Report by the Center for Data Innovation: “From screening chemical compounds to optimizing clinical trials to improving post-market surveillance of drugs, the increased use of data and better analytical tools such as artificial intelligence (AI) hold the potential to transform drug development, leading to new treatments, improved patient outcomes, and lower costs. However, achieving the full promise of data-driven drug development will require the U.S. federal government to address a number of obstacles. This should be a priority for policymakers for two main reasons. First, enabling data-driven drug development will accelerate access to more effective and affordable treatments. Second, the competitiveness of the U.S. biopharmaceutical industry is at risk so long as these obstacles exist. As other nations, particularly China, pursue data-driven innovation, especially greater use of AI, foreign life sciences firms could become more competitive at drug development….(More)”.
Jacqueline Hicks at the Conversation: “There is a global standoff going on about who stores your data. At the close of June’s G20 summit in Japan, a number of developing countries refused to sign an international declaration on data flows – the so-called Osaka Track. Part of the reason why countries such as India, Indonesia and South Africa boycotted the declaration was because they had no opportunity to put their own interests about data into the document.
With 50 other signatories, the declaration still stands as a statement of future intent to negotiate further, but the boycott represents an ongoing struggle by some countries to assert their claim over the data generated by their own citizens.
Back in the dark ages of 2016, data was touted as the new oil. Although the metaphor was quickly debunked it’s still a helpful way to understand the global digital economy. Now, as international negotiations over data flows intensify, the oil comparison helps explain the economics of what’s called “data localisation” – the bid to keep citizens’ data within their own country.
Just as oil-producing nations pushed for oil refineries to add value to crude oil, so governments today want the world’s Big Tech companies to build data centres on their own soil. The cloud that powers much of the world’s tech industry is grounded in vast data centres located mainly around northern Europe and the US coasts. Yet, at the same time, US Big Tech companies are increasingly turning to markets in the global south for expansion as enormous numbers of young tech savvy populations come online….(More)”.
MIT News: “India is on a path with dual — and potentially conflicting — goals related to the use of citizen data.
To improve the efficiency their municipal services, many Indian cities have started enabling government-service requests, which involves collecting and sharing citizen data with government officials and, potentially, the public. But there’s also a national push to protect citizen privacy, potentially restricting data usage. Cities are now beginning to question how much citizen data, if any, they can use to track government operations.
In a new study, MIT researchers find that there is, in fact, a way for Indian cities to preserve citizen privacy while using their data to improve efficiency.
The researchers obtained and analyzed data from more than 380,000 government service requests by citizens across 112 cities in one Indian state for an entire year. They used the dataset to measure each city government’s efficiency based on how quickly they completed each service request. Based on field research in three of these cities, they also identified the citizen data that’s necessary, useful (but not critical), or unnecessary for improving efficiency when delivering the requested service.
In doing so, they identified “model” cities that performed very well in both categories, meaning they maximized privacy and efficiency. Cities worldwide could use similar methodologies to evaluate their own government services, the researchers say. …(More)”.
Report by Philip Howard and Samantha Bradshaw: “…The report explores the tools, capacities, strategies and resources employed by global ‘cyber troops’, typically government agencies and political parties, to influence public opinion in 70 countries.
Key findings include:
- Organized social media manipulation has more than doubled since 2017, with 70 countries using computational propaganda to manipulate public opinion.
- In 45 democracies, politicians and political parties have used computational propaganda tools by amassing fake followers or spreading manipulated media to garner voter support.
- In 26 authoritarian states, government entities have used computational propaganda as a tool of information control to suppress public opinion and press freedom, discredit criticism and oppositional voices, and drown out political dissent.
- Foreign influence operations, primarily over Facebook and Twitter, have been attributed to cyber troop activities in seven countries: China, India, Iran, Pakistan, Russia, Saudi Arabia and Venezuela.
- China has now emerged as a major player in the global disinformation order, using social media platforms to target international audiences with disinformation.
- 25 countries are working with private companies or strategic communications firms offering a computational propaganda as a service.
- Facebook remains the platform of choice for social media manipulation, with evidence of formally organised campaigns taking place in 56 countries….
