Data for an Inclusive Economic Recovery

Curated on Posted on by Stefaan Verhulst

Report by the National Skills Coalition: “A truly inclusive economic recovery means that the workers and businesses who were most impacted by this pandemic, as well as workers who have been held back by structural barriers of discrimination or lack of opportunity, are empowered to equitably participate in and benefit from the economy’s expansion and restructuring. 

But we need data on how different workers and businesses are faring in the recovery, so 

we can hold policymakers accountable to equitable outcomes. Disparities and inequities in skills training programs can only be eliminated if there is high-quality information on program outcomes available to practitioners and policymakers to assess and address equity gaps. Once we have the data – we can use it to drive the change we need! 

 Data for an Inclusive Economic Recovery provides recommendations on how to measure and report on what really matters to help diminish structural inequities and to shape implementation of federal recovery investments as well as new state and federal workforce investments…  

Recommendations Include: 

  • Requiring that all education and skills training programs include collection of self-reported demographic characteristics of workers and learners so outcomes can be disaggregated by race, ethnicity, gender, English language proficiency, income, and geography ;
  • Ensuring participants of skills training programs know what demographic characteristics are being collected about them, who will have access to personally identifiable information, and how their data will be used; 
  • Establishing common outcomes metrics across federal skills training programs;
  • Expanding outcomes to include those that allow policymakers to assess the quality of skills training programs and measure economic mobility along a career pathway; 
  • Ensuring equitable access to administrative data; 
  • Mandating public reporting on skills training and workforce investment outcomes; and

Providing sufficient funding for linked education and workforce data systems…(More)”.

The Labor Market Impacts of Technological Change: From Unbridled Enthusiasm to Qualified Optimism to Vast Uncertainty

Curated on Posted on by Stefaan Verhulst

NBER Working Paper by David Autor: “This review considers the evolution of economic thinking on the relationship between digital technology and inequality across four decades, encompassing four related but intellectually distinct paradigms, which I refer to as the education race, the task polarization model, the automation-reinstatement race, and the era of Artificial Intelligence uncertainty. The nuance of economic understanding has improved across these epochs. Yet, traditional economic optimism about the beneficent effects of technology for productivity and welfare has eroded as understanding has advanced. Given this intellectual trajectory, it would be natural to forecast an even darker horizon ahead. I refrain from doing so because forecasting the “consequences” of technological change treats the future as a fate to be divined rather than an expedition to be undertaken. I conclude by discussing opportunities and challenges that we collectively face in shaping this future….(More)”.

Facebook-owner Meta to share more political ad targeting data

Curated on Posted on by Stefaan Verhulst

Article by Elizabeth Culliford: “Facebook owner Meta Platforms Inc (FB.O) will share more data on targeting choices made by advertisers running political and social-issue ads in its public ad database, it said on Monday.

Meta said it would also include detailed targeting information for these individual ads in its “Facebook Open Research and Transparency” database used by academic researchers, in an expansion of a pilot launched last year.

“Instead of analyzing how an ad was delivered by Facebook, it’s really going and looking at an advertiser strategy for what they were trying to do,” said Jeff King, Meta’s vice president of business integrity, in a phone interview.

The social media giant has faced pressure in recent years to provide transparency around targeted advertising on its platforms, particularly around elections. In 2018, it launched a public ad library, though some researchers criticized it for glitches and a lack of detailed targeting data.Meta said the ad library will soon show a summary of targeting information for social issue, electoral or political ads run by a page….The company has run various programs with external researchers as part of its transparency efforts. Last year, it said a technical error meant flawed data had been provided to academics in its “Social Science One” project…(More)”.

Social Engineering: How Crowdmasters, Phreaks, Hackers, and Trolls Created a New Form of Manipulative Communication

Curated on Posted on by Stefaan Verhulst

Open Access book by Robert W. Gehl, and Sean T Lawson: “Manipulative communication—from early twentieth-century propaganda to today’s online con artistry—examined through the lens of social engineering. The United States is awash in manipulated information about everything from election results to the effectiveness of medical treatments. Corporate social media is an especially good channel for manipulative communication, with Facebook a particularly willing vehicle for it. In Social Engineering, Robert Gehl and Sean Lawson show that online misinformation has its roots in earlier techniques: mass social engineering of the early twentieth century and interpersonal hacker social engineering of the 1970s, converging today into what they call “masspersonal social engineering.” As Gehl and Lawson trace contemporary manipulative communication back to earlier forms of social engineering, possibilities for amelioration become clearer.

The authors show how specific manipulative communication practices are a mixture of information gathering, deception, and truth-indifferent statements, all with the instrumental goal of getting people to take actions the social engineer wants them to. Yet the term “fake news,” they claim, reduces everything to a true/false binary that fails to encompass the complexity of manipulative communication or to map onto many of its practices. They pay special attention to concepts and terms used by hacker social engineers, including the hacker concept of “bullshitting,” which the authors describe as a truth-indifferent mix of deception, accuracy, and sociability. They conclude with recommendations for how society can undermine masspersonal social engineering and move toward healthier democratic deliberation…(More)”.

