Are New Technologies Changing the Nature of Work? The Evidence So Far

Curated on Posted on by Stefaan Verhulst

Report by Kristyn Frank and Marc Frenette for the Institute for Research on Public Policy (Canada): “In recent years, ground breaking advances in artificial intelligence and their implications for automation technology have fuelled speculation that the very nature of work is being altered in unprecedented ways. News headlines regularly refer to the ”changing nature of work,” but what does it mean? Is there evidence that work has already been transformed by the new technologies? And if so, are these changes more dramatic than those experienced before?

In this paper, Kristyn Frank and Marc Frenette offer insights on these questions, based on the new research they conducted with their colleague Zhe Yang at Statistics Canada. Two aspects of work are under the microscope: the mix of work activities (or tasks) that constitute a job, and the mix of jobs in the economy. If new automation technologies are indeed changing the nature of work, the authors argue, then nonautomatable tasks should be increasingly important, and employment should be shifting toward occupations primarily involving such tasks.

According to the authors, nonroutine cognitive tasks (analytical or interpersonal) did become more important between 2011 and 2018. However, the changes were relatively modest, ranging from a 1.5 percent increase in the average importance of establishing and maintaining interpersonal relationships, to a 3.7 percent increase in analyzing data or information. Routine cognitive tasks — such as data entry — also gained importance, but these gains were even smaller. The picture is less clear for routine manual tasks, as the importance of tasks for which the pace is determined by the speed of equipment declined by close to 3 percent, whereas other tasks in that category became slightly more important.

Looking at longer-term shifts in overall employment, between 1987 and 2018, the authors find a gradual increase in the share of workers employed in occupations associated with nonroutine tasks, and a decline in routine-task-related occupations. The most pronounced shift in employment was away from production, craft, repair and operative occupations toward managerial, professional and technical occupations. However, they note that this shift to nonroutine occupations was not more pronounced between 2011 and 2018 than it was in the preceding decades. For instance, the share of employment in managerial, professional and technical occupations increased by 1.8 percentage points between 2011 and 2018, compared with a 6 percentage point increase between 1987 and 2010.

Most sociodemographic groups experienced the shift toward nonroutine jobs, although there were some exceptions. For instance, the employment share of workers in managerial, professional and technical occupations increased for all workers, but much more so for women than for men. Interestingly, there was a decline in the employment shares of workers in these occupations among those with a post-­secondary education. The explanation for this lies in the major increase over the past three decades in the proportion of workers with post-secondary education, which led some of them to move into jobs for which they are overqualified….(More)”.

Democratizing data in a 5G world

Curated on Posted on by Stefaan Verhulst

Blog by Dimitrios Dosis at Mastercard: “The next generation of mobile technology has arrived, and it’s more powerful than anything we’ve experienced before. 5G can move data faster, with little delay — in fact, with 5G, you could’ve downloaded a movie in the time you’ve read this far. 5G will also create a vast network of connected machines. The Internet of Things will finally deliver on its promise to fuse all our smart products — vehicles, appliances, personal devices — into a single streamlined ecosystem.

My smartwatch could monitor my blood pressure and schedule a doctor’s appointment, while my car could collect data on how I drive and how much gas I use while behind the wheel. In some cities, petrol trucks already act as roving gas stations, receiving pings when cars are low on gas and refueling them as needed, wherever they are.

This amounts to an incredible proliferation of data. By 2025, every connected person will conduct nearly 5,000 data interactions every day — one every 18 seconds — whether they know it or not. 

Enticing and convenient as new 5G-powered developments may be, it also raises complex questions about data. Namely, who is privy to our personal information? As your smart refrigerator records the foods you buy, will the refrigerator’s manufacturer be able to see your eating habits? Could it sell that information to a consumer food product company for market research without your knowledge? And where would the information go from there? 

People are already asking critical questions about data privacy. In fact, 72% of them say they are paying attention to how companies collect and use their data, according to a global survey released last year by the Harvard Business Review Analytic Services. The survey, sponsored by Mastercard, also found that while 60% of executives believed consumers think the value they get in exchange for sharing their data is worthwhile, only 44% of consumers actually felt that way.

