COVID Response Alliance for Social Entrepreneurs


Article by François Bonnici: “…Social innovators and social entrepreneurs have been working to solve market failures and demonstrate more sustainable models to build inclusive economies for years. The Schwab Foundation 2020 Impact Report “Two Decades of Impact” demonstrated how the network of 400 leading social innovators and entrepreneurs it supports have improved the lives of more than 622 million people, protecting livelihoods, driving movements for social inclusion and environmental sustainability, and providing improved access to health, sanitation, education and energy.

From providing reliable information, services and care for the most vulnerable, to developing community tracing initiatives or mental health support through mobile phones, the work of social entrepreneurs is even more critical during the COVID-19 pandemic, as they reach those who the market and governments are unable to account for.

But right now, these front-line organizations face severe constraints or even bankruptcy. Decades of work in the impact sector are at stake.

Over the past four decades, a sophisticated impact ecosystem has emerged to support the work of social innovators and impact enterprises. This includes funding provided by capital sources ranging from philanthropy and impact investing, intermediaries providing certification and standards, peer networks of learning and policy and regulation of this new “social economy” seeking to embed inclusive and sustainable organizational approaches imbued with principles of equality, justice and respect for our planet.

From this ecosystem, 40 leading global organizations collectively supporting more than 15,000 social entrepreneurs have united to launch the COVID Response Alliance for Social Entrepreneurs. The aim is to share knowledge, experience and resources to coordinate and amplify social entrepreneurs’ response to COVID-19….(More)”.

Secondhand Smoke, Moral Sanctions, and How We Should Respond to COVID-19


Article by Barry Schwartz: “How did we get from that day to this one, with widespread smoking bans in public places? The answer, I believe, was the discovery of the effects of secondhand smoke. When I smoked, it harmed innocent bystanders. It harmed children, including my own. The research on secondhand smoke began in the 1960s, showing negative effects on lab animals. As the work continued, it left no doubt that secondhand smoke contributes to asthma, cardiovascular disease, many types of cancer, stroke, cognitive impairment, and countless other maladies. These sorts of findings empowered people to demand, not request, that others put out their cigarettes. The secondhand smoke research led eventually to all the regulation that we now take for granted.

Why did this research change public attitudes and change them so fast—in a single generation? The answer, I think, is that research on secondhand smoke took an individual (perhaps foolish) choice and moralized it, by emphasizing its effects on others. It was no longer simply dumb to smoke; it was immoral. And that changed everything.

Psychologist Paul Rozin has studied the process of moralization. When activities get moralized, they move from being matters of individual discretion to being matters of obligation. Smoking went from being an individual consumer decision to being a transgression. And the process of moralization can go in the other direction, as we have seen, for most people, in the case of sexuality. In recent years, homosexuality has been “demoralized,” and moral sanctions against it have slowly been melting away….(More)”.

The Bigot in the Machine: Bias in Algorithmic Systems


Article by Barbara Fister: “We are living in an “age of algorithms.” Vast quantities of information are collected, sorted, shared, combined, and acted on by proprietary black boxes. These systems use machine learning to build models and make predictions from data sets that may be out of date, incomplete, and biased. We will explore the ways bias creeps into information systems, take a look at how “big data,” artificial intelligence and machine learning often amplify bias unwittingly, and consider how these systems can be deliberately exploited by actors for whom bias is a feature, not a bug. Finally, we’ll discuss ways we can work with our communities to create a more fair and just information environment….(More)”.

Why local data is the key to successful place making


Blog by Sally Kerr: “The COVID emergency has brought many challenges that were unimaginable a few months ago. The first priorities were safety and health, but when lockdown started one of the early issues was accessing and sharing local data to help everyone deal with and live through the emergency. Communities grappled with the scarcity of local data, finding it difficult to source for some services, food deliveries and goods. This was not a new issue, but the pandemic brought it into sharp relief.

Local data use covers a broad spectrum. People moving to a new area want information about the environment — schools, amenities, transport, crime rates and local health. For residents, continuing knowledge of business opening hours, events, local issues, council plans and roadworks remains important, not only for everyday living but to help understand issues and future plans that will change their environment. Really local data (hyperlocal data) is either fragmented or unavailable, making it difficult for local people to stay informed, whilst larger data sets about an area (e.g. population, school performance) are not always easy to understand or use. They sit in silos owned by different sectors, on disparate websites, usually collated for professional or research use.