We Need to Take Back Our Privacy

Curated on Posted on by Stefaan Verhulst

Zeynep Tufekci in The New York Times: “…Congress, and states, should restrict or ban the collection of many types of data, especially those used solely for tracking, and limit how long data can be retained for necessary functions — like getting directions on a phone.

Selling, trading and merging personal data should be restricted or outlawed. Law enforcement could obtain it subject to specific judicial oversight.

Researchers have been inventing privacy-preserving methods for analyzing data sets when merging them is in the public interest but the underlying data is sensitive — as when health officials are tracking a disease outbreak and want to merge data from multiple hospitals. These techniques allow computation but make it hard, if not impossible, to identify individual records. Companies are unlikely to invest in such methods, or use end-to-end encryption as appropriate to protect user data, if they could continue doing whatever they want. Regulation could make these advancements good business opportunities, and spur innovation.

I don’t think people like things the way they are. When Apple changed a default option from “track me” to “do not track me” on its phones, few people chose to be tracked. And many who accept tracking probably don’t realize how much privacy they’re giving up, and what this kind of data can reveal. Many location collectors get their data from ordinary apps — could be weather, games, or anything else — that often bury that they will share the data with others in vague terms deep in their fine print.

Under these conditions, requiring people to click “I accept” to lengthy legalese for access to functions that have become integral to modern life is a masquerade, not informed consent.

Many politicians have been reluctant to act. The tech industry is generous, cozy with power, and politicians themselves use data analysis for their campaigns. This is all the more reason to press them to move forward…(More)”.

Automating the Analysis of Online Deliberation? Comparing computational analyses of polarized discussions on climate change to established content analysis

Curated on Posted on by Stefaan Verhulst

Paper by Lisa Oswald: “High­-quality discussions can help people acquire an adequate understanding of issues and alleviate mechanisms of opinion polarization. However, the extent to which the quality of the online public discourse contributes is contested. Facing the importance and the sheer volume of online discussions, reliable computational approaches to assess the deliberative quality of online discussions at scale would open a new era of deliberation research. But is it possible to automate the assessment of deliberative quality? I compare structural features of discussion threads and sim­ple text­-based measures to established manual content analysis by applying all measures to online discussions on ‘Reddit’ that deal with the 2020 wildfires in Australia and California. I further com­ pare discussions between two ideologically opposite online communities, one featuring discussions in line with the scientific consensus and one featuring climate change skepticism. While no single computational measure can capture the multidimensional concept of deliberative quality, I find that (1) measures of structural complexity capture engagement and participation as preconditions for deliberation, (2) the length of comments is correlated with manual measures of argumentation, and (3) automated toxicity scores are correlated with manual measures of respect. While the presented computational approaches cannot replace in­depth content coding, the findings imply that selected automated measures can be useful, scalable additions to the measurement repertoire for specific dimensions of online deliberation. I discuss implications for communication research and platform regulation and suggest interdisciplinary research to synthesize past content coding efforts using machine learning….(More)”.

How the Pandemic Made Algorithms Go Haywire

Curated on Posted on by Stefaan Verhulst

Article by Ravi Parikh and Amol Navathe: “Algorithms have always had some trouble getting things right—hence the fact that ads often follow you around the internet for something you’ve already purchased.

But since COVID upended our lives, more of these algorithms have misfired, harming millions of Americans and widening existing financial and health disparities facing marginalized groups. At times, this was because we humans weren’t using the algorithms correctly. More often it was because COVID changed life in a way that made the algorithms malfunction.

Take, for instance, an algorithm used by dozens of hospitals in the U.S. to identify patients with sepsis—a life-threatening consequence of infection. It was supposed to help doctors speed up transfer to the intensive care unit. But starting in spring of 2020, the patients that showed up to the hospital suddenly changed due to COVID. Many of the variables that went into the algorithm—oxygen levels, age, comorbid conditions—were completely different during the pandemic. So the algorithm couldn’t effectively discern sicker from healthier patients, and consequently it flagged more than twice as many patients as “sick” even though hospital capacity was 35 percent lower than normal. The result was presumably more instances of doctors and nurses being summoned to the patient bedside. It’s possible all of these alerts were necessary – after all, more patients were sick. However, it’s also possible that many of these alerts were false alarms because the type of patients showing up to the hospital were different. Either way, this threatened to overwhelm physicians and hospitals. This “alert overload” was discovered months into the pandemic and led the University of Michigan health system to shut down its use of the algorithm…(More)”.

Canada is the first country to provide census data on transgender and non-binary people

Curated on Posted on by Stefaan Verhulst

StatsCan: “Prior to the 2021 Census, some individuals indicated that they were not able to see themselves in the two responses of male or female on the existing sex question in the census.

Following extensive consultation and countrywide engagement with the Canadian population, the census evolved—as it has for more than a century—to reflect societal changes, adding new content on gender in 2021.

Beginning in 2021, the precision of “at birth” was added to the sex question on the census questionnaire, and a new question on gender was included. As a result, the historical continuity of information on sex was maintained while allowing all cisgender, transgender and non-binary individuals to report their gender. This addressed an important information gap on gender diversity (see Filling the gaps: Information on gender in the 2021 Census and 2021 Census: Sex at birth and gender—the whole picture).