There are many reasons for this data disconnect, including the lack of transparency that currently exists in data sharing and the tension between an individual’s need for privacy and his or her desire for personalization.

This paradox can be solved by putting data in the hands of the people who create it — giving consumers the ability to manage, control and share their own personal information when they want to, with whom they want to, and in a way that benefits them.

That’s the basis of Mastercard’s core set of principles regarding data responsibility – and in this 5G world, it’s more important than ever. We will be able to gain from these new technologies, but this change must come with trust and user control at its core. The data ecosystem needs to evolve from schemes dominated by third parties, where some data brokers collect inferred, often unreliable and inaccurate data, then share it without the consumer’s knowledge….(More)”.

Personal experiences bridge moral and political divides better than facts

Curated on Posted on by Stefaan Verhulst

Paper by Emily Kubin, Curtis Puryear, Chelsea Schein, and Kurt Gray: “All Americans are affected by rising political polarization, whether because of a gridlocked Congress or antagonistic holiday dinners. People believe that facts are essential for earning the respect of political adversaries, but our research shows that this belief is wrong. We find that sharing personal experiences about a political issue—especially experiences involving harm—help to foster respect via increased perceptions of rationality. This research provides a straightforward pathway for increasing moral understanding and decreasing political intolerance. These findings also raise questions about how science and society should understand the nature of truth in the era of “fake news.” In moral and political disagreements, everyday people treat subjective experiences as truer than objective facts….(More)”

Digital Technology and Democratic Theory

Curated on Posted on by Stefaan Verhulst

Book edited by Lucy Bernholz, Helene Landemore, and Rob Reich: “One of the most far-reaching transformations in our era is the wave of digital technologies rolling over—and upending—nearly every aspect of life. Work and leisure, family and friendship, community and citizenship have all been modified by now-ubiquitous digital tools and platforms. Digital Technology and Democratic Theory looks closely at one significant facet of our rapidly evolving digital lives: how technology is radically changing our lives as citizens and participants in democratic governments.


To understand these transformations, this book brings together contributions by scholars from multiple disciplines to wrestle with the question of how digital technologies shape, reshape, and affect fundamental questions about democracy and democratic theory. As expectations have whiplashed—from Twitter optimism in the wake of the Arab Spring to Facebook pessimism in the wake of the 2016 US election—the time is ripe for a more sober and long-term assessment. How should we take stock of digital technologies and their promise and peril for reshaping democratic societies and institutions? To answer, this volume broaches the most pressing technological changes and issues facing democracy as a philosophy and an institution….(More)”.

The High Price of Mistrust

Curated on Posted on by Stefaan Verhulst

fs.blog: “There are costs to falling community participation. Rather than simply lamenting the loss of a past golden era (as people have done in every era), Harvard political scientist Robert D. Putnam explains these costs, as well as how we might bring community participation back.

First published twenty years ago, Bowling Alone is an exhaustive, hefty work. In its 544 pages, Putnam negotiated mountains of data to support his thesis that the previous few decades had seen Americans retreat en masse from public life. Putnam argued Americans had become disconnected from their wider communities, as evidenced by changes such as a decline in civic engagement and dwindling membership rates for groups such as bowling leagues and PTAs.

Though aspects of Bowling Alone are a little dated today (“computer-mediated communication” isn’t a phrase you’re likely to have heard recently), a quick glance at 2021’s social landscape would suggest many of the trends Putnam described have only continued and apply in other parts of the world too.

Right now, polarization and social distancing have forced us apart from any sense of community to a degree that can seem irresolvable.

Will we ever bowl in leagues alongside near strangers and turn them into friends again? Will we ever bowl again at all, even if alone, or will those gleaming aisles, too-tight shoes, and overpriced sodas fade into a distant memory we recount to our children?