Third sector organisations in a community will gather data relevant to their work such as contacts and event numbers but may not source wider data sets about the area, such as demographics, to improve their work. Using this data could strengthen future grant applications by validating their work. For Government or Health bodies carrying out place making community projects, there is a reliance on their own or national data sources supplemented with qualitative data snapshots. Their dependence on tried and tested sources is due to time and resource pressures but means there is no time to gather that rich seam of local data that profiles individual needs.

Imagine a future community where local data is collected and managed together for both official organisations and the community itself. Where there are shared aims and varied use. Current and relevant data would be accessible and easy to understand, provided in formats that suit the user — from data scientist to school child. A curated data hub would help citizens learn data skills and carry out collaborative projects on anything from air quality to local biodiversity, managing the data and offering increased insight and useful validation for wider decision making. Costs would be reduced with duplication and effort reduced….(More)”.

Scraping Court Records Data to Find Dirty Cops


Article by Lawsuit.org: “In the 2002 dystopian sci-fi film “Minority Report,” law enforcement can manage crime by “predicting” illegal behavior before it happens. While fiction, the plot is intriguing and contributes to the conversation on advanced crime-fighting technology. However, today’s world may not be far off.

Data’s role in our lives and more accessibility to artificial intelligence is changing the way we approach topics such as research, real estate, and law enforcement. In fact, recent investigative reporting has shown that “dozens of [American] cities” are now experimenting with predictive policing technology.

Despite the current controversy surrounding predictive policing, it seems to be a growing trend that has been met with little real resistance. We may be closer to policing that mirrors the frightening depictions in “Minority Report” than we ever thought possible. 

Fighting Fire With Fire

In its current state, predictive policing is defined as:

“The usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. Predictive policing methods fall into four general categories: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators’ identities, and methods for predicting victims of crime.”

While it might not be possible to prevent predictive policing from being employed by the criminal justice system, perhaps there are ways we can create a more level playing field: One where the powers of big data analysis aren’t just used to predict crime, but also are used to police law enforcement themselves.

Below, we’ve provided a detailed breakdown of what this potential reality could look like when applied to one South Florida county’s public databases, along with information on how citizens and communities can use public data to better understand the behaviors of local law enforcement and even individual police officers….(More)”.

How Data-Driven Cities Respond Swiftly and Effectively to COVID-19


Blog Post by Jennifer Park, Lauren Su, Lisa Fiedler, and Madeleine Weatherhead: “Since January of this year, the novel coronavirus has swept rapidly throughout the United States, leaving no city untouched. To contain the virus’ spread and protect residents’ health and livelihoods, local leaders have had to act swiftly and decisively. It is a challenge in scope and scale unlike any other in recent history — and it has underscored the power of data to guide life-and-death decisions and build trust.

Take, for example, Los Angeles. As cities across the country began issuing states of emergency and acting to promote public health, Mayor Eric Garcetti quickly identified the city’s response priorities: supporting families, small businesses, healthcare workers, and unhoused Angelenos, and increasing the healthcare equipment and testing kits available for the city. Mayor Garcetti tapped his Chief Information Officer and Innovation Team to collect and analyze data, to inform decisions, and share real-time information publicly.

A snapshot of Los Angeles’ publicly shared data from one of the city’s daily COVID-19 summary briefings. Image courtesy of the City of Los Angeles’ Innovation Team.

The Mayor was soon conducting daily briefings, updating the public on the latest virus-related data and informing city residents about various decisions made by the city — from pausing parking rules enforcement to opening thousands of temporary shelter beds. He used data to justify key decisions, linking stay-at-home orders to a decrease in COVID-19 cases from week to week.

Los Angeles’ swift response built on an existing culture of leveraging data to set goals, make decisions, and communicate with the public. Its leaders are now seeing the positive impact of having invested in foundational data capacity — regular tracking of cases, hospital capacity, and infection rates have proven to be vital to helping and accelerating the city’s responses to COVID-19.

Other cities, too, have leaned on established data practices and infrastructure in their response efforts, both to the benefit of their residents and to lay a stronger foundation to guide recovery….(More)“.

