The Unexpected Power of Google-Doc Activism


 at The Cut: “Earlier this month, after major news outlets published detailed allegations of abuse and harassment by Harvey Weinstein, an anonymous woman created a public Google spreadsheet titled Shitty Media Men. It was a space for other anonymous women to name men in media who had exhibited bad behavior ranging from sleazy DMs to rape. There were just a few rules: “Please never name an accuser,” it said at the top. “Please never share this spreadsheet with a man.” The document was live for less than 48 hours, in which time it was shared with dozens of women — and almost certainly a few men.

The goal of the document was not public accountability, according to its creator. It was to privately warn other women, especially those who are not well connected in the industry, about which men in their profession to avoid. This is information women have always shared among themselves, at after-work drinks and in surreptitious chat messages, but the Google Doc sought to collect it in a way that transcended any one woman’s immediate social network. And because the goal was to occupy a kind of middle ground — not public, not quite private either — with little oversight, it made perfect sense that the information appeared as a Google Doc.

Especially in the year since the election, the shared Google Doc has become a familiar way station on the road to collective political action. Shared documents are ideal for collecting resources in one place quickly and easily, without gatekeepers, because they’re free and easy to use. They have been used to crowdsource tweets and hashtags for pushing back against Trump’s first State of the Union address, to spread information on local town-hall events with members of Congress, and to collect vital donation and evacuee info for people affected by the fires in Northern California. A shared Google Doc allows collaborators to work together across time zones and is easy to update as circumstances change.

But perhaps most notably, a Google Doc can be technically public while functionally quite private, allowing members of a like-minded community to reach beyond their immediate friends and collaborators while avoiding the abuse and trolling that comes with publishing on other platforms….(More)”.

Linux Foundation Debuts Community Data License Agreement


Press Release: “The Linux Foundation, the nonprofit advancing professional open source management for mass collaboration, today announced the Community Data License Agreement(CDLA) family of open data agreements. In an era of expansive and often underused data, the CDLA licenses are an effort to define a licensing framework to support collaborative communities built around curating and sharing “open” data.

Inspired by the collaborative software development models of open source software, the CDLA licenses are designed to enable individuals and organizations of all types to share data as easily as they currently share open source software code. Soundly drafted licensing models can help people form communities to assemble, curate and maintain vast amounts of data, measured in petabytes and exabytes, to bring new value to communities of all types, to build new business opportunities and to power new applications that promise to enhance safety and services.

The growth of big data analytics, machine learning and artificial intelligence (AI) technologies has allowed people to extract unprecedented levels of insight from data. Now the challenge is to assemble the critical mass of data for those tools to analyze. The CDLA licenses are designed to help governments, academic institutions, businesses and other organizations open up and share data, with the goal of creating communities that curate and share data openly.

For instance, if automakers, suppliers and civil infrastructure services can share data, they may be able to improve safety, decrease energy consumption and improve predictive maintenance. Self-driving cars are heavily dependent on AI systems for navigation, and need massive volumes of data to function properly. Once on the road, they can generate nearly a gigabyte of data every second. For the average car, that means two petabytes of sensor, audio, video and other data each year.

Similarly, climate modeling can integrate measurements captured by government agencies with simulation data from other organizations and then use machine learning systems to look for patterns in the information. It’s estimated that a single model can yield a petabyte of data, a volume that challenges standard computer algorithms, but is useful for machine learning systems. This knowledge may help improve agriculture or aid in studying extreme weather patterns.

And if government agencies share aggregated data on building permits, school enrollment figures, sewer and water usage, their citizens benefit from the ability of commercial entities to anticipate their future needs and respond with infrastructure and facilities that arrive in anticipation of citizens’ demands.

“An open data license is essential for the frictionless sharing of the data that powers both critical technologies and societal benefits,” said Jim Zemlin, Executive Director of The Linux Foundation. “The success of open source software provides a powerful example of what can be accomplished when people come together around a resource and advance it for the common good. The CDLA licenses are a key step in that direction and will encourage the continued growth of applications and infrastructure.”…(More)”.

The role of policy entrepreneurs in open government data policy innovation diffusion: An analysis of Australian Federal and State Governments


Paper by Akemi TakeokaChatfield and Christopher G.Reddick: “Open government data (OGD) policy differs substantially from the existing Freedom of Information policies. Consequently OGD can be viewed as a policy innovation. Drawing on both innovation diffusion theory and its application to public policy innovation research, we examine Australia’s OGD policy diffusion patterns at both the federal and state government levels based on the policy adoption timing and CKAN portal “Organization” and “Category” statistics. We found that state governments that had adopted OGD policies earlier had active policy entrepreneurs (or lead departments/agencies) responsible for the policy innovation diffusion across the different government departments. We also found that their efficacy ranking was relatively high in terms of OGD portal openness when openness is measured by the greater number of datasets proactively and systematically published through their OGD portals. These findings have important implications for the role played by OGD policy entrepreneurs in openly sharing the government-owned datasets with the public….(More)”.

Are you doing what’s needed to get the state to respond to its citizens? Or are you part of the problem?