The idea of going into a public space for a non-essential reason can feel incredibly out of reach for many of us right now. And who knows how spaces like bowling alleys will survive in the long run without the social scenes that fuelled them. Now is a perfect time to revisit Bowling Alone to see what it can still teach us, because many of its warnings and lessons are perhaps more relevant now than at its time of publication.

One key lesson we can derive from Bowling Alone is that the less we trust each other—something which is both a cause and consequence of declining community engagement—the more it costs us. Mistrust is expensive.…(More)”

These crowdsourced maps will show exactly where surveillance cameras are watching

Curated on Posted on by Stefaan Verhulst

Mark Sullivan at FastCompany: “Amnesty International is producing a map of all the places in New York City where surveillance cameras are scanning residents’ faces.

The project will enlist volunteers to use their smartphones to identify, photograph, and locate government-owned surveillance cameras capable of shooting video that could be matched against people’s faces in a database through AI-powered facial recognition.

The map that will eventually result is meant to give New Yorkers the power of information against an invasive technology the usage of which and purpose is often not fully disclosed to the public. It’s also meant to put pressure on the New York City Council to write and pass a law restricting or banning it. Other U.S. cities, such as Boston, Portland, and San Francisco, have already passed such laws.

Facial recognition technology can be developed by scraping millions of images from social media profiles and driver’s licenses without people’s consent, Amnesty says. Software from companies like Clearview AI can then use computer vision algorithms to match those images against facial images captured by closed-circuit television (CCTV) or other video surveillance cameras and stored in a database.

Starting in May, volunteers will be able to use a software tool to identify all the facial recognition cameras within their view—like at an intersection where numerous cameras can often be found. The tool, which runs on a phone’s browser, lets users place a square around any cameras they see. The software integrates Google Street View and Google Earth to help volunteers label and attach geolocation data to the cameras they spot.

The map is part of a larger campaign called “Ban the Scan” that’s meant to educate people around the world on the civil rights dangers of facial recognition. Research has shown that facial recognition systems aren’t as accurate when it comes to analyzing dark-skinned faces, putting Black people at risk of being misidentified. Even when accurate, the technology exacerbates systemic racism because it is disproportionately used to identify people of color, who are already subject to discrimination by law enforcement officials. The campaign is sponsored by Amnesty in partnership with a number of other tech advocacy, privacy, and civil liberties groups.

In the initial phase of the project, which was announced last Thursday, Amnesty and its partners launched a website that New Yorkers can use to generate public comments on the New York Police Department’s (NYPD’s) use of facial recognition….(More)”.

Sharing Student Health Data with Health Agencies: Considerations and Recommendations

Curated on Posted on by Stefaan Verhulst

Memo by the Center for Democracy and Technology: “As schools respond to COVID-19 on their campuses, some have shared student information with state and local health agencies, often to aid in contact tracing or to provide services to students. Federal and state student privacy laws, however, do not necessarily permit that sharing, and schools should seek to protect both student health and student privacy.

How Are Schools Sharing COVID-Related Student Data?

When it comes to sharing student data, schools’ practices vary widely. For example, the New York City Department of Education provides a consent form for sharing COVID-related student data. Other schools do not have consent forms, but instead, share COVID-related data as required by local or state health agencies. For instance, Orange County Public Schools in Florida assists the local health agency in contact tracing by collecting information such as students’ names and dates of birth. Some districts, such as the Dallas Independent School District in Texas, report positive cases to the county, but do not publicly specify what information is reported. Many schools, however, do not publicly disclose their collection and sharing of COVID-related student data….(More)”

Citizen acceptance of mass surveillance? Identity, intelligence, and biodata concerns

