2: Digital Technology is Fundamentally Transforming the Nature of Work

“Our city of the future must also be one where people have access to opportunity and jobs.” –Mayor Durkan

Contemporary advances in digital technology, enabled by big data, artificial intelligence, and machine learning, are altering the way that work is done in organizations of all kinds, including in the public sector. While adapting to technology has been a consistent challenge since the Industrial Revolution, these advancements represent unprecedented leaps in telecommunications, logistics and The World Economic Forum notes that four particular technologies will be critical drivers of business growth and transformational economic shifts: ubiquitous high speed and mobile internet, artificial intelligence, widespread adoption of big data analytics, and cloud technology. 1 Workforces, the Forum continues, will be affected along two parallel fronts: 1) large-scale decline in roles whose tasks become fully automated or redundant, 2) large-scale growth in new products and services, and in turn jobs, from the adoption of new technologies and other socio-economic developments. 2 supply chains, and financial services, to name a few. In turn, there are substantial opportunities for improved productivity and enhanced job fulfilment, just as there are challenges with such changes. As the City of Seattle prepares its municipal workforce for the future, it is critical to understand the national, and indeed global, trends driving changes in the labor market. This section of the report examines such trends, provides a framework for their impact on workers, and identifies how these shifts will impact public

Global trends in technological change

sector work.

Digital technologies have applications. broad

Advances in technology have enabled the development of artificial intelligence and machine learning, which continue to reach new frontiers. This report focuses on the applications of such technologies for the provision of public services and the subsequent impacts on City employees that manage these services. When discussing these digital technologies throughout the report, we are referring to the following: 3,4

Artificial Intelligence (AI): the ability of computer programs/machines to

discern patterns and generate predictions from large data sets, to emulate and perform human tasks. Machine Learning (ML): a subset of AI that trains a machine how to learn based on large data sets and examples to create algorithms that increase accuracy and performance, without specific coding from humans. Automation: the creation and application of technology to monitor and control production and delivery of products and services. Big Data: large volumes of data (structured and unstructured) that is so large, fast, or complex that it is difficult or impossible to process using traditional methods. The applications of these technologies are substantial: predictive analytics, autonomous systems, and robotics, to name a few. Automation is of key concern because of the potential of many occupation-specific tasks performed by humans to be impacted.

Effects on productivity and employment are difficult to predict.

Predictions on the rate of technological adoption vary and scenarios abound on how such adoption will affect the labor market in the long-term. While the equivalent of millions of jobs are potentially automatable with today’s technology 5 , traditionally the automation of tasks has also resulted in the creation of additional jobs—in the United States, this has proved consistent since the 1940s. Further historical perspective is helpful to contextualize such trends. Labor economists David Autor and Anna Salomons find that “technological progress has been broadly employment-augmenting and labordisplacing for at least three decades.” 6 They find that shifts towards labordisplacing technologies in the 1980s affected the decline in labor’s share of value added, a dynamic that accelerated substantially in the 2000s. Nevertheless, they note that this subsequent acceleration cannot solely be attributed to technological changes. Aggregate employment and productivity levels are important to consider, but there is also significant variation between industries. Subsequent research on specific technologies may help to shed light on more nuanced industry-or time-specific trends.

The impacts of technology on people and places will be uneven.

The benefits of enhanced productivity and job creation, perhaps unsurprisingly, do not accrue evenly. Many experts believe current trends in automation will increase gaps in the United States across existing cleavages: high-growth cities vs. struggling rural areas, and high-wage vs. low-wage workers, among others. 7 Indeed, Carnegie Mellon economist Lee Bransetter cautions that policymakers should be less concerned about mass unemployment but rather about growing inequalities along a “pronounced skills bias.” 8

Seattle, a high-growth city, has experienced impressive economic growth and population increases in recent years, but challenges remain on

how to promote increased economic opportunity for all residents. Though the State of Washington is on track to add 740,000 job openings in the next five years 9 , such challenges in access will likely continue. The City government will need to incorporate macro-level trends into its workforce development strategies, as its own employees will necessarily be impacted. In short, continued automation will affect the structure of the labor force The Future of Work is both a continuation and an acceleration of trends in the economy. This section provides a framework for understanding how such trends affect workers.