Vanessa Herringshaw at Making All Voices Count: ” …I’ve been reading over the incredibly rich and practically-orientated research and practice papers already on the Making All Voices Count website, and some of those coming out soon. There’s a huge amount of useful and challenging learning, and I’ll be putting out a couple of papers summarising some important threads later this year.

But as different civic tech and accountability actors prepare to come together in Brighton for Making All Voices Count’s final learning event later this week, I’m going to focus here on three things that really stood out and would benefit from the kind of ‘group grappling’ that such a gathering can best support. And I aim to be provocative!

  1. Improving state responsiveness to citizens is a complex business – even more than we realised – and a lot more complex than most interventions are designed to address. If we don’t address this complexity, our interventions won’t work. And that risks making things worse, not better.
  2. It’s clear we need to make more of a shift from narrow, ‘tactical’ approaches to more complex, systems-based ‘strategic’ approaches. Thinking is developing on how to do this in theory. But it’s not clear that our current institutional approaches will support, or even allow, a major shift in practice.
  3. So when we each look at our individual roles and those of our organisations, are we part of the solution, or part of the problem?

Let’s look at each of these in turn….(More)”

2017 CPA-Zicklin Index of Corporate Political Disclosure and Accountability


Introduction to the 2017 CPA-Zicklin Index by Morris Pearl: “In our modern financial system, investors, by necessity, delegate virtually all control over the businesses in which they invest to a board of directors. That board then, perhaps by necessity, perhaps not, often delegates virtually all control to the officers who run the company day to day. That usually works out pretty well. The interests of the officers are generally aligned with that of the shareholders, and most boards have a compensation committee which (hopefully) deals with the obvious conflicts around the pay of the officers. That, however, is not enough. Occasionally the officers use corporate resources for politics, sometimes with disastrous consequences. The practice of spending money on politics can open up the corporation to both subtle and not-so-subtle coercion from government officials. Indeed, the first campaign finance regulations were favored by business people who found themselves under a barrage of demands for money from government officials who had some power over their businesses. There are some things that businesses can do to defend themselves. Chief among those are:

  • An official corporate policy on high level approval of political expenditures. Based on my experience, telling someone soliciting a donation that they are welcome to make their case, publicly, to a board committee, can be great fun.
  • Openness – making records of whatever the business does available to the general public. Based again on my experience, people doing things that they don’t want to be publicly known are often doing things that they should not be doing.

We do not have the ability to end the practice, but by publicly giving companies credit for doing those two things, the CPA-Zicklin Index is making a difference….(Full Report)”.

Enabling Blockchain Innovation in the U.S. Federal Government


Primer by the American Council for Technology – Industry Advisory Council: “… intended to be a foundational tool in the understanding of blockchain and its use cases within the United States federal government. To that end, it should help allay the concerns that some may have about this new technology by providing an introduction to blockchain and its related technologies, and how blockchain can be safely and securely applied to the right government use cases. Blockchain has the potential to help government to reduce fraud, errors and the cost of paper-intensive processes, while enabling collaboration across multiple divisions and agencies to provide more efficient and effective services to citizens. Moreover, the adoption of blockchain may also allow governmental agencies to provide new value-added services to businesses and others which can generate new sources of revenue for these agencies….(More)”.

Our laws don’t do enough to protect our health data


 at the Conversation: “A particularly sensitive type of big data is medical big data. Medical big data can consist of electronic health records, insurance claims, information entered by patients into websites such as PatientsLikeMeand more. Health information can even be gleaned from web searches, Facebook and your recent purchases.

Such data can be used for beneficial purposes by medical researchers, public health authorities, and healthcare administrators. For example, they can use it to study medical treatments, combat epidemics and reduce costs. But others who can obtain medical big data may have more selfish agendas.

I am a professor of law and bioethics who has researched big data extensively. Last year, I published a book entitled Electronic Health Records and Medical Big Data: Law and Policy.

I have become increasingly concerned about how medical big data might be used and who could use it. Our laws currently don’t do enough to prevent harm associated with big data.

What your data says about you

Personal health information could be of interest to many, including employers, financial institutions, marketers and educational institutions. Such entities may wish to exploit it for decision-making purposes.

For example, employers presumably prefer healthy employees who are productive, take few sick days and have low medical costs. However, there are laws that prohibit employers from discriminating against workers because of their health conditions. These laws are the Americans with Disabilities Act (ADA) and the Genetic Information Nondiscrimination Act. So, employers are not permitted to reject qualified applicants simply because they have diabetes, depression or a genetic abnormality.

However, the same is not true for most predictive information regarding possible future ailments. Nothing prevents employers from rejecting or firing healthy workers out of the concern that they will later develop an impairment or disability, unless that concern is based on genetic information.

What non-genetic data can provide evidence regarding future health problems? Smoking status, eating preferences, exercise habits, weight and exposure to toxins are all informative. Scientists believe that biomarkers in your blood and other health details can predict cognitive decline, depression and diabetes.

Even bicycle purchases, credit scores and voting in midterm elections can be indicators of your health status.

Gathering data

How might employers obtain predictive data? An easy source is social media, where many individuals publicly post very private information. Through social media, your employer might learn that you smoke, hate to exercise or have high cholesterol.