Curated on Posted on by Stefaan Verhulst

Paper by Westerlund, Mika; Isabelle, Diane A; Leminen, Seppo: “News media and human rights organizations are warning about the rise of the surveillance state that builds on distrust and mass surveillance of its citizens. Further, the global pandemic has fostered public-private collaboration such as the launch of contact tracing apps to tackle COVID-19. Thus, such apps also contribute to the diffusion of technologies that can collect and analyse large amounts of sensitive data and the growth of the surveillance society. This study examines the impacts of citizens’ concerns about digital identity, government’s intelligence activities, and security of the increasing biodata on their trust in and acceptance of government’s use of personal data. Our analysis of survey data from 1,486 Canadians suggest that those concerns have direct effects on people’s acceptance of government’s use of personal data, but not necessarily on the trust in the government being respectful of privacy. Authorities should be more transparent about the collection and uses of data….(More)”

Re-use of smart city data: The need to acquire a social license through data assemblies

Curated on Posted on by Stefaan Verhulst

Written Testimony by Stefaan G. Verhulst before the New York City Council Committee on Technology: “…In crises such as these, calls for the city to harness technology and data to help policy-makers find solutions grow louder and stronger. Many have spoken about accelerating already ongoing work to turn New York into “a smart city” — using digital technology to connect, protect, and improve the lives of its residents. Some of this proposed work could involve the use of sensors to collect data on how people live and work across New York City. Other work could involve expanding the city’s relationships with private organizations through data collaboratives. Data collaboratives, which are central to our work at the GovLab, are a new form of collaboration that extends beyond the conventional public-private partnership model, in which participants from different sectors exchange their data to create public value. The city already operates one such data collaborative in the form of the NYC Recovery Data Partnership, a partnership that allows New York-based private and civic organizations to provide their data to analysts at city agencies to inform the COVID-19 pandemic response. I have the privilege of serving as an advisor to that initiative.

Data collaboration takes place widely through a variety of institutional, contractual and technical structures and instruments. Borrowing in language and inspiration from the open data movement, the emerging data collaborative movement has proven its value and possible positive impact. Data reuse has the potential to improve disease treatment, identify better ways to source supplies, monitor adherence to non-pharmaceutical restrictions, and provide a range of other public benefits. Whether it is informing decision-making or shaping the development of new tools and techniques, it is clear that data has tremendous potential to mitigate the worst effects of this pandemic.

However, as promising and attractive as reusing data might seem, it is important to keep in mind that there also exist widespread concerns and challenges….

My colleagues and I at The GovLab believe the Data Assembly methodology offers the city a new way forward on the issues under discussion today, as they relate to smart cities. In our view, oversight cannot just be a reactive process of responding to complaints but a proactive one, inviting city residents, data holders, and advocacy groups to the table to determine what is and is not acceptable. Amid rapidly changing circumstances, the city needs ways to collect and synthesize actionable and diverse public input to identify concerns, expectations, and opportunities. We encourage the city to explore assembling mini-publics of its own or, failing that, commission legitimate partners to lead such efforts.

New York faces many challenges in 2021 but I do not doubt the capacity of its people to overcome these struggles. Through people-led innovation and processes, the city can ensure that data re-use conducted as part of the smart city is deemed legitimate and more effective and targeted. It can also support the city in ensuring work across the city is more open, collaborative, and legitimate…(More)”.

Nowcasting Gentrification Using Airbnb Data

Curated on Posted on by Stefaan Verhulst

Paper by Shomik Jain, Davide Proserpio, Giovanni Quattrone, and Daniele Quercia: “There is a rumbling debate over the impact of gentrification: presumed gentrifiers have been the target of protests and attacks in some cities, while they have been welcome as generators of new jobs and taxes in others. Census data fails to measure neighborhood change in real-time since it is usually updated every ten years. This work shows that Airbnb data can be used to quantify and track neighborhood changes. Specifically, we consider both structured data (e.g. number of listings, number of reviews, listing information) and unstructured data (e.g. user-generated reviews processed with natural language processing and machine learning algorithms) for three major cities, New York City (US), Los Angeles (US), and Greater London (UK). We find that Airbnb data (especially its unstructured part) appears to nowcast neighborhood gentrification, measured as changes in housing affordability and demographics. Overall, our results suggest that user-generated data from online platforms can be used to create socioeconomic indices to complement traditional measures that are less granular, not in real-time, and more costly to obtain….(More)”.