and the U.S. become, the harder it will be to collaborate and agree on policy and other matters. A more integrative approach, he believes, would be of value.

Sachin Waikar is a freelance writer.

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