Technology is threatening our democracy. How do we save it?


MIT Technology Review: “Our newest issue is live today, in which we dive into the many ways that technology is changing politics.

A major shift: In 2013 we emblazoned our cover with the words, “Big Data Will Save Politics.” When we chose that headline, Barack Obama had just won reelection with the help of a crack team of data scientists. The Arab Spring had already cooled into an Arab Winter, but the social-media platforms that had powered the uprisings were still basking in the afterglow. As our editor in chief Gideon Lichfield writes, today, with Cambridge Analytica, fake news, election hacking, and the shrill cacophony that dominates social media, technology feels as likely to destroy politics as to save it.

The political impact: From striking data visualizations that take a close look at the famed “filter bubble” effect that’s blamed for political polarization to an examination of how big data is disrupting the cozy world of political lobbying, we’re analyzing how emerging technologies are shaping the political landscape, eroding trust, and, possibly, becoming a part of the solution….(More)”.

Odd Numbers: Algorithms alone can’t meaningfully hold other algorithms accountable


Frank Pasquale at Real Life Magazine: “Algorithms increasingly govern our social world, transforming data into scores or rankings that decide who gets credit, jobs, dates, policing, and much more. The field of “algorithmic accountability” has arisen to highlight the problems with such methods of classifying people, and it has great promise: Cutting-edge work in critical algorithm studies applies social theory to current events; law and policy experts seem to publish new articles daily on how artificial intelligence shapes our lives, and a growing community of researchers has developed a field known as “Fairness, Accuracy, and Transparency in Machine Learning.”

The social scientists, attorneys, and computer scientists promoting algorithmic accountability aspire to advance knowledge and promote justice. But what should such “accountability” more specifically consist of? Who will define it? At a two-day, interdisciplinary roundtable on AI ethics I recently attended, such questions featured prominently, and humanists, policy experts, and lawyers engaged in a free-wheeling discussion about topics ranging from robot arms races to computationally planned economies. But at the end of the event, an emissary from a group funded by Elon Musk and Peter Thiel among others pronounced our work useless. “You have no common methodology,” he informed us (apparently unaware that that’s the point of an interdisciplinary meeting). “We have a great deal of money to fund real research on AI ethics and policy”— which he thought of as dry, economistic modeling of competition and cooperation via technology — “but this is not the right group.” He then gratuitously lashed out at academics in attendance as “rent seekers,” largely because we had the temerity to advance distinctive disciplinary perspectives rather than fall in line with his research agenda.

Most corporate contacts and philanthrocapitalists are more polite, but their sense of what is realistic and what is utopian, what is worth studying and what is mere ideology, is strongly shaping algorithmic accountability research in both social science and computer science. This influence in the realm of ideas has powerful effects beyond it. Energy that could be put into better public transit systems is instead diverted to perfect the coding of self-driving cars. Anti-surveillance activism transmogrifies into proposals to improve facial recognition systems to better recognize all faces. To help payday-loan seekers, developers might design data-segmentation protocols to show them what personal information they should reveal to get a lower interest rate. But the idea that such self-monitoring and data curation can be a trap, disciplining the user in ever finer-grained ways, remains less explored. Trying to make these games fairer, the research elides the possibility of rejecting them altogether….(More)”.

Searching for the Smart City’s Democratic Future


Article by Bianca Wylie at the Center for International Governance Innovation: “There is a striking blue building on Toronto’s eastern waterfront. Wrapped top to bottom in bright, beautiful artwork by Montreal illustrator Cecile Gariepy, the building — a former fish-processing plant — stands out alongside the neighbouring parking lots and a congested highway. It’s been given a second life as an office for Sidewalk Labs — a sister company to Google that is proposing a smart city development in Toronto. Perhaps ironically, the office is like the smart city itself: something old repackaged to be light, fresh and novel.

“Our mission is really to use technology to redefine urban life in the twenty-first century.”

Dan Doctoroff, CEO of Sidewalk Labs, shared this mission in an interview with Freakonomics Radio. The phrase is a variant of the marketing language used by the smart city industry at large. Put more simply, the term “smart city” is usually used to describe the use of technology and data in cities.