How Data Can Map and Make Racial Inequality More Visible (If Done Responsibly)


Reflection Document by The GovLab: “Racism is a systemic issue that pervades every aspect of life in the United States and around the world. In recent months, its corrosive influence has been made starkly visible, especially on Black people. Many people are hurting. Their rage and suffering stem from centuries of exclusion and from being subject to repeated bias and violence. Across the country, there have been protests decrying racial injustice. Activists have called upon the government to condemn bigotry and racism, to act against injustice, to address systemic and growing inequality.

Institutions need to take meaningful action to address such demands. Though racism is not experienced in the same way by all communities of color, policymakers must respond to the anxieties and apprehensions of Black people as well as those of communities of color more generally. This work will require institutions and individuals to reflect on how they may be complicit in perpetuating structural and systematic inequalities and harm and to ask better questions about the inequities that exist in society (laid bare in both recent acts of violence and in racial disadvantages in health outcomes during the ongoing COVID-19 crisis). This work is necessary but unlikely to be easy. As Rashida Richardson, Director of Policy Research at the AI Now Institute at NYU notes:

“Social and political stratifications also persist and worsen because they are embedded into our social and legal systems and structures. Thus, it is difficult for most people to see and understand how bias and inequalities have been automated or operationalized over time.”

We believe progress can be made, at least in part, through responsible data access and analysis, including increased availability of (disaggregated) data through data collaboration. Of course, data is only one part of the overall picture, and we make no claims that data alone can solve such deeply entrenched problems. Nonetheless, data can have an impact by making inequalities resulting from racism more quantifiable and inaction less excusable.

…Prioritizing any of these topics will also require increased community engagement and participatory agenda setting. Likewise, we are deeply conscious that data can have a negative as well as positive impact and that technology can perpetuate racism when designed and implemented without the input and participation of minority communities and organizations. While our report here focuses on the promise of data, we need to remain aware of the potential to weaponize data against vulnerable and already disenfranchised communities. In addition, (hidden) biases in data collected and used in AI algorithms, as well as in a host of other areas across the data life cycle, will only exacerbate racial inequalities if not addressed….(More)”

ALSO: The piece is supplemented by a crowdsourced listing of Data-Driven Efforts to Address Racial Inequality.

Science Alone Can’t Solve Covid-19. The Humanities Must Help


Article by Anna Magdalena Elsner and Vanesa Rampton: “…To judge by news reports, the humanities are “nice to have” — think of the entertainment value of balcony music or an online book club — but not essential for helping resolve the crisis. But as the impacts of public health measures ripple through societies, languages, and cultures, thinking critically about our reaction to SARS-CoV-2 is as important as new scientific findings about the virus. The humanities can contribute to a deeper understanding of the entrenched mentalities and social dynamics that have informed society’s response to this crisis. And by encouraging us to turn a mirror on our own selves, they prompt us to question whether we are the rational individuals that we aspire to be, and whether we are sufficiently equipped, as a society, to solve our own problems.

WE ARE CREATURES of stories. Scholarship in the medical humanities has persistently emphasized that narratives are crucial for how humans experience illness. For instance, Felicity Callard, a professor of human geography, has written about how a lack of “narrative anchors” during the early days of the Covid-19 pandemic led to confusion over what counts as a “mild” symptom and what the “normal” course of the disease looks like, ultimately heightening the suffering the disease caused. Existing social conditions, previous illnesses and disabilities, a sense of precarity — all of these factors influence our attitude toward disease and how it affects the way we exist in the world.

We are entangled with nature. We tend to imagine a human world separate from natural laws, but the novel coronavirus reminds us of the extent to which we are intricately bound up with the life around us. As philosopher David Benatar has noted, the emergence of the new coronavirus is most likely a result of our treatment of nonhuman animals. The virus has forced us to alter our behavior, likely triggering higher rates of anxiety, depression, and other stress-related responses. In essence, it has shown how what we think of as “non-human” can become a fundamental part of our lives in unexpected ways.

We react to crises in predictable fashion, and with foreseeable cognitive and moral failings. A growing body of work suggests that, although we want to act on knowledge, it is our nature to react instinctively and short-sightedly. Images of overcapacity intensive care units, for example, galvanize us to comply with lockdown restrictions, even as we have much more difficulty acting prudentially to prevent the emergence of such viruses. The desire for a quick solution has fueled a race for a vaccine, even though — as historian of science David Jones has noted — failures and false starts have been recurring themes in past attempts to handle epidemics. Even if a vaccine were available, it wouldn’t erase the striking disparities in health outcomes across class, race, and gender…(More)”.

