When it comes to the threat or promise of automation, experts are divided as to whether AI and robotics will eliminate jobs en masse or merely automate rote tasks and free up more of workers’ time for innovation and creativity. McKinsey has put out some interesting research throughout the year in which they attempt to forecast the impact of these new technologies on the workforce. In January, they released the attention-grabbing headline finding that half of the work currently performed by humans could be automated with already-existing technology. Though fewer than 5 percent of jobs can be automated entirely, their research found, most jobs could have at least one third of their component tasks automated today.
In an update to that work published this week, McKinsey takes a closer look at the various factors that will drive automation in the coming decades—such as technical feasibility, cost of deployment, and labor market considerations—and concludes that “between almost zero and 30 percent of the hours worked globally could be automated by 2030, depending on the speed of adoption.” The effects will not, however, be evenly distributed among occupations:
Activities most susceptible to automation include physical ones in predictable environments, such as operating machinery and preparing fast food. Collecting and processing data are two other categories of activities that increasingly can be done better and faster with machines. This could displace large amounts of labor—for instance, in mortgage origination, paralegal work, accounting, and back-office transaction processing. … Automation will have a lesser effect on jobs that involve managing people, applying expertise, and social interactions, where machines are unable to match human performance for now.
At an event organized by the Jack Kemp Foundation last week, US Secretary of Labor Alexander Acosta expressed support for a speedy overhaul of US employment laws to account for the advent of the gig economy and the changing relationship between workers and employers today, Chris Opfer reported at Bloomberg BNA. The secretary said the government needed to “keep pace with the pace of change in the private sector” and “re-examine the rules that regulate the employer-employee relationships that have an impact on the ability of individuals to work in a modern system.”
Acosta’s concern reflects a growing understanding that the employment laws and regulations written in the 20th century don’t account for the way many people work today and in particular, that some new form of employment classification may be needed to reflect the situation of people like Uber and Lyft drivers, who work as independent contractors but resemble regular employees in many aspects. The rights and obligations of these individuals and the platforms through which they find work are currently a legal gray area, being defined in the courts through litigation rather than by Congress.
That US employment laws need updating to account for today’s very different labor economy is not especially controversial, but what those updates should look like is hotly debated: Labor activists want gig economy workers to enjoy the same protections as traditional employees and progressive gig economy companies want a new social safety net for these workers based on portable benefits, whereas other businesses and lobbying groups want to limit regulation of this emerging economy as much as possible.
The annual Freelancing in America survey, released this week by Upwork and the Freelancers Union, paints a picture of a freelance workforce that is growing much faster than the US workforce in general. The report estimates the total number of US freelancers today at 57.3 million, or 36 percent of the total American workforce. That number has grown more than three times faster than the overall workforce in the past three years, and if this rate of change holds, freelancers are projected to compose a majority of the US workforce by 2027. Millennials are leading the trend in this direction, with 47 percent of millennial workers saying they freelanced.
The survey of over 6,000 US adults also finds that freelancers are doing better than their traditionally employed peers at preparing themselves for their professional futures: 55 percent of freelancers said they had engaged in some kind of re-skilling activity in the past six months, compared to 30 percent of regular workers. In general, 65 percent of freelancers said they were updating their skills as work evolved, while just 45 percent of others said so.
Freelancers are also feeling the impact of technological change more acutely, with 49 percent saying their work had already been affected by AI and robotics, against just 18 percent of full-time employees. At the same time, technology is also bringing them more work, with 71 percent saying the amount of work they had found online had increased in the past year.
Another interesting finding is that while many people lump freelancers in with the gig economy, freelancers don’t: Only 10 percent of freelancers in the survey said they considered themselves a part of that economy. Indeed, we’ve seen from other research that the gig economy, properly speaking—meaning workers who make a living through platforms like Uber—is just one component of the new trend toward contingent and temporary employment in the US labor market. Fast Company’s Ruth Reader considers why freelancers might be rejecting the “gig economy” label:
The advent of artificial intelligence and other previously unimaginable technologies has a lot of people worried about what work will look like in the future and whether the current workforce is prepared to survive the ongoing disruption of the economy. With that in mind, Google has announced a commitment to donate $1 billion in grants and 1 million hours of Googlers’ volunteer time over the next five years to nonprofit organizations dedicated to training US workers and building businesses for the future of work.
