media

Six or Seven Things Social Media Can Do For Democracy

Curated on June 6, 2018August 3, 2018 by Stefaan Verhulst

Ethan Zuckerman: “I am concerned that we’ve not had a robust conversation about what we want social media to do for us.

We know what social media does for platform companies like Facebook and Twitter: it generates enormous masses of user-generated content that can be monetized with advertising, and reams of behavioral data that make that advertising more valuable. Perhaps we have a sense for what social media does for us as individuals, connecting us to distant friends, helping us maintain a lightweight awareness of each other’s lives even when we are not co-present. Or perhaps it’s a machine for disappointment and envy, a window into lives better lived than our own. It’s likely that what social media does for us personally is a deeply idiosyncratic question, dependent on our own lives, psyches and decisions, better discussed with our therapists than spoken about in generalities.

I’m interested in what social media should do for us as citizens in a democracy. We talk about social media as a digital public sphere, invoking Habermas and coffeehouses frequented by the bourgeoisie. Before we ask whether the internet succeeds as a public sphere, we ought to ask whether that’s actually what we want it to be.

I take my lead here from journalism scholar Michael Schudson, who took issue with a hyperbolic statement made by media critic James Carey: “journalism as a practice is unthinkable except in the context of democracy; in fact, journalism is usefully understood as another name for democracy.” For Schudson, this was a step too far. Journalism may be necessary for democracy to function well, but journalism by itself is not democracy and cannot produce democracy. Instead, we should work to understand the “Six or Seven Things News Can Do for Democracy”, the title of an incisive essay Schudson wrote to anchor his book, Why Democracies Need an Unloveable Press….

In this same spirit, I’d like to suggest six or seven things social media can do for democracy. I am neither as learned or as wise as Schudson, so I fully expect readers to offer half a dozen functions that I’ve missed. In the spirit of Schudson’s public forum and Benkler’s digital public sphere, I offer these in the hopes of starting, not ending, a conversation.

Social media can inform us…

Social media can amplify important voices and issues…

Social media can be a tool for connection and solidarity…

Social media can be a space for mobilization…

Social media can be a space for deliberation and debate…

Social media can be a tool for showing us a diversity of views and perspectives…

Social media can be a model for democratically governed spaces…(More).

Technology and satellite companies open up a world of data

Curated on June 5, 2018August 3, 2018 by Stefaan Verhulst

Gabriel Popkin at Nature: “In the past few years, technology and satellite companies’ offerings to scientists have increased dramatically. Thousands of researchers now use high-resolution data from commercial satellites for their work. Thousands more use cloud-computing resources provided by big Internet companies to crunch data sets that would overwhelm most university computing clusters. Researchers use the new capabilities to track and visualize forest and coral-reef loss; monitor farm crops to boost yields; and predict glacier melt and disease outbreaks. Often, they are analysing much larger areas than has ever been possible — sometimes even encompassing the entire globe. Such studies are landing in leading journals and grabbing media attention.

Commercial data and cloud computing are not panaceas for all research questions. NASA and the European Space Agency carefully calibrate the spectral quality of their imagers and test them with particular types of scientific analysis in mind, whereas the aim of many commercial satellites is to take good-quality, high-resolution pictures for governments and private customers. And no company can compete with Landsat’s free, publicly available, 46-year archive of images of Earth’s surface. For commercial data, scientists must often request images of specific regions taken at specific times, and agree not to publish raw data. Some companies reserve cloud-computing assets for researchers with aligned interests such as artificial intelligence or geospatial-data analysis. And although companies publicly make some funding and other resources available for scientists, getting access to commercial data and resources often requires personal connections. Still, by choosing the right data sources and partners, scientists can explore new approaches to research problems.

Mapping poverty

Joshua Blumenstock, an information scientist at the University of California, Berkeley (UCB), is always on the hunt for data he can use to map wealth and poverty, especially in countries that do not conduct regular censuses. “If you’re trying to design policy or do anything to improve living conditions, you generally need data to figure out where to go, to figure out who to help, even to figure out if the things you’re doing are making a difference.”

In a 2015 study, he used records from mobile-phone companies to map Rwanda’s wealth distribution (J. Blumenstock et al. Science 350, 1073–1076; 2015). But to track wealth distribution worldwide, patching together data-sharing agreements with hundreds of these companies would have been impractical. Another potential information source — high-resolution commercial satellite imagery — could have cost him upwards of US$10,000 for data from just one country….