No matter the words chosen to describe it, the smart city model has a flaw at its core: corporations are seeking to exert influence on urban spaces and democratic governance. And because most governments don’t have the policy in place to regulate smart city development — in particular, projects driven by the fast-paced technology sector — this presents a growing global governance concern.

This is where the story usually descends into warnings of smart city dystopia or failure. Loads of recent articles have detailed the science fiction-style city-of-the-future and speculated about the perils of mass data collection, and for good reason — these are important concepts that warrant discussion. It’s time, however, to push past dystopian narratives and explore solutions for the challenges that smart cities present in Toronto and globally…(More)”.

Data-Driven Law: Data Analytics and the New Legal Services


Book by Edward J. Walters: “For increasingly data-savvy clients, lawyers can no longer give “it depends” answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions.

Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as:

  • Mining legal data
  • Computational law
  • Uncovering bias through the use of Big Data
  • Quantifying the quality of legal services
  • Data mining and decision-making
  • Contract analytics and contract standards

In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable….(More)”.

Data Publics: Urban Protest, Analytics and the Courts


Article by Anthony McCosker and Timothy Graham in MC Journal: “There are many examples globally of the use of social media to engage publics in battles over urban development or similar issues (e.g. Fredericks and Foth). Some have asked how social media might be better used by neighborhood organisations to mobilise protest and save historic buildings, cultural landmarks or urban sites (Johnson and Halegoua). And we can only note here the wealth of research literature on social movements, protest and social media. To emphasise Gerbaudo’s point, drawing on Mattoni, we “need to account for how exactly the use of these media reshapes the ‘repertoire of communication’ of contemporary movements and affects the experience of participants” (2). For us, this also means better understanding the role that social data plays in both aiding and reshaping urban protest or arming third sector groups with evidence useful in social institutions such as the courts.

New modes of digital engagement enable forms of distributed digital citizenship, which Meikle sees as the creative political relationships that form through exercising rights and responsibilities. Associated with these practices is the transition from sanctioned, simple discursive forms of social protest in petitions, to new indicators of social engagement in more nuanced social media data and the more interactive forms of online petition platforms like change.org or GetUp (Halpin et al.). These technical forms code publics in specific ways that have implications for contemporary protest action. That is, they provide the operational systems and instructions that shape social actions and relationships for protest purposes (McCosker and Milne).

All protest and social movements are underwritten by explicit or implicit concepts of participatory publics as these are shaped, enhanced, or threatened by communication technologies. But participatory protest publics are uneven, and as Kelty asks: “What about all the people who are neither protesters nor Twitter users? In the broadest possible sense this ‘General Public’ cannot be said to exist as an actual entity, but only as a kind of virtual entity” (27). Kelty is pointing to the porous boundary between a general public and an organised public, or formal enterprise, as a reminder that we cannot take for granted representations of a public, or the public as a given, in relation to Like or follower data for instance.

If carefully gauged, the concept of data publics can be useful. To start with, the notions of publics and publicness are notoriously slippery. Baym and boyd explore the differences between these two terms, and the way social media reconfigures what “public” is. Does a Comment or a Like on a Facebook Page connect an individual sufficiently to an issues-public? As far back as the 1930s, John Dewey was seeking a pragmatic approach to similar questions regarding human association and the pluralistic space of “the public”. For Dewey, “the machine age has so enormously expanded, multiplied, intensified and complicated the scope of the indirect consequences [of human association] that the resultant public cannot identify itself” (157). To what extent, then, can we use data to constitute a public in relation to social protest in the age of data analytics?

There are numerous well formulated approaches to studying publics in relation to social media and social networks. Social network analysis (SNA) determines publics, or communities, through links, ties and clustering, by measuring and mapping those connections and to an extent assuming that they constitute some form of sociality. Networked publics (Ito, 6) are understood as an outcome of social media platforms and practices in the use of new digital media authoring and distribution tools or platforms and the particular actions, relationships or modes of communication they afford, to use James Gibson’s sense of that term. “Publics can be reactors, (re)makers and (re)distributors, engaging in shared culture and knowledge through discourse and social exchange as well as through acts of media reception” (Ito 6). Hashtags, for example, facilitate connectivity and visibility and aid in the formation and “coordination of ad hoc issue publics” (Bruns and Burgess 3). Gray et al., following Ruppert, argue that “data publics are constituted by dynamic, heterogeneous arrangements of actors mobilised around data infrastructures, sometimes figuring as part of them, sometimes emerging as their effect”. The individuals of data publics are neither subjugated by the logics and metrics of digital platforms and data structures, nor simply sovereign agents empowered by the expressive potential of aggregated data (Gray et al.).

