UK passport photo checker shows bias against dark-skinned women

Curated on Posted on by Stefaan Verhulst

Maryam Ahmed at BBC News: “Women with darker skin are more than twice as likely to be told their photos fail UK passport rules when they submit them online than lighter-skinned men, according to a BBC investigation.

One black student said she was wrongly told her mouth looked open each time she uploaded five different photos to the government website.

This shows how “systemic racism” can spread, Elaine Owusu said.

The Home Office said the tool helped users get their passports more quickly.

“The indicative check [helps] our customers to submit a photo that is right the first time,” said a spokeswoman.

“Over nine million people have used this service and our systems are improving.

“We will continue to develop and evaluate our systems with the objective of making applying for a passport as simple as possible for all.”

Skin colour

The passport application website uses an automated check to detect poor quality photos which do not meet Home Office rules. These include having a neutral expression, a closed mouth and looking straight at the camera.

BBC research found this check to be less accurate on darker-skinned people.

More than 1,000 photographs of politicians from across the world were fed into the online checker.

The results indicated:

  • Dark-skinned women are told their photos are poor quality 22% of the time, while the figure for light-skinned women is 14%
  • Dark-skinned men are told their photos are poor quality 15% of the time, while the figure for light-skinned men is 9%

Photos of women with the darkest skin were four times more likely to be graded poor quality, than women with the lightest skin….(More)”.

How Not to Kill People With Spreadsheets

Curated on Posted on by Stefaan Verhulst

David Gerard at Foreign Policy: “The U.K.’s response to COVID-19 is widely regarded as scattershot and haphazard. So how did they get here?

Excel is a top-of-the-line spreadsheet tool. A spreadsheet is good for quickly modeling a problem—but too often, organizations cut corners and press the cardboard-and-string mock-up into production, instead of building a robust and unique system based on the Excel proof of concept.

Excel is almost universally misused for complex data processing, as in this case—because it’s already present on your work computer and you don’t have to spend months procuring new software. So almost every business has at least one critical process that relies on a years-old spreadsheet set up by past staff members that nobody left at the company understands.

That’s how the U.K. went wrong. An automated process at Public Health England (PHE) transformed the incoming private laboratory test data (which was in text-based CSV files) into Excel-format files, to pass to the Serco Test and Trace teams’ dashboards.

Unfortunately, the process produced XLS files—an outdated Excel format that went extinct in 2003—which had a limit of 65,536 rows, rather than the around 1 million-row limit in the more recent XLSX format. With several lines of data per patient, this meant a sheet could only hold 1,400 cases. Further cases just fell off the end.

Technicians at PHE monitoring the dashboards noticed on Oct. 2 that not all data that had been sent in was making it out the other end. The data was corrected the next day, and PHE announced the issue the day after.

It’s not clear if the software at PHE was an Excel spreadsheet or an in-house program using the XLS format for data interchange—the latter would explain why PHE stated that replacing it might take months—but the XLS format would have been used on the assumption that Excel was universal.

And even then, a system based on Excel-format files would have been an improvement over earlier systems—the system for keeping a count of COVID-19 cases in the U.K. was, as of May, still based on data handwritten on cards….

The process that went wrong was a workaround for a contract issue: The government’s contract with Deloitte to run the testing explicitly stipulated that the company did not have to report “Pillar 2” (general public testing) positive cases to PHE at all.

Since a test-and-trace system is not possible without this data, PHE set up feeds for the data anyway, as CSV text files directly from the testing labs. The data was then put into this system—the single system that serves as the bridge between testing and tracing, for all of England. PHE had to put in place technological duct tape to make a system of life-or-death importance work at all….

The Brookings Institution report Doomed: Challenges and solutions to government IT projects lists factors to consider when outsourcing government information technology. The outsourcing of tracking and tracing is an example where the government has assumed all of the risk, and the contractor assumes all of the profit. PHE did one thing that you should never do: It outsourced a core function. Running a call center or the office canteen? You can outsource it. Tracing a pandemic? You must run it in-house.