TechCrunch’s Brian Heater covers the announcement, which Google CEO Sundar Pichai made at an event in Pittsburgh — a place where the topics of economic disruption and technological displacement are very salient:
The location of the event will not be lost on anyone who has followed Pittsburgh’s growth over the last few decades. The Steel City has long served as an ideal example of an economy that’s rebounded from the brink of disaster. In Pittsburgh’s case, technology was a primary driver, thanks to Carnegie Mellon, which has helped transform it from post-Rust Belt depression to one of the country’s leading tech hubs. These days, the walls of Pittsburgh’s former factories house cutting-edge innovations in fields like robotics and autonomous driving. …
The company is committing $10 million to Goodwill as part of the initiative — the largest Google.org has committed to one organization. That money will be used to help launch the Goodwill Digital Career Accelerator, aimed at preparing the American workforce for high-tech jobs. Grow with Google also will take the form of a national tour hosted by libraries and community organizations aimed at bringing training and career advice directly to local towns and cities.
According to the announcement, the initiative’s overarching goal is to “give anyone in America the tools and training they need to get a job, for free”:
The recent news of Microsoft’s massive increase in headcount for its AI division indicates the company’s dedication to the technology that it believes will shape the future. The business unit was launched by CEO Satya Nadella a year ago to position the company for what he saw as a “paradigm shift in computing” of which he wanted Microsoft to be on the forefront.
“Microsoft is dedicated to democratizing AI for every person and organization, making it more accessible and valuable to everyone and ultimately enabling new ways to solve some of society’s toughest challenges,” the company wrote in an announcement at the time.
Having grown from 5,000 to over 8,000 employees, the AI and Research group now accounts for roughly 7 percent of the Seattle-based giant’s total workforce. So what is all that talent working on? What does Microsoft have to show for all this investment?
For starters, the investment goes far beyond human capital. Microsoft’s $26 billion acquisition of LinkedIn last year undoubtedly played a big role in the company building out its AI capabilities. An initial run of joint projects is underway, making it clear this merger aims to significantly reshape the way technology is used in the workplace, GeekWire’s Nat Levy reports:
Office 365 will include a new “profile card” that can display LinkedIn information. For example, interviewers using Outlook would be able to easily access LinkedIn profiles of job seekers. This integration, the first between Office 365 and LinkedIn since the acquisition, is designed to make it easier for people to search for others inside their organizations.
At our ReimagineHR summit in London on Thursday, CEB (now Gartner) Principal Executive Advisor Clare Moncrieff led a session on creating a common vision of digitalization for the business and HR. After examining hundreds of trends, our research councils serving chief HR officers and chief information officers have identified six deep shifts in the business environment that will result from digitalization. These shifts should act as the framework for heads of HR to:
- Ensure talent conversations with the line are grounded in business context
- Identify the current talent implications of these shifts, project future implications, and partner with the line and C-suite peers to prioritize and respond to each
- Improve their teams’ business acumen (to underscore the importance of this, 58 percent of HR business partners indicated in one of our surveys that building business acumen was their top development goal in 2017)
(The case studies we link to below are available exclusively to CEB Corporate Leadership Council members)
1) Demand Grows More Personal
As customers seek personalized products that align with their preferences and values as individuals (rather than as segments), companies will rely on digital channels and digital innovations in logistics and customer service to achieve personalization at scale. Customers will continue to expect lower-effort, nonintrusive service.
This could, for example, affect how HR functions look for new talent. Attraction of critical talent now requires differentiated, customized branding and career coaching. Candidates will demand a more effortless, personalized application experience. AT&T approached this shift by creating a more personalized “Experience Weekend” to show the innovation of its brand to campus candidates and make top talent more likely to accept job offers.
With the rapid advance of AI and machine learning technology, employers need talent with skills and knowledge in this field at a greater rate than university programs are able to churn them out. The imbalance of supply and demand has led to large, rich companies buying up all the AI startups and luring AI professors away from universities with much larger salaries. To address this issue and expand access to AI education, Stanford University professor and Coursera co-founder Andrew Ng has launched a new website, Deeplearning.ai, whose courses “offer coders without an AI background training in how to use deep learning, the technique behind the current frenzy of investment in AI,” Wired’s Tom Simonite reports:
“This sounds naive, but I want us to build a new AI-powered society,” Ng tells WIRED. “The only way to build this is if there are hundreds of thousands of people with the skills to do things like improve the water supply for your city or help resource allocation in developing economies.” Ng’s new courses cost $49 a month and are offered through online-education startup Coursera, which he cofounded in 2012 and where he still sits on the board. …
With his new courses, Ng is offering a solution to a problem he helped create. His prominence comes from work on deep learning at Stanford and Google’s X Labs that helped prove machine learning could do transformational things for businesses. In a 2012 paper, he and coauthors described a system that learned to recognize cats in still images from YouTube without human help. Now there aren’t enough people with machine learning skills to go around.
Ng’s motivation to launch Deeplearning also stems from his sense that people who don’t understand how AI works are afraid of it, which he thinks we shouldn’t be, Daniel Terdiman adds at Fast Company: Read more