Book by Thomas H. Davenport and Steven M. Miller: “This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers.These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems…(More)”.
A Massive LinkedIn Study Reveals Who Actually Helps You Get That Job
Article by Viviane Callier : “If you want a new job, don’t just rely on friends or family. According to one of the most influential theories in social science, you’re more likely to nab a new position through your “weak ties,” loose acquaintances with whom you have few mutual connections. Sociologist Mark Granovetter first laid out this idea in a 1973 paper that has garnered more than 65,000 citations. But the theory, dubbed “the strength of weak ties,” after the title of Granovetter’s study, lacked causal evidence for decades. Now a sweeping study that looked at more than 20 million people on the professional social networking site LinkedIn over a five-year period finally shows that forging weak ties does indeed help people get new jobs. And it reveals which types of connections are most important for job hunters…Along with job seekers, policy makers could also learn from the new paper. “One thing the study highlights is the degree to which algorithms are guiding fundamental, baseline, important outcomes, like employment and unemployment,” Aral says. The role that LinkedIn’s People You May Know function plays in gaining a new job demonstrates “the tremendous leverage that algorithms have on employment and probably other factors of the economy as well.” It also suggests that such algorithms could create bellwethers for economic changes: in the same way that the Federal Reserve looks at the Consumer Price Index to decide whether to hike interest rates, Aral suggests, networks such as LinkedIn might provide new data sources to help policy makers parse what is happening in the economy. “I think these digital platforms are going to be an important source of that,” he says…(More)”
The New ADP National Employment Report
Press Release: “The new ADP National Employment Report (NER) launched today in collaboration with the Stanford Digital Economy Lab. Earlier this spring, the ADP Research Institute paused the NER in order to refine the methodology and design of the report. Part of that evolution was teaming up data scientists at the Stanford Digital Economy Lab to add a new perspective and rigor to the report. The new report uses fine-grained, high-frequency data on jobs and wages to deliver a richer and more useful analysis of the labor market.
Let’s take a look at some of the key changes with the new NER, along with the new ADP® Pay Insights Report.
It’s independent. The key change is that the new ADP NER is an independent measure of the US labor market, rather than a forecast of the BLS monthly jobs number. Jobs report and pay insights are based on anonymized and aggregated payroll data from more than 25 million US employees across 500,000 companies. The new report focuses solely on ADP’s clients and private-sector change…(More)”.
Reorganise: 15 stories of workers fighting back in a digital age
Book edited by Hannah O’Rourke & Edward Saperia: “In only a decade, the labour market has changed beyond all recognition – from zero-hour contracts to platform monopolies. As capitalism has re-created itself for the digital age, so too must the workers whose labour underpins it.
From a union for instagram influencers to roadworkers organising through a Facebook Group, former WSJ journalist Lucy Harley-McKeown takes us on a journey to discover how workers are fighting back in the 21st century…(More)”.
The fear of technology-driven unemployment and its empirical base
Article by Kerstin Hötte, Melline Somers and Angelos Theodorakopoulos:”New technologies may replace human labour, but can simultaneously create jobs if workers are needed to use these technologies or if new economic activities emerge. At the same time, technology-driven productivity growth may increase disposable income, stimulating a demand-induced employment expansion. Based on a systematic review of the empirical literature on technological change and its impact on employment published in the past four decades, this column suggests that the empirical support for the labour-creating effects of technological change dominates that for labour-replacement…(More)”.
The Rise of the Worker Productivity Score
Jodi Kantor and Arya Sundaram in The New York Times: “Across industries and incomes, more employees are being tracked, recorded and ranked. What is gained, companies say, is efficiency and accountability. What is lost?…
In lower-paying jobs, the monitoring is already ubiquitous: not just at Amazon, where the second-by-second measurements became notorious, but also for Kroger cashiers, UPS drivers and millions of others. Eight of the 10 largest private U.S. employers track the productivity metrics of individual workers, many in real time, according to an examination by The New York Times.
Now digital productivity monitoring is also spreading among white-collar jobs and roles that require graduate degrees. Many employees, whether working remotely or in person, are subject to trackers, scores, “idle” buttons, or just quiet, constantly accumulating records. Pauses can lead to penalties, from lost pay to lost jobs.
Some radiologists see scoreboards showing their “inactivity” time and how their productivity stacks up against their colleagues’. At companies including J.P. Morgan, tracking how employees spend their days, from making phone calls to composing emails, has become routine practice. In Britain, Barclays Bank scrapped prodding messages to workers, like “Not enough time in the Zone yesterday,” after they caused an uproar. At UnitedHealth Group, low keyboard activity can affect compensation and sap bonuses. Public servants are tracked, too: In June, New York’s Metropolitan Transportation Authority told engineers and other employees they could work remotely one day a week if they agreed to full-time productivity monitoring.
Architects, academic administrators, doctors, nursing home workers and lawyers described growing electronic surveillance over every minute of their workday. They echoed complaints that employees in many lower-paid positions have voiced for years: that their jobs are relentless, that they don’t have control — and in some cases, that they don’t even have enough time to use the bathroom. In interviews and in hundreds of written submissions to The Times, white-collar workers described being tracked as “demoralizing,” “humiliating” and “toxic.” Micromanagement is becoming standard, they said.
But the most urgent complaint, spanning industries and incomes, is that the working world’s new clocks are just wrong: inept at capturing offline activity, unreliable at assessing hard-to-quantify tasks and prone to undermining the work itself…(More)”.