Use of commercial images can also be restricted. Scientists are free to share or publish most government data or data they have collected themselves. But they are typically limited to publishing only the results of studies of commercial data, and at most a limited number of illustrative images.

Many researchers are moving towards a hybrid approach, combining public and commercial data, and running analyses locally or in the cloud, depending on need. Weiss still uses his tried-and-tested ArcGIS software from Esri for studies of small regions, and jumps to Earth Engine for global analyses.

The new offerings herald a shift from an era when scientists had to spend much of their time gathering and preparing data to one in which they’re thinking about how to use them. “Data isn’t an issue any more,” says Roy. “The next generation is going to be about what kinds of questions are we going to be able to ask?”…(More)”.

Algorithm Observatory: Where anyone can study any social computing algorithm.

Curated on June 3, 2018August 3, 2018 by Stefaan Verhulst

About: “We know that social computing algorithms are used to categorize us, but the way they do so is not always transparent. To take just one example, ProPublica recently uncovered that Facebook allows housing advertisers to exclude users by race.

Even so, there are no simple and accessible resources for us, the public, to study algorithms empirically, and to engage critically with the technologies that are shaping our daily lives in such profound ways.

That is why we created Algorithm Observatory.

Part media literacy project and part citizen experiment, the goal of Algorithm Observatory is to provide a collaborative online lab for the study of social computing algorithms. The data collected through this site is analyzed to compare how a particular algorithm handles data differently depending on the characteristics of users.

Algorithm Observatory is a work in progress. This prototype only allows users to explore Facebook advertising algorithms, and the functionality is limited. We are currently looking for funding to realize the project’s full potential: to allow anyone to study any social computing algorithm….

Our future plans

This is a prototype, which only begins to showcase the things that Algorithm Observatory will be able to do in the future.

Eventually, the website will allow anyone to design an experiment involving a social computing algorithm. The platform will allow researchers to recruit volunteer participants, who will be able to contribute content to the site securely and anonymously. Researchers will then be able to conduct an analysis to compare how the algorithm handles users differently depending on individual characteristics. The results will be shared by publishing a report evaluating the social impact of the algorithm. All data and reports will become publicly available and open for comments and reviews. Researchers will be able to study any algorithm, because the site does not require direct access to the source code, but relies instead on empirical observation of the interaction between the algorithm and volunteer participants….(More)”.

How Citizens Can Hack EU Democracy

Curated on June 2, 2018August 3, 2018 by Stefaan Verhulst

Stephen Boucher at Carnegie Europe: “…To connect citizens with the EU’s decisionmaking center, European politicians will need to provide ways to effectively hack this complex system. These democratic hacks need to be visible and accessible, easily and immediately implementable, viable without requiring changes to existing European treaties, and capable of having a traceable impact on policy. Many such devices could be imagined around these principles. Here are three ideas to spur debate.

Hack 1: A Citizens’ Committee for the Future in the European Parliament

The European Parliament has proposed that twenty-seven of the seventy-three seats left vacant by Brexit should be redistributed among the remaining member states. According to one concept, the other forty-six unassigned seats could be used to recruit a contingent of ordinary citizens from around the EU to examine legislation from the long-term perspective of future generations. Such a “Committee for the Future” could be given the power to draft a response to a yearly report on the future produced by the president of the European Parliament, initiate debates on important political themes of their own choosing, make submissions on future-related issues to other committees, and be consulted by members of the European Parliament (MEPs) on longer-term matters.

MEPs could decide to use these forty-six vacant seats to invite this Committee for the Future to sit, at least on a trial basis, with yearly evaluations. This arrangement would have real benefits for EU politics, acting as an antidote to the union’s existential angst and helping the EU think systemically and for the longer term on matters such as artificial intelligence, biodiversity, climate concerns, demography, mobility, and energy.

Hack 2: An EU Participatory Budget

In 1989, the city of Porto Alegre, Brazil, decided to cede control of a share of its annual budget for citizens to decide upon. This practice, known as participatory budgets, has since spread globally. As of 2015, over 1,500 instances of participatory budgets have been implemented across five continents. These processes generally have had a positive impact, with people proving that they take public spending matters seriously.