Another potential source is wellness programs. These programs seek to improve workers’ health through incentives to exercise, stop smoking, manage diabetes, obtain health screenings and so on. While many wellness programs are run by third party vendors that promise confidentiality, that is not always the case.

In addition, employers may be able to purchase information from data brokers that collect, compile and sell personal information. Data brokers mine sources such as social media, personal websites, U.S. Census records, state hospital records, retailers’ purchasing records, real property records, insurance claims and more. Two well-known data brokers are Spokeo and Acxiom.

Some of the data employers can obtain identify individuals by name. But even information that does not provide obvious identifying details can be valuable. Wellness program vendors, for example, might provide employers with summary data about their workforce but strip away particulars such as names and birthdates. Nevertheless, de-identified information can sometimes be re-identified by experts. Data miners can match information to data that is publicly available….(More)”.

The Arsenal of Exclusion and Inclusion


Book by Tobias Armborst, Daniel D’Oca and Georgeen Theodore: “Urban History 101 teaches us that the built environment is not the product of invisible, uncontrollable market forces, but of human-made tools that could have been used differently (or not at all). The Arsenal of Exclusion & Inclusion is an encyclopedia of 202 tools–or what we call “weapons”–used by architects, planners, policy-makers, developers, real estate brokers, activists, and other urban actors in the United States use to restrict or increase access to urban space. The Arsenal of Exclusion & Inclusion inventories these weapons, examines how they have been used, and speculates about how they might be deployed (or retired) to make more open cities in which more people feel welcome in more spaces.

The Arsenal of Exclusion & Inclusion includes minor, seemingly benign weapons like no loitering signs and bouncers, but also big, headline-grabbing things like eminent domaon and city-county consolidation. It includes policies like expulsive zoning and annexation, but also practices like blockbusting, institutions like neighborhood associations, and physical things like bombs and those armrests that park designers put on benches to make sure homeless people don’t get too comfortable. It includes historical things that aren’t talked about too much any more (e.g., ugly laws), things that seem historical but aren’t (e.g., racial steering), and things that are brand new (e.g., aging improvement district).

With contributions from over fifty of the best minds in architecture, urban planning, urban history, and geography, The Arsenal of Exclusion & Inclusion offers a wide-ranging view of the policies, institutions, and social practices that shape our cities. It can be read as a historical account of the making of the modern American city, a toolbox of best practices for creating better, more just spaces, or as an introduction to the process of city-making in The United States….(More)”.

Reboot for the AI revolution


Yuval Noah Harari in Nature: “The ongoing artificial-intelligence revolution will change almost every line of work, creating enormous social and economic opportunities — and challenges. Some believe that intelligent computers will push humans out of the job market and create a new ‘useless class’; others maintain that automation will generate a wide range of new human jobs and greater prosperity for all. Almost everybody agrees that we should take action to prevent the worst-case scenarios….

Governments might decide to deliberately slow down the pace of automation, to lessen the resulting shocks and allow time for readjustments. But it will probably be both impossible and undesirable to prevent automation and job loss completely. That would mean giving up the immense positive potential of AI and robotics. If self-driving vehicles drive more safely and cheaply than humans, it would be counterproductive to ban them just to protect the jobs of taxi and lorry drivers.

A more sensible strategy is to create new jobs. In particular, as routine jobs are automated, opportunities for new non-routine jobs will mushroom. For example, general physicians who focus on diagnosing known diseases and administering familiar treatments will probably be replaced by AI doctors. Precisely because of that, there will be more money to pay human experts to do groundbreaking medical research, develop new medications and pioneer innovative surgical techniques.

This calls for economic entrepreneurship and legal dexterity. Above all, it necessitates a revolution in education…Creating new jobs might prove easier than retraining people to fill them. A huge useless class might appear, owing to both an absolute lack of jobs and a lack of relevant education and mental flexibility….

With insights gleaned from early warning signs and test cases, scholars should strive to develop new socio-economic models. The old ones no longer hold. For example, twentieth-century socialism assumed that the working class was crucial to the economy, and socialist thinkers tried to teach the proletariat how to translate its immense economic power into political clout. In the twenty-first century, if the masses lose their economic value they might have to struggle against irrelevance rather than exploitation….The challenges posed in the twenty-first century by the merger of infotech and biotech are arguably bigger than those thrown up by steam engines, railways, electricity and fossil fuels. Given the immense destructive power of our modern civilization, we cannot afford more failed models, world wars and bloody revolutions. We have to do better this time….(More)”

Laboratories for news? Experimenting with journalism hackathons


Jan Lauren Boyles in Journalism: “Journalism hackathons are computationally based events in which participants create news product prototypes. In the ideal case, the gatherings are rooted in local community, enabling a wide set of institutional stakeholders (legacy journalists, hacker journalists, civic hackers, and the general public) to gather in conversation around key civic issues. This study explores how and to what extent journalism hackathons operate as a community-based laboratory for translating open data from practitioners to the public. Surfaced from in-depth interviews with event organizers encompassing nine countries, the findings illustrate that journalism hackathons are most successful when collaboration integrates civic organizations and community leaders….(More)”.