Data publics are more than just aggregates of individual data points or connections. They are inherently unstable, dynamic (despite static analysis and visualisations), or vibrant, and ephemeral. We emphasise three key elements of active data publics. First, to be more than an aggregate of individual items, a data public needs to be consequential (in Dewey’s sense of issues or problem-oriented). Second, sufficient connection is visible over time. Third, affective or emotional activity is apparent in relation to events that lend coherence to the public and its prevailing sentiment. To these, we add critical attention to the affordising processes – or the deliberate and incidental effects of datafication and analysis, in the capacities for data collection and processing in order to produce particular analytical outcomes, and the data literacies these require. We return to the latter after elaborating on the Save the Palace case….(More)”.

Countries Can Learn from France’s Plan for Public Interest Data and AI


Nick Wallace at the Center for Data Innovation: “French President Emmanuel Macron recently endorsed a national AI strategy that includes plans for the French state to make public and private sector datasets available for reuse by others in applications of artificial intelligence (AI) that serve the public interest, such as for healthcare or environmental protection. Although this strategy fails to set out how the French government should promote widespread use of AI throughout the economy, it will nevertheless give a boost to AI in some areas, particularly public services. Furthermore, the plan for promoting the wider reuse of datasets, particularly in areas where the government already calls most of the shots, is a practical idea that other countries should consider as they develop their own comprehensive AI strategies.

The French strategy, drafted by mathematician and Member of Parliament Cédric Villani, calls for legislation to mandate repurposing both public and private sector data, including personal data, to enable public-interest uses of AI by government or others, depending on the sensitivity of the data. For example, public health services could use data generated by Internet of Things (IoT) devices to help doctors better treat and diagnose patients. Researchers could use data captured by motorway CCTV to train driverless cars. Energy distributors could manage peaks and troughs in demand using data from smart meters.

Repurposed data held by private companies could be made publicly available, shared with other companies, or processed securely by the public sector, depending on the extent to which sharing the data presents privacy risks or undermines competition. The report suggests that the government would not require companies to share data publicly when doing so would impact legitimate business interests, nor would it require that any personal data be made public. Instead, Dr. Villani argues that, if wider data sharing would do unreasonable damage to a company’s commercial interests, it may be appropriate to only give public authorities access to the data. But where the stakes are lower, companies could be required to share the data more widely, to maximize reuse. Villani rightly argues that it is virtually impossible to come up with generalizable rules for how data should be shared that would work across all sectors. Instead, he argues for a sector-specific approach to determining how and when data should be shared.

After making the case for state-mandated repurposing of data, the report goes on to highlight four key sectors as priorities: health, transport, the environment, and defense. Since these all have clear implications for the public interest, France can create national laws authorizing extensive repurposing of personal data without violating the General Data Protection Regulation (GDPR) which allows national laws that permit the repurposing of personal data where it serves the public interest. The French strategy is the first clear effort by an EU member state to proactively use this clause in aid of national efforts to bolster AI….(More)”.

To the smart city and beyond? Developing a typology of smart urban innovation


Maja Nilssen in Technological Forecasting and Social Change: “The smart city is an increasingly popular topic in urban development, arousing both excitement and skepticism. However, despite increasing enthusiasm regarding the smartness of cities, the concept is still regarded as somewhat evasive. Encouraged by the multifaceted character of the concept, this article examines how we can categorize the different dimensions often included in the smart city concept, and how these dimensions are coupled to innovation. Furthermore, the article examines the implications of the different understandings of the smart city concept for cities’ abilities to be innovative.