To replicate these experiences at the European level, the complex realities of EU budgeting would require specific features. First, participative spending probably would need to be both local and related to wider EU priorities in order to ensure that citizens see its relevance and its wider European implications. Second, significant resources would need to be allocated to help citizens come up with and promote projects. For instance, the city of Paris has ensured that each suggested project that meets the eligibility requirements has a desk officer within its administration to liaise with the idea’s promoters. It dedicates significant resources to reach out to citizens, in particular in the poorer neighborhoods of Paris, both online and face-to-face. Similar efforts would need to be deployed across Europe. And third, in order to overcome institutional complexities, the European Parliament would need to work with citizens as part of its role in negotiating the budget with the European Council.

Hack 3: An EU Collective Intelligence Forum

Many ideas have been put forward to address popular dissatisfaction with representative democracy by developing new forums such as policy labs, consensus conferences, and stakeholder facilitation groups. Yet many citizens still feel disenchanted with representative democracy, including at the EU level, where they also strongly distrust lobby groups. They need to be involved more purposefully in policy discussions.

A yearly Deliberative Poll could be run on a matter of significance, ahead of key EU summits and possibly around the president of the commission’s State of the Union address. On the model of the first EU-wide Deliberative Poll, Tomorrow’s Europe, this event would bring together in Brussels a random sample of citizens from all twenty-seven EU member states, and enable them to discuss various social, economic, and foreign policy issues affecting the EU and its member states. This concept would have a number of advantages in terms of promoting democratic participation in EU affairs. By inviting a truly representative sample of citizens to deliberate on complex EU matters over a weekend, within the premises of the European Parliament, the European Parliament would be the focus of a high-profile event that would draw media attention. This would be especially beneficial if—unlike Tomorrow’s Europe—the poll was not held at arm’s length by EU policymakers, but with high-level national officials attending to witness good-quality deliberation remolding citizens’ views….(More)”.

Free Speech is a Triangle

Curated on May 30, 2018November 15, 2018 by admin

Essay by Jack Balkin: “The vision of free expression that characterized much of the twentieth century is inadequate to protect free expression today.

The twentieth century featured a dyadic or dualist model of speech regulation with two basic kinds of players: territorial governments on the one hand, and speakers on the other. The twenty-first century model is pluralist, with multiple players. It is easiest to think of it as a triangle. On one corner are nation states and the European Union. On the second corner are privately-owned Internet infrastructure companies, including social media companies, search engines, broadband providers, and electronic payment systems. On the third corner are many different kinds of speakers, legacy media, civil society organizations, hackers, and trolls.

Territorial goverments continue to regulate speakers and legacy media through traditional or “old-school” speech regulation. But nation states and the European Union also now employ “new-school” speech regulation that is aimed at Internet infrastructure owners and designed to get these private companies to surveil, censor, and regulate speakers for them. Finally, infrastructure companies like Facebook also regulate and govern speakers through techniques of private governance and surveillance.

The practical ability to speak in the digital world emerges from the struggle for power between these various forces, with old-school, new-school and private regulation directed at speakers, and both nation states and civil society organizations pressuring infrastructure owners to regulate speech.

If the characteristic feature of free speech regulation in our time is a triangle that combines new school speech regulation with private governance, then the best way to protect free speech values today is to combat and compensate for that triangle’s evolving logic of public and private regulation. The first goal is to prevent or ameliorate as much as possible collateral censorship and new forms of digital prior restraint. The second goal is to protect people from new methods of digital surveillance and manipulation—methods that emerged from the rise of large multinational companies that depend on data collection, surveillance, analysis, control, and distribution of personal data.

This essay describes how nation states should and should not regulate the digital infrastructure consistent with the values of freedom of speech and press; it emphasizes that different models of regulation are appropriate for different parts of the digital infrastructure. Some parts of the digital infrastructure are best regulated along the lines of common carriers or places of public accommodation. But governments should not impose First Amendment-style or common carriage obligations on social media and search engines. Rather, governments should require these companies to provide due process toward their end-users. Governments should also treat these companies as information fiduciaries who have duties of good faith and non-manipulation toward their end-users. Governments can implement all of these reforms—properly designed—consistent with constitutional guarantees of free speech and free press….(More)”.