For many people, their gender corresponds to their sex at birth (cisgender men and cisgender women). For some, these do not align (transgender men and transgender women) or their gender is not exclusively “man” or “woman” (non-binary people).

The strength of the census is to provide reliable data for local communities throughout the country and for smaller populations such as the transgender and non-binary populations. Statistics Canada always protects privacy and confidentiality of respondents when disseminating detailed data.

These modifications reflect today’s reality in terms of the evolving acceptance and understanding of gender and sexual diversity and an emerging social and legislative recognition of transgender, non-binary and LGBTQ2+ people in general, that is, people who are lesbian, gay, bisexual, transgender, queer, Two-Spirit, or who use other terms related to gender or sexual diversity. In 2017, the Canadian government amended the Canadian Human Rights Act and the Canadian Criminal Code to protect individuals from discrimination and hate crimes based on gender identity and expression.

These data can be used by public decision makers, employers, and providers of health care, education, justice, and other services to better meet the needs of all men and women—including transgender men and women—and non-binary people in their communities….(More)”.

Can behavioral interventions be too salient? Evidence from traffic safety messages

Curated on Posted on by Stefaan Verhulst


Article by Jonathan D. Hall and Joshua M. Madsen: “Policy-makers are increasingly turning to behavioral interventions such as nudges and informational campaigns to address a variety of issues. Guidebooks say that these interventions should “seize people’s attention” at a time when they can take the desired action, but little consideration has been given to the costs of seizing one’s attention and to the possibility that these interventions may crowd out other, more important, considerations. We estimated these costs in the context of a widespread, seemingly innocuous behavioral campaign with the stated objective of reducing traffic crashes. This campaign displays the year-to-date number of statewide roadside fatalities (fatality messages) on previously installed highway dynamic message signs (DMSs) and has been implemented in 28 US states.

We estimated the impact of displaying fatality messages using data from Texas. Texas provides an ideal setting because the Texas Department of Transportation (TxDOT) decided to show fatality messages starting in August 2012 for 1 week each month: the week before TxDOT’s monthly board meeting (campaign weeks). This allows us to measure the impact of the intervention, holding fixed the road segment, year, month, day of week, and time of day. We used data on 880 DMSs and all crashes occurring in Texas between 1 January 2010 and 31 December 2017 to investigate the effects of this safety campaign. We estimated how the intervention affects crashes near DMSs as well as statewide. As placebo tests, we estimated whether the chosen weeks inherently differ using data from before TxDOT started displaying fatality messages and data from upstream of DMSs.

Contrary to policy-makers’ expectations, we found that displaying fatality messages increases the number of traffic crashes. Campaign weeks realize a 1.52% increase in crashes within 5 km of DMSs, slightly diminishing to a 1.35% increase over the 10 km after DMSs. We used instrumental variables to recover the effect of displaying a fatality message and document a significant 4.5% increase in the number of crashes over 10 km. The effect of displaying fatality messages is comparable to raising the speed limit by 3 to 5 miles per hour or reducing the number of highway troopers by 6 to 14%. We also found that the total number of statewide on-highway crashes is higher during campaign weeks. The social costs of these fatality messages are large: Back-of-the-envelope calculations suggest that this campaign causes an additional 2600 crashes and 16 fatalities per year in Texas alone, with a social cost of $377 million per year…(More)”.

Modernizing Agriculture Data Infrastructure to Improve Economic and Ecological Outcomes.

Curated on Posted on by Stefaan Verhulst

Paper by the AGree Initiative and the Data Foundation: “The paper highlights the necessity of data innovation to address a growing number of critical short and long-term food and agricultural issues, including agricultural production, environmental sustainability, nutrition assistance, food waste, and food and farm labor. It concludes by offering four practical options that are effective case studies for data acquisition, management, and use in other sectors.

Given the increasingly dynamic conditions in which the sector operates, the modernization of agricultural data collection, storage, and analysis will equip farmers, ranchers, and the U.S. Department of Agriculture (USDA) with tools to adapt, innovate, and ensure a food-secure future.

While USDA has made strides over the years, to truly unlock the potential of data to improve farm productivity and the resilience of rural communities, the department must establish a more effective data infrastructure, which will require addressing gaps in USDA’s mandate and authorities across its agencies and programs.

The white paper explores four options that are effective case studies for data acquisition, management, and use in other sectors:

  1. Centralized Data Infrastructure Operated by USDA
  2. Centralized Data Infrastructure Operated by a Non-Governmental Intermediary
  3. Data Linkage Hub Operated by a Non-USDA Agency in the Federal Government
  4. Contractual Model with Relevant Partners

Each of the models considered offers opportunities for collaboration with farmers and other stakeholders to ensure there are clear benefits and to address shortfalls in the current system. Careful consideration of the trade-offs of each option is critical given the dynamic weather and economic challenges the agriculture sector faces and the potential new economic opportunities that may be unlocked by harnessing the power of data…(More)”.