Emerging Developments in Citizen Science: Reflecting on Areas of Innovation

Emerging Developments in Citizen Science: Reflecting on Areas of Innovation. RAND Corporation. Brandi Leach et al. February 16, 2020

Citizen science — an approach whereby citizens actively contribute to the generation of knowledge about important research questions — is gaining increased attention in research and policy communities. Recent years have seen an expansion in the scale of citizen science activity globally, as well as an increase in the diversity of ways in which citizens can contribute to research endeavours. This report, informed by a literature review and interviews with selected experts, explores key areas of innovation and emerging and topical issues in citizen science, with a particular but not exclusive interest in healthcare related applications. More specifically, the report explores innovation related to new areas of applications of citizen science; novel methods of data gathering and analysis; innovative approaches to recruiting, retaining and enabling participation in citizen science projects; and building capacity for citizen science. The report also considers emerging themes and topical issues within the field and their implications. [Note: contains copyrighted material].

[PDF format, 45 pages].

U.S. Has Changed In Key Ways In The Past Decade, From Tech Use To Demographics

U.S. Has Changed In Key Ways In The Past Decade, From Tech Use To Demographics. Pew Research Center.  Katherine Schaeffer. December 20, 2019

The past decade in the United States has seen technological advancements, demographic shifts and major changes in public opinion. Pew Research Center has tracked these developments through surveys, demographic analyses and other research. [Note: contains copyrighted material].

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Automation: A Guide for Policymakers

Automation: A Guide for Policymakers. Brookings Institution. James Bessen et al. January 14, 2020.

Advancing technologies are increasingly able to fully or partially automate job tasks. These technologies range from robotics to machine learning and other forms of artificial intelligence, and are being adopted across many sectors of the economy. Applications range from selecting job applicants for interviewing, picking orders in a warehouse, interpreting X-rays to diagnose disease, and automated customer service. These developments have raised concern that workers are being displaced by advancing automation technology. Indeed, over 18 recent studies predict job losses from new automation technologies, including some predictions of massive job losses (Winick 2018). A large literature on worker displacement suggests that the effects of such developments could be dire: individual workers subject to plant closings and mass layoffs experience reduced employment probabilities and wage reductions, leading to long-term earnings losses, as well as reductions in consumption and worse health outcomes. Concerns about these effects of automation have led some commentators to call for policies to directly combat mass unemployment, such as a Universal Basic Income.

But is this right? At a time when many firms are investing in automation, the unemployment rate is at historic lows. Low unemployment might seem hard to reconcile with apocalyptic predictions about mass unemployment. This paper reviews the evidence from recent studies and reports on a new paper we have written, “Automatic Reaction: What happens to workers at firms that automate” (Bessen et al. 2019). This paper is the first to take a look at what actually happens to those workers. We build on some of the findings in order to draw the implications for policy. [Note: contains copyrighted material].

[PDF format, 17 pages].

The Macroeconomics of Automation: Data, Theory, and Policy Analysis

The Macroeconomics of Automation: Data, Theory, and Policy Analysis.  Brookings Institution. Nir Jaimovich et al. January 14, 2020.

Advanced economies have experienced a significant drop in the fraction of the population employed in middle wage, “routine task-intensive” occupations. Applying machine learning techniques, we identify characteristics of those who used to be employed in such occupations and show they are now less likely to work in routine occupations. Instead, they are either not-participants in the labor force or working at occupations that tend to occupy the bottom of the wage distribution. We then develop a quantitative, heterogeneous agent, general equilibrium model of labor force participation, occupational choice, and capital investment. This allows us to quantify the role of advancement in automation technology in accounting for these labor market changes. We then use this framework as a laboratory to evaluate various public policies aimed at addressing the disappearance of routine employment and its consequent impacts on inequality. [Note: contains copyrighted material].

[PDF format, 51 pages].

Is Seeing Still Believing? The Deepfake Challenge to Truth in Politics

Is Seeing Still Believing? The Deepfake Challenge to Truth in Politics. Brookings Institution. William A. Galston. January 8, 2020

On Nov. 25, an article headlined “Spot the deepfake. (It’s getting harder.)” appeared on the front page of The New York Times business section. The editors would not have placed this piece on the front page a year ago. If they had, few would have understood what its headline meant. Today, most do. This technology, one of the most worrying fruits of rapid advances in artificial intelligence (AI), allows those who wield it to create audio and video representations of real people saying and doing made-up things. As this technology develops, it becomes increasingly difficult to distinguish real audio and video recordings from fraudulent misrepresentations created by manipulating real sounds and images. “In the short term, detection will be reasonably effective,” says Subbarao Kambhampati, a professor of computer science at Arizona State University. “In the longer run, I think it will be impossible to distinguish between the real pictures and the fake pictures.” [Note: contains copyrighted material].

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10 Tech-Related Trends That Shaped the Decade

10 Tech-Related Trends That Shaped the Decade. Pew Research Center. Brooke Auxier, Monica Anderson And Madhu Kumar. December 20, 2019

The tech landscape has changed dramatically over the past decade, both in the United States and around the world. There have been notable increases in the use of social media and online platforms (including YouTube and Facebook) and technologies (like the internet, cellphones and smartphones), in some cases leading to near-saturation levels of use among major segments of the population. But digital tech also faced significant backlash in the 2010s. [Note: contains copyrighted material].

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How Ed-Tech Can Help Leapfrog Progress In Education

How Ed-Tech Can Help Leapfrog Progress In Education.  Brookings Institution. Emiliana Vegas,  Lauren Ziegler, Nicolas Zerbino.  November 20, 2019.

This brief is the second in a series of Leapfrogging in Education snapshots that provide analyses of our global catalog of education innovations. (Our first snapshot focused on playful learning.) The catalog and our corresponding research on leapfrogging is explained in depth in CUE’s book, “Leapfrogging inequality: Remaking education to help young people thrive.” Of the nearly 3,000 global innovations CUE cataloged, more than one half involve the use of technology, which suggests strong interest in its use and application in aiding educators around the world. [Note: contains copyrighted material].

[PDF format, 18 pages].