AI trust and AI fears: A media debate that could divide society

Curated on May 20, 2018May 29, 2019 by admin

Article by Vyacheslav Polonski: “Unless you live under a rock, you probably have been inundated with recent news on machine learning and artificial intelligence (AI). With all the recent breakthroughs, it almost seems like AI can already predict the future. Police forces are using it to map when and where crime is likely to occur. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences.

Of course, many decisions in our lives require a good forecast, and AI agents are almost always better at forecasting than their human counterparts. Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions. Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if these experts are wrong.

If we want AI to really benefit people, we need to find a way to get people to trust it. To do that, we need to understand why people are so reluctant to trust AI in the first place….

Many people are also simply not familiar with many instances of AI actually working, because it often happens in the background. Instead, they are acutely aware of instances where AI goes terribly wrong:

A Google algorithm that classifies people of colour as gorillas.
A self-driving Uber that runs a red light in San Francisco.
An automated YouTube ad campaign that displays ads next to anti-semitic and homophobic videos.
An Amazon Alexa device that starts offering adult content to children.
A Pokémon Go algorithm that replicates and amplifies racial segregation.
A Microsoft chatbot that decides to become a white supremacist in less than a day.
A Tesla car operating in autopilot mode that resulted in a fatal accident.

These unfortunate examples have received a disproportionate amount of media attention, emphasising the message that humans cannot always rely on technology. In the end, it all goes back to the simple truth that machine learning is not foolproof, in part because the humans who design it aren’t….

Fortunately we already have some ideas about how to improve trust in AI — there’s light at the end of the tunnel.

Experience: One solution may be to provide more hands-on experiences with automation apps and other AI applications in everyday situations (like this robot that can get you a beer from the fridge). Thus, instead of presenting the Sony’s new robot dog Aibo as an exclusive product for the upper-class, we’d recommend making these kinds of innovations more accessible to the masses. Simply having previous experience with AI can significantly improve people’s attitudes towards the technology, as we found in our experimental study. And this is especially important for the general public that may not have a very sophisticated understanding of the technology. Similar evidence also suggests the more you use other technologies such as the Internet, the more you trust them.
Insight: Another solution may be to open the “black-box” of machine learning algorithms and be slightly more transparent about how they work. Companies such as Google, Airbnb and Twitter already release transparency reports on a regular basis. These reports provide information about government requests and surveillance disclosures. A similar practice for AI systems could help people have a better understanding of how algorithmic decisions are made. Therefore, providing people with a top-level understanding of machine learning systems could go a long way towards alleviating algorithmic aversion.
Control: Lastly, creating more of a collaborative decision-making process will help build trust and allow the AI to learn from human experience. In our work at Avantgarde Analytics, we have also found that involving people more in the AI decision-making process could improve trust and transparency. In a similar vein, a group of researchers at the University of Pennsylvania recently found that giving people control over algorithms can help create more trust in AI predictions. Volunteers in their study who were given the freedom to slightly modify an algorithm felt more satisfied with it, more likely to believe it was superior and more likely to use in in the future.

These guidelines (experience, insight and control) could help making AI systems more transparent and comprehensible to the individuals affected by their decisions….(More)”.

Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing

Curated on May 19, 2018November 15, 2018 by admin

Paper by Martin Mueller and Marcel Salath: “In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and increasingly potent hardware and software that enables us to work with these new big data streams.

At the same time, many challenging problems have been identified. First, there is often a mismatch between how rapidly online data can change, and how rapidly algorithms are updated, which means that there is limited reusability for algorithms trained on past data as their performance decreases over time. Second, much of the work is focusing on specific issues during a specific past period in time, even though public health institutions would need flexible tools to assess multiple evolving situations in real time. Third, most tools providing such capabilities are proprietary systems with little algorithmic or data transparency, and thus little buy-in from the global public health and research community.

Here, we introduce Crowdbreaks, an open platform which allows tracking of health trends by making use of continuous crowdsourced labelling of public social media content. The system is built in a way which automatizes the typical workflow from data collection, filtering, labelling and training of machine learning classifiers and therefore can greatly accelerate the research process in the public health domain. This work introduces the technical aspects of the platform and explores its future use cases…(More)”.