If you need outside expertise for a core function, use contractors working within a department. Competing with the private sector on pay can be an issue, but a meaningful project can be a powerful incentive….(More)”.

Scotland’s future vision discussed today in first Citizens’ Assembly

Curated on Posted on by Stefaan Verhulst

Article by Richard Mason: “The group of 100 broadly representative Scots have been meeting throughout the year to discuss some of the country’s major constitutional issues.

Members have been asked to consider three questions, the first of which is: “What kind of country are we seeking to build?”

The assembly will meet online to develop the vision, having examined issues such as finances and taxation, and discussed how decisions are taken for and about Scotland. A report of the meeting will be published on October 9

The other two parts of the Assembly’s remit – how to best overcome the challenges the country faces, including Brexit, and how to empower people to make “informed choices” about Scotland’s future – will be addressed in a final report by the end of the year.

Assembly convener Kate Wimpress said: “The meeting this weekend will see a group of people from all walks of life across Scotland come together to agree a shared vision of our country’s future.

“The Citizens’ Assembly’s vision for Scotland will help give a roadmap for the country at an uncertain and difficult time.

“Our members have worked hard together across the months, and it’s exciting to witness their efforts now coming to fruition.”

First Minister Nicola Sturgeon announced the creation of the Citizens’ Assembly and outlined its remit, but she stressed it would be independent from Government following criticism it was set up to garner independence support.

Constitution Secretary Michael Russell said the Scottish Government is spending £1.37 million to fund six assembly meetings, which were held in person before moving online following the coronavirus lockdown….(More)”

Social license for the use of big data in the COVID-19 era

Curated on Posted on by Stefaan Verhulst

Commentary by James A. Shaw, Nayha Sethi & Christine K. Cassel: “… Social license refers to the informal permissions granted to institutions such as governments or corporations by members of the public to carry out a particular set of activities. Much of the literature on the topic of social license has arisen in the field of natural resources management, emphasizing issues that include but go beyond environmental stewardship4. In their seminal work on social license in the pulp and paper industry, Gunningham et al. defined social license as the “demands and expectations” placed on organizations by members of civil society which “may be tougher than those imposed by regulation”; these expectations thereby demand actions that go beyond existing legal rules to demonstrate concern for the interests of publics. We use the plural term “publics” as opposed to the singular “public” to illustrate that stakeholder groups to which organizations must appeal are often diverse and varied in their assessments of whether a given organizational activity is acceptable6. Despite the potentially fragmented views of various publics, the concept of social license is considered in a holistic way (either an organization has it or does not). Social license is closely related to public trust, and where publics view a particular institution as trustworthy it is more likely to have social license to engage in activities such as the collection and use of personal data7.

The question of how the leaders of an organization might better understand whether they have social license for a particular set of activities has also been addressed in the literature. In a review of literature on social license, Moffat et al. highlighted disagreement in the research community about whether social license can be accurately measured4. Certain groups of researchers emphasize that because of the intangible nature of social license, accurate measurement will never truly be possible. Others propose conceptual models of the determinants of social license, and establish surveys that assess those determinants to indicate the presence or absence of social license in a given context. However, accurate measurement of social license remains a point of debate….(More)”.

How to fix the GDPR’s frustration of global biomedical research

Curated on Posted on by Stefaan Verhulst

Jasper Bovenberg, David Peloquin, Barbara Bierer, Mark Barnes, and Bartha Maria Knoppers at Science: “Since the advent of the European Union (EU) General Data Protection Regulation (GDPR) in 2018, the biomedical research community has struggled to share data with colleagues and consortia outside the EU, as the GDPR limits international transfers of personal data. A July 2020 ruling of the Court of Justice of the European Union (CJEU) reinforced obstacles to sharing, and even data transfer to enable essential research into coronavirus disease 2019 (COVID-19) has been restricted in a recent Guidance of the European Data Protection Board (EDPB). We acknowledge the valid concerns that gave rise to the GDPR, but we are concerned that the GDPR’s limitations on data transfers will hamper science globally in general and biomedical science in particular (see the text box) (1)—even though one stated objective of the GDPR is that processing of personal data should serve humankind, and even though the GDPR explicitly acknowledges that the right to the protection of personal data is not absolute and must be considered in relation to its function in society and be balanced against other fundamental rights. We examine whether there is room under the GDPR for EU biomedical researchers to share data from the EU with the rest of the world to facilitate biomedical research. We then propose solutions for consideration by either the EU legislature, the EU Commission, or the EDPB in its planned Guidance on the processing of health data for scientific research. Finally, we urge the EDPB to revisit its recent Guidance on COVID-19 research….(More)“.