Automation affects tasks.

Because jobs are comprised of many activities, a task-based framework allows researchers to analyze the susceptibility of particular tasks to automation, and to understand the resulting labor impacts. Automation represents an unrivaled opportunity to change the nature of work in positive ways, particularly in terms of how workers spend their time and businesses allocate costs. Automation can improve the quality of the good or service being produced, reduce or eliminate mundane tasks, and reduce businesses’ operations costs. For example, General Electric implemented machine learningenabled automation by integrating supplier data to their contract over time, in uneven ways. While harnessing these technologies allows for positive economic growth, policymakers can promote inclusive growth in the face of long-term shifts by “connecting displaced workers with new opportunities, equipping people with the skills they need to succeed, revitalizing distressed areas, and supporting workers in transition.” 10 The responses to technology-driven shifts, may be as consequential as the shifts

Effects of Technological Change on Workers

themselves. negotiation processes, generating $80 million in savings in its first year. 11

Importantly, even though aspects of jobs can be automated, the nature of work will also change based on the tasks that remain. For example, in the public sector, the US Patent and Trademark Office has piloted AIassisted searches for initial patent reviews, and workers increased their productivity due to the enhanced inputs they received. 12

The McKinsey Global Institute finds that “less than 5 percent of occupations can be automated in their entirety, but within 60 percent of jobs, at least 30 percent of activities could be automated by adopting currently demonstrated technologies.” 13 Of course, these are averages and the impacts of automation differ across industries and occupations. Further in the report, we provide such estimates for the City government’s workforce.

Routine Tasks are at greatest risk.

Continued advances in such technologies will facilitate increasing automation of many routine, predictable physical and cognitive tasks. Because routine tasks follow precise, wellunderstood procedures, they are more easily codified by algorithms. Routine tasks tend to be characteristic of many mid-wage occupations and, as researchers from MIT assert, “there has been an employment decline across clerical, administrative, support, production, and operations tasks.” 14 Despite predictions of overall job growth and new occupations from technological adoption, the “hollowing out” of middle-wage jobs across the economy is expected to continue. 15 In addition, demand is expected to increase for high skill and certain types of low skill jobs that are, in turn, more difficult to automate (e.g. health care workers, therapists and social workers, teachers, caretakers). Nevertheless, there are still myriad aspects of workers’ tasks that cannot be distilled into predictable rules, because they rely on physical flexibility, common sense, judgment, intuition, and creativity. With present technologies, humans retain significant comparative advantage for many jobs. Activities in many jobs will also be enhanced, and new responsibilities will emerge, rather than entire occupations becoming completely obsolete in the near term. For example, humanmachine pairing can create new responsibilities and workers can take advantage of opportunities to apply their skills and competencies to new or related roles. In turn, workers will need to be trained to be more productive alongside software, platforms, etc., particularly to take advantage of the quality improvements that humanmachine pairings generate. We understand, over time, that demand will decrease for occupations that have more automatable portions, while demand will increasefor jobs with tasks less susceptible to automation.

STEM and Problem-Solving Skills will be in Demand.

Given the trends that favor high-skilled workers at the forefront of the knowledge economy, markets and employers will continue to reward science, technology, engineering, and math (STEM) based skills. Demand will also increase for social and emotional skills, as well as for higher skills linked to creativity and complex information processing. 16

Roles with substantial expected growth include data analysts and scientists, software and applications developers, AI and ML specialists, big data specialists, process automation experts, and robotics engineers. On the other hand, roles such as customer service workers, marketing professionals, and organizational development specialists will also see increased demand. 17 C-suite executives surveyed by the Boston Consulting Group and Harvard Business School note that recruiting workers with the requisite skills (e.g. hard skills, such as STEM-based skills, and “soft” social and emotional skills) for ever-changing jobs is their highest

priority for managing the future of work. 18

Reskilling Workers is Imperative.