Building on existing scholarly contributions on the smartness of cities and innovation literature, the article develops a typology of smart city initiatives based on the extent and types of innovations they involve. The typology is structured as a smart city continuum, comprising four dimensions of innovation: (1) technological, (2) organizational, (3) collaborative, (4) experimental.

The smart city continuum is then utilized to analyze empirical data from a Norwegian urban development project triggered by a critical juncture. The empirical data shows that the case holds elements of different dimensions of the continuum, supporting the need for a typology of smart cities as multifaceted urban innovation. The continuum can be used as an analytical model for different types of smart city initiatives, and thus shed light on what types of innovation are central in the smart city. Consequently, the article offers useful insights for both practitioners and scholars interested in smart city initiatives….(More)”

How Taiwan’s online democracy may show future of humans and machines


Shuyang Lin at the Sydney Morning Herald: “Taiwanese citizens have spent the past 30 years prototyping future democracy since the lift of martial law in 1987. Public participation in Taiwan has been developed in several formats, from face-to-face to deliberation over the internet. This trajectory coincides with the advancement of technology, and as new tools arrived, democracy evolved.

The launch of vTaiwan (v for virtual, vote, voice and verb), an experiment that prototypes an open consultation process for the civil society, showed that by using technology creatively humanity can facilitate deep and fair conversations, form collective consensus, and deliver solutions we can all live with.

It is a prototype that helps us envision what future democracy could look like….

Decision-making is not an easy task, especially when it has to do with a larger group of people. Group decision-making could take several protocols, such as mandate, to decide and take questions; advise, to listen before decisions; consent, to decide if no one objects; and consensus, to decide if everyone agrees. So there is a pressing need for us to be able to collaborate together in a large scale decision-making process to update outdated standards and regulations.

The future of human knowledge is on the web. Technology can help us to learn, communicate, and make better decisions faster with larger scale. The internet could be the facilitation and AI could be the catalyst. It is extremely important to be aware that decision-making is not a one-off interaction. The most important direction of decision-making technology development is to have it allow humans to be engaged in the process anytime and also have an invitation to request and submit changes.

Humans have started working with computers, and we will continue to work with them. They will help us in the decision-making process and some will even make decisions for us; the actors in collaboration don’t necessarily need to be just humans. While it is up to us to decide what and when to opt in or opt out, we should work together with computers in a transparent, collaborative and inclusive space.

Where shall we go as a society? What do we want from technology? As Audrey Tang,  Digital Minister without Portfolio of Taiwan, puts it: “Deliberation — listening to each other deeply, thinking together and working out something that we can all live with — is magical.”…(More)”.

China’s Aggressive Surveillance Technology Will Spread Beyond Its Borders


Already there are reports that Zimbabwe, for example, is turning to Chinese firms to implement nationwide facial-recognition and surveillance programs, wrapped into China’s infrastructure investments and a larger set of security agreements as well, including for policing online communication. The acquisition of black African faces will help China’s tech sector improve its overall data set.

Malaysia, too, announced new partnerships this spring with China to equip police with wearable facial-recognition cameras. There are quiet reports of Arab Gulf countries turning to China not just for the drone technologies America has denied but also for the authoritarian suite of surveillance, recognition, and data tools perfected in China’s provinces. In a recent article on Egypt’s military-led efforts to build a new capital city beyond Cairo’s chaos and revolutionary squares, a retired general acting as project spokesman declared, “a smart city means a safe city, with cameras and sensors everywhere. There will be a command center to control the entire city.” Who is financing construction? China.

While many governments are making attempts to secure this information, there have been several alarming stories of data leaks. Moreover, these national identifiers create an unprecedented opportunity for state surveillance at scale. What about collecting biometric information in nondemocratic regimes? In 2016, the personal details of nearly 50 million people in Turkey were leaked….

China and other determined authoritarian states may prove undeterrable in their zeal to adopt repressive technologies. A more realistic goal, as Georgetown University scholar Nicholas Wright has argued, is to sway countries on the fence by pointing out the reputational costs of repression and supporting those who are advocating for civil liberties in this domain within their own countries. Democracy promoters (which we hope will one day again include the White House) will also want to recognize the coming changes to the authoritarian public sphere. They can start now in helping vulnerable populations and civil society to gain greater technological literacy to advocate for their rights in new domains. It is not too early for governments and civil society groups alike to study what technological and tactical countermeasures exist to circumvent and disrupt new authoritarian tools.