Use of Data in Public Sector Human Resources and Workforce Management: Solutions and Challenges
White Paper by Katherine Barrett and Richard Greene: “Across the U.S., a growing number of cities, counties, and states are using data across agencies to improve management and make decisions—and HR and payroll professionals in particular stand to gain much from this data to help drive staffing and other strategic decisions. In this white paper, industry experts Katherine Barrett and Richard Greene take a deep dive into both the benefits and challenges of using data with real-life examples of how data has been instrumental in building a resilient HR apparatus.
Data can be used for positive change that includes shorter new-hire onboarding, fairer overtime distribution, and even improved employee safety. However, obstacles to using data in an optimal way to improve HR management, such as insufficient funding, lack of training, and lack of software access, can keep government organizations from making the most of all it can offer.
Despite barriers, many organizations are moving toward creating a culture that is conducive to the use of the data their computers can create. Examples of how data and data analysis can transform workforce management practices include:
- Studying existing hiring and onboarding data to facilitate more effective and efficient administration
- Tracking turnover data to document employee departures and reveal information about those most at risk of sudden departure
- Reducing overtime by using the data to ensure fairer distribution of overtime
- Uncovering equity issues by assessing and comparing the demographic makeup of a workforce to see how closely it matches their population…(More)”
Your Boss Is an Algorithm: Artificial Intelligence, Platform Work and Labour
Book by Antonio Aloisi and Valerio De Stefano: “What effect do robots, algorithms, and online platforms have on the world of work? Using case studies and examples from across the EU, the UK, and the US, this book provides a compass to navigate this technological transformation as well as the regulatory options available, and proposes a new map for the era of radical digital advancements.
From platform work to the gig-economy and the impact of artificial intelligence, algorithmic management, and digital surveillance on workplaces, technology has overwhelming consequences for everyone’s lives, reshaping the labour market and straining social institutions. Contrary to preliminary analyses forecasting the threat of human work obsolescence, the book demonstrates that digital tools are more likely to replace managerial roles and intensify organisational processes in workplaces, rather than opening the way for mass job displacement.
Can flexibility and protection be reconciled so that legal frameworks uphold innovation? How can we address the pervasive power of AI-enabled monitoring? How likely is it that the gig-economy model will emerge as a new organisational paradigm across sectors? And what can social partners and political players do to adopt effective regulation?
Technology is never neutral. It can and must be governed, to ensure that progress favours the many. Digital transformation can be an essential ally, from the warehouse to the office, but it must be tested in terms of social and political sustainability, not only through the lenses of economic convenience. Your Boss Is an Algorithm offers a guide to explore these new scenarios, their promises, and perils…(More)”
Stories to Work By
Essay by William E. Spriggs: “In Charlie Chaplin’s 1936 film Modern Times, humans in a factory are reduced to adjuncts to a massive series of cogs and belts. Overlords bark commands from afar to a servant class, and Chaplin’s hapless hero is literally consumed by the machine … and then spit out by it. In the film, the bosses have all the power, and machines keep workers in check.
Modern Times’s dystopian narrative remains with us today. In particular, it is still held by many policymakers who assume that increasing technological progress, whether mechanical or informational, inevitably means that ordinary workers will lose. This view perpetuates itself when policies that could give workers more power in times of technological change are overlooked, while those that disempower workers are adopted. If we are to truly consider science policy for the future, we need to understand how this narrative about workers and technology functions, where it is misleading, and how deliberate policies can build a better world for all….
Today’s tales of pending technological dystopia—echoed in economics papers as well as in movies and news reports—blind us to the lessons we could glean from the massive disruptions of earlier periods of even greater change. Today the threat of AI is portrayed as revolutionary, and previous technological change as slow and inconsequential—but this was never the case. These narratives of technological inevitability limit the tools we have at our disposal to promote equality and opportunity.
The challenges we face today are far from insurmountable: technology is not destiny. Workers are not doomed to be Chaplin’s victim of technology with one toe caught in the gears of progress. We have choices, and the central challenge of science and technology policy for the next century will be confronting those choices head on. Policymakers should focus on the fundamental tasks of shaping how technology is deployed and enacting the economic rules we need to ensure that technology works for us all, rather than only the few….(More)”.
Tech Inclusion for Excluded Communities
Essay by Linda Jakob Sadeh & Smadar Nehab: “Companies often offer practical trainings to address the problem of diversity in high tech, acknowledging the disadvantages that members of excluded communities face and trying to level the playing field in terms of expertise and skills. But such trainings often fail in generating mass participation among excluded communities in tech professions. Beyond the professional knowledge and hands-on technical experience that these trainings provide, the fundamental social, ethnic, and economic barriers often remain unaddressed.
Thus, a paradoxical situation arises: On the one hand, certain communities are excluded from high tech and from the social mobility it affords. On the other hand, even when well-meaning companies wish to hire from these communities and implement diversity and inclusion measures that should make doing so possible, the pool of qualified and interested candidates often remains small. Members of the excluded communities remain discouraged from studying or training for these professions and from joining economic growth sectors, particularly high tech.
Tech Inclusion, the model we advance in this article, seeks to untangle this paradox. It takes a sincere look at the social and economic barriers that prevent excluded communities from participating in the tech industry. It suggests that the technology industry can be a driving force for inclusion if we turn the inclusion paradigm on its head, by bringing the industry to the excluded community, instead of trying to bring the excluded community to the industry, while cultivating a supportive environment for both potential candidates and firms…(More)”.