To be successful, workers will need to adapt to new demands and task composition. Governments and firms need to substantially invest in training and reskilling. By some estimates, “by 2022, no less than 54% of all employees [worldwide] will require significant re- and up-skilling. Of these, about 35% are expected to require additional training of up to 6 months, while 10% will require additional skills training of more than one year.” 19 In addition, on-the-job training can equip workers with task-specific skills or complementarities, in scenarios where the nature of their work is complemented alongside AI-supported technologies. 20

Failing to equip workers with the skills necessary for success in an everchanging economy will have significant repercussions: employers would be forfeiting additional productivity, and workers will be less likely to grow professionally and continue to contribute to the economy. The public and private sectors need to invest substantially in workforce training to increase employees’ ability to succeed in this competitive and changing landscape.

Applying a RSJEI Lens is Key to Mitigate Disparate Impacts.

Changes to the labor market will be particularly consequential for people of color and underrepresented groups in the United States, as analyses show that younger, less educated, and underrepresented minorities work in more automatable occupations. 21 In turn, many low-resourced communities do not have sufficient resources (for example, extra time, financial or family net worth) to finance continued education or independent training, making the role that government and industry can play in reskilling critical. Moreover, such groups are traditionally underrepresented in STEM occupations, which further limits future prospects. According to the Brookings Institution, “average automation potential for U.S. occupations requiring less than a bachelor’s degree is 55 percent, more than double the 24 percent susceptibility among occupations that require a bachelor’s degree or more.” 22 In addition, “African Americans could experience the disruptive forces of automation from a distinctly disadvantaged position, partially because they are often overrepresented in the ‘support roles’ that are most likely to be affected by automation (e.g. truck drivers, food service workers, office clerks).” 23 Relatedly, the Hispanic/Latino population has a job displacement rate (percentage of jobs potentially lost due to automation by 2030) of 25.5 percent, slightly outpacing the African American rate of 23.1 percent. 24

Firms and government should apply RSJEI lens to future of work strategies, to ensure that policies address inequities that can result along socioeconomic and demographic lines.

The public sector must harness automation to fulfill its mission over the long-term

While the private sector is at the forefront of technological adoption, it is imperative that the public sector keep up so it can provide the best quality service at the most reasonable cost.

Digital technology will transform how the public sector fulfills its mission.

IBM and the Partnership for Public Service find that, at the federal level, AI will impact government by transforming the federal workday, personalizing customer service, and increasing demand for technical and data skills. 25 Deloitte finds that the Future of Work in Government will evolve in the following categories 26 : •

Work: public sector employees can create more value for constituents, and enhance their own workplace satisfaction. Scenarios with humanmachine pairing will become increasingly common.

Workforce: government can take advantage of more varied work arrangements by accessing varied pools of skills and capabilities.

Workplace: technologycan change physical workspaces and arrangements (e.g. remote work), which can promote employee satisfaction and productivity.

Effects on public sector workers need to be considered.

Being intentional and critical with regards to technology adoption necessarily means employing a workercentric lens. Engaging relevant stakeholders, particularly the actual workers, and their representatives (e.g. unions), is a critical first step for these analyses. Such considerations are especially key for entry-level and public-facing workers, whose jobs may have more tasks susceptible to automation. Working with partners at the state level to strengthen regional strategies is another opportunity for the City. The Washington State Future of Work Taskforce’s 2019 Policy Report calls for comprehensive worker upskilling and lifelong learning, which the City can tap into for its own strategies.

Competition with the private sector for skilled workers will continue.

The challenge for governments is twopronged: competition with the private sector for human capital, and adequate workforce development. Accordingly, governments will need to increase investment in current and future employees by offering training and continuous education, fostering internal growth opportunities, and providing dynamic professional development. By leveraging its key assets, such as being a mission-driven organization, and improving upon its existing systems, the City can better compete with other top employers in Seattle. In turn, by designing a workforce development strategy that incorporates digital transformation, the City can prepare its employees for the evolving demands they will face.