Seven years ago, techno-optimists expressed hope that a wave of new digital tools for social networking and self-expression could help young people in the Middle East and elsewhere to find their voices. Today, a new wave of Chinese-led technological advances threatens to blossom into what we consider an “Arab spring in reverse”—in which the next digital wave shifts the pendulum back, enabling state domination and repression at a staggering scale and algorithmic effectiveness.

Americans are absolutely right to be urgently focused on countering Russian weaponized hacking and leaking as its primary beneficiary sits in the Oval Office. But we also need to be more proactive in countering the tools of algorithmic authoritarianism that will shape the worldwide future of individual freedom….(More)”.

Humans are a post-truth species


Yuval Noah Harari at the Guardian: “….A cursory look at history reveals that propaganda and disinformation are nothing new, and even the habit of denying entire nations and creating fake countries has a long pedigree. In 1931 the Japanese army staged mock attacks on itself to justify its invasion of China, and then created the fake country of Manchukuo to legitimise its conquests. China itself has long denied that Tibet ever existed as an independent country. British settlement in Australia was justified by the legal doctrine of terra nullius (“nobody’s land”), which effectively erased 50,000 years of Aboriginal history. In the early 20th century, a favourite Zionist slogan spoke of the return of “a people without a land [the Jews] to a land without a people [Palestine]”. The existence of the local Arab population was conveniently ignored.

In 1969 Israeli prime minister Golda Meir famously said that there is no Palestinian people and never was. Such views are very common in Israel even today, despite decades of armed conflicts against something that doesn’t exist. For example, in February 2016 MP Anat Berko gave a speech in the Israeli parliament in which she doubted the reality and history of the Palestinian people. Her proof? The letter “p” does not even exist in Arabic, so how can there be a Palestinian people? (In Arabic, “F” stands for “P”, and the Arabic name for Palestine is Falastin.)

In fact, humans have always lived in the age of post-truth. Homo sapiens is a post-truth species, whose power depends on creating and believing fictions. Ever since the stone age, self-reinforcing myths have served to unite human collectives. Indeed, Homo sapiensconquered this planet thanks above all to the unique human ability to create and spread fictions. We are the only mammals that can cooperate with numerous strangers because only we can invent fictional stories, spread them around, and convince millions of others to believe in them. As long as everybody believes in the same fictions, we all obey the same laws, and can thereby cooperate effectively.

So if you blame Facebook, Trump or Putin for ushering in a new and frightening era of post-truth, remind yourself that centuries ago millions of Christians locked themselves inside a self-reinforcing mythological bubble, never daring to question the factual veracity of the Bible, while millions of Muslims put their unquestioning faith in the Qur’an. For millennia, much of what passed for “news” and “facts” in human social networks were stories about miracles, angels, demons and witches, with bold reporters giving live coverage straight from the deepest pits of the underworld. We have zero scientific evidence that Eve was tempted by the serpent, that the souls of all infidels burn in hell after they die, or that the creator of the universe doesn’t like it when a Brahmin marries an Untouchable – yet billions of people have believed in these stories for thousands of years. Some fake news lasts for ever.

I am aware that many people might be upset by my equating religion with fake news, but that’s exactly the point. When a thousand people believe some made-up story for one month, that’s fake news. When a billion people believe it for a thousand years, that’s a religion, and we are admonished not to call it fake news in order not to hurt the feelings of the faithful (or incur their wrath). Note, however, that I am not denying the effectiveness or potential benevolence of religion. Just the opposite. For better or worse, fiction is among the most effective tools in humanity’s toolkit. By bringing people together, religious creeds make large-scale human cooperation possible. They inspire people to build hospitals, schools and bridges in addition to armies and prisons. Adam and Eve never existed, but Chartres Cathedral is still beautiful. Much of the Bible may be fictional, but it can still bring joy to billions and encourage humans to be compassionate, courageous and creative – just like other great works of fiction, such as Don QuixoteWar and Peace and Harry Potter….(More)”.