Why we must break the constraints of the industrial model of government

Curated on Posted on by Stefaan Verhulst

Max Beverton Palmer at the New Statesman: “…In practice, governments must shift from delivering what they always have to ensuring people’s needs are met in the best possible way. This should open up delivery to partners from both the private and charity sectors, where they can provide a better service that delivers better value to citizens, and much greater engagement with the public.

To manage this shift, leaders will need to resolve three key trade-offs.

First, states must be able to give up control to encourage innovation while protecting quality and in-house capacity. They must create new frameworks to assess where to encourage more open policymaking and delivery and where to double down on the competencies and infrastructure only they can provide. Technology can help here, creating new levers to protect the public interest by governing services’ access to government platforms and datasets akin to app store guidelines.

Second, states must reorganise around scale economies underpinned by technology while moving delivery closer to people’s lives. They should provide the foundations that allow new services to operate, while letting go of controlling the last mile of service delivery. A better way forward is a more collaborative approach that encourages communities, charities and companies to design more tailored services on top of public-controlled infrastructure, enabling people to choose those which best meet their needs.

Third, governments must be able to better listen, engage with and adapt to peoples’ views without descending into mob-rule. A core part of product and service design both in business and in the public sector is iterating delivery according to user needs, but the feedback loops in policymaking are comparably non-existent. New tools can help leaders understand the plurality of public opinions and address the growing disconnect between public institutions and those they represent.

MaxGetting from the status quo to this more open model will be challenging. But action in four priority areas should provide a starting point: infrastructure, organisation, competition and engagement….(More)”

The secret to building a smart city that’s antiracist

Curated on Posted on by Stefaan Verhulst

Article by Eliza McCullough: “….Instead of a smart city model that extracts from, surveils, and displaces poor people of color, we need a democratic model that allows community members to decide how technological infrastructure operates and to ensure the equitable distribution of benefits. Doing so will allow us to create cities defined by inclusion, shared ownership, and shared prosperity.

In 2016, Barcelona, for example, launched its Digital City Plan, which aims to empower residents with control of technology used in their communities. The document incorporates over 8,000 proposals from residents and includes plans for open source software, government ownership of all ICT infrastructure, and a pilot platform to help citizens maintain control over their personal data. As a result, the city now has free applications that allow residents to easily propose city development ideas, actively participate in city council meetings, and choose how their data is shared.

In the U.S., we need a framework for tech sovereignty that incorporates a racial equity approach: In a racist society, race neutrality facilitates continued exclusion and exploitation of people of color. Digital Justice Lab in Toronto illustrates one critical element of this kind of approach: access to information. In 2018, the organization gave community groups a series of grants to hold public events that shared resources and information about digital rights. Their collaborative approach intentionally focuses on the specific needs of people of color and other marginalized groups.

The turn toward intensified surveillance infrastructure in the midst of the coronavirus outbreak makes the need to adopt such practices all the more crucial. Democratic tech models that uplift marginalized populations provide us the chance to build a city that is just and open to everyone….(More)”.

Why Modeling the Spread of COVID-19 Is So Damn Hard


Curated on Posted on by Stefaan Verhulst

Matthew Hutson at IEEE Spectrum: “…Researchers say they’ve learned a lot of lessons modeling this pandemic, lessons that will carry over to the next.