Technical Excellence and Scale


Cory Doctorow at EFF: “In America, we hope that businesses will grow by inventing amazing things that people love – rather than through deep-pocketed catch-and-kill programs in which every competitor is bought and tamed before it can grow to become a threat. We want vibrant, competitive, innovative markets where companies vie to create the best products. Growth solely through merger-and-acquisition helps create a world in which new firms compete to be bought up and absorbed into the dominant players, and customers who grow dissatisfied with a product or service and switch to a “rival” find that they’re still patronizing the same company—just another division.

To put it bluntly: we want companies that are good at making things as well as buying things.

This isn’t the whole story, though.

Small companies with successful products can become victims of their own success. As they are overwhelmed by eager new customers, they are strained beyond their technical and financial limits – for example, they may be unable to buy server hardware fast enough, and unable to lash that hardware together in efficient ways that let them scale up to meet demand.

When we look at the once small, once beloved companies that are now mere divisions of large, widely mistrusted ones—Instagram and Facebook; YouTube and Google; Skype and Microsoft; DarkSkies and Apple—we can’t help but notice that they are running at unimaginable scale, and moreover, they’re running incredibly well.

These services were once plagued with outages, buffering delays, overcapacity errors, slowdowns, and a host of other evils of scale. Today, they run so well that outages are newsworthy events.

There’s a reason for that: big tech companies are really good at being big. Whatever you think of Amazon, you can’t dispute that it gets a lot of parcels from A to B with remarkably few bobbles. Google’s search results arrive in milliseconds, Instagram photos load as fast as you can scroll them, and even Skype is far more reliable than in the pre-Microsoft days. These services have far more users than they ever did as independents, and yet, they are performing better than they did in those early days.

Can we really say that this is merely “buying things” and not also “making things?” Isn’t this innovation? Isn’t this technical accomplishment? It is. Does that mean big = innovative? It does not….(More)”.

The technology of witnessing brutality


Axios: “The ways Americans capture and share records of racist violence and police misconduct keep changing, but the pain of the underlying injustices they chronicle remains a stubborn constant.

Driving the news: After George Floyd’s death at the hands of Minneapolis police sparked wide protests, Minnesota Gov. Tim Walz said, “Thank God a young person had a camera to video it.”

Why it matters: From news photography to TV broadcasts to camcorders to smartphones, improvements in the technology of witness over the past century mean we’re more instantly and viscerally aware of each new injustice.

  • But unless our growing power to collect and distribute evidence of injustice can drive actual social change, the awareness these technologies provide just ends up fueling frustration and despair.

For decades, still news photography was the primary channel through which the public became aware of incidents of racial injustice.

  • horrific 1930 photo of the lynching of J. Thomas Shipp and Abraham S. Smith, two black men in Marion, Indiana, brought the incident to national attention and inspired the song “Strange Fruit.” But the killers were never brought to justice.
  • Photos of the mutilated body of Emmett Till catalyzed a nationwide reaction to his 1955 lynching in Mississippi.

In the 1960s, television news footage brought scenes of police turning dogs and water cannons on peaceful civil rights protesters in Birmingham and Selma, Alabama into viewers’ living rooms.

  • The TV coverage was moving in both senses of the word.

In 1991, a camcorder tape shot by a Los Angeles plumber named George Holliday captured images of cops brutally beating Rodney King.

  • In the pre-internet era, it was only after the King tape was broadcast on TV that Americans could see it for themselves.

Over the past decade, smartphones have enabled witnesses and protesters to capture and distribute photos and videos of injustice quickly — sometimes, as it’s happening.

  • This power helped catalyze the Black Lives Matter movement beginning in 2013 and has played a growing role in broader public awareness of police brutality.

Between the lines: For a brief moment mid-decade, some hoped that the combination of a public well-supplied with video recording devices and requirements that police wear bodycams would introduce a new level of accountability to law enforcement.

The bottom line: Smartphones and social media deliver direct accounts of grief- and rage-inducing stories…(More)”.