The first set of lessons is all about data. Garbage in, garbage out, they say. Jarad Niemi, an associate professor of statistics at Iowa State University who helps run the forecast hub used by the CDC, says it’s not clear what we should be predicting. Infections, deaths, and hospitalization numbers each have problems, which affect their usefulness not only as inputs for the model but also as outputs. It’s hard to know the true number of infections when not everyone is tested. Deaths are easier to count, but they lag weeks behind infections. Hospitalization numbers have immense practical importance for planning, but not all hospitals release those figures. How useful is it to predict those numbers if you never have the true numbers for comparison? What we need, he said, is systematized random testing of the population, to provide clear statistics of both the number of people currently infected and the number of people who have antibodies against the virus, indicating recovery. Prakash, of Georgia Tech, says governments should collect and release data quickly in centralized locations. He also advocates for central repositories of policy decisions, so modelers can quickly see which areas are implementing which distancing measures.

Researchers also talked about the need for a diversity of models. At the most basic level, averaging an ensemble of forecasts improves reliability. More important, each type of model has its own uses—and pitfalls. An SEIR model is a relatively simple tool for making long-term forecasts, but the devil is in the details of its parameters: How do you set those to match real-world conditions now and into the future? Get them wrong and the model can head off into fantasyland. Data-driven models can make accurate short-term forecasts, and machine learning may be good for predicting complicated factors. But will the inscrutable computations of, for instance, a neural network remain reliable when conditions change? Agent-based models look ideal for simulating possible interventions to guide policy, but they’re a lot of work to build and tricky to calibrate.

Finally, researchers emphasize the need for agility. Niemi of Iowa State says software packages have made it easier to build models quickly, and the code-sharing site GitHub lets people share and compare their models. COVID-19 is giving modelers a chance to try out all their newest tools, says Meyers, of the University of Texas. “The pace of innovation, the pace of development, is unlike ever before,” she says. “There are new statistical methods, new kinds of data, new model structures.”…(More)”.

Public Sector Tech: New tools for the new normal

Curated on Posted on by Stefaan Verhulst

Special issue by ZDNet exploring “how new technologies like AI, cloud, drones, and 5G are helping government agencies, public organizations, and private companies respond to the events of today and tomorrow…:

The Cruel New Era of Data-Driven Deportation

Curated on Posted on by Stefaan Verhulst

Article by Alvaro M. Bedoya: “For a long time, mass deportations were a small-data affair, driven by tips, one-off investigations, or animus-driven hunches. But beginning under George W. Bush, and expanding under Barack Obama, ICE leadership started to reap the benefits of Big Data. The centerpiece of that shift was the “Secure Communities” program, which gathered the fingerprints of arrestees at local and state jails across the nation and compared them with immigration records. That program quickly became a major driver for interior deportations. But ICE wanted more data. The agency had long tapped into driver address records through law enforcement networks. Eyeing the breadth of DMV databases, agents began to ask state officials to run face recognition searches on driver photos against the photos of undocumented people. In Utah, for example, ICE officers requested hundreds of face searches starting in late 2015. Many immigrants avoid contact with any government agency, even the DMV, but they can’t go without heat, electricity, or water; ICE aimed to find them, too. So, that same year, ICE paid for access to a private database that includes the addresses of customers from 80 national and regional electric, cable, gas, and telephone companies.

Amid this bonanza, at least, the Obama administration still acknowledged red lines. Some data were too invasive, some uses too immoral. Under Donald Trump, these limits fell away.

In 2017, breaking with prior practice, ICE started to use data from interviews with scared, detained kids and their relatives to find and arrest more than 500 sponsors who stepped forward to take in the children. At the same time, ICE announced a plan for a social media monitoring program that would use artificial intelligence to automatically flag 10,000 people per month for deportation investigations. (It was scuttled only when computer scientists helpfully indicated that the proposed system was impossible.) The next year, ICE secured access to 5 billion license plate scans from public parking lots and roadways, a hoard that tracks the drives of 60 percent of Americans—an initiative blocked by Department of Homeland Security leadership four years earlier. In August, the agency cut a deal with Clearview AI, whose technology identifies people by comparing their faces not to millions of driver photos, but to 3 billion images from social media and other sites. This is a new era of immigrant surveillance: ICE has transformed from an agency that tracks some people sometimes to an agency that can track anyone at any time….(More)”.