The report explores the tools and techniques of computational propaganda, including the use of fake accounts – bots, humans, cyborgs and hacked accounts – to spread disinformation. The report finds:
- 87% of countries used human accounts
- 80% of countries used bot accounts
- 11% of countries used cyborg accounts
- 7% of countries used hacked or stolen accounts…(More)”.
Mary Hui at Quartz: “The “Be Water” nature of Hong Kong’s protests means that crowds move quickly and spread across the city. They might stage a protest in the central business district one weekend, then industrial neighborhoods and far-flung suburban towns the next. And a lot is happening at any one time at each protest. One of the key difficulties for protesters is to figure out what’s happening in the crowded, fast-changing, and often chaotic circumstances.
Citizen-led efforts to map protests in real-time are an attempt to address those challenges and answer some pressing questions for protesters and bystanders alike: Where should they go? Where have tear gas and water cannons been deployed? Where are police advancing, and are there armed thugs attacking civilians?
One of the most widely used real-time maps of the protests is HKMap.live, a volunteer-run and crowdsourced effort that officially launched in early August. It’s a dynamic map of Hong Kong that users can zoom in and out of, much like Google Maps. But in addition to detailed street and building names, this one features various emoji to communicate information at a glance: a dog for police, a worker in a yellow hardhat for protesters, a dinosaur for the police’s black-clad special tactical squad, a white speech-bubble for tear gas, two exclamation marks for danger.
Founded by a finance professional in his 20s and who only wished to be identified as Kuma, HKMap is an attempt to level the playing field between protesters and officers, he said in an interview over chat app Telegram. While earlier on in the protest movement people relied on text-based, on-the-ground live updates through public Telegram channels, Kuma found these to be too scattered to be effective, and hard to visualize unless someone knew the particular neighborhood inside out.
“The huge asymmetric information between protesters and officers led to multiple occasions of surround and capture,” said Kuma. Passersby and non-frontline protesters could also make use of the map, he said, to avoid tense conflict zones. After some of his friends were arrested in late July, he decided to build HKMap….(More)”.
By Michelle Winowatan, Andrew J. Zahuranec, Andrew Young, Stefaan Verhulst, Max Jun Kim
The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on the data universe.
Please share any additional, illustrative statistics on data, or other issues at the nexus of technology and governance, with us at email@example.com
- Percentage of the world’s population that uses the internet: 51.2% (3.9 billion people) – 2018
- Number of search processed worldwide by Google every year: at least 2 trillion – 2016
- Website traffic worldwide generated through mobile phones: 52.2% – 2018
- The total number of mobile subscriptions in the first quarter of 2019: 7.9 billion (addition of 44 million in quarter) – 2019
- Amount of mobile data traffic worldwide: nearly 30 billion GB – 2018
- Data category with highest traffic worldwide: video (60%) – 2018
- Global average of data traffic per smartphone per month: 5.6 GB – 2018
- Time between the creation of each new bitcoin block: 9.27 minutes – 2019
- Total hours of video streamed by Netflix users every minute: 97,222 – 2017
- Hours of YouTube watched per day: over 1 billion – 2018
- Number of tracks uploaded to Spotify every day: Over 20,000 – 2019
- Number of Spotify’s monthly active users: 232 million – 2019
- Spotify’s total subscribers: 108 million – 2019
- Spotify’s hours of content listened: 17 billion – 2019
- Total number of songs on Spotify’s catalog: over 30 million – 2019
- Apple Music’s total subscribers: 60 million – 2019
- Total number of songs on Apple Music’s catalog: 45 million – 2019
- Number of snaps shared by Snapchat users every day: Over 3.5 billion – 2017
- Number of tweets sent every day: 500 million – 2019
- Number of Instagram users: over 700 million – 2017
- Amount of data created by Facebook in a day: 4,000,000 GB – 2014
- Number of LinkedIn members: 645 million – 2019
- LinkedIn sign-up rate: 2 members per second – 2019
- Number of photos and videos shared on Instagram every day: 95 million – 2019
- Tinder dates per week: 1 million – 2019
- Total matches on Tinder: over 30 billion – 2019
- Most popular month on Tinder in the US: August – 2018
- Day: Monday – 2018
- Time of day: 9 PM EST – 2018
Calls and Messaging:
- Estimated robocalls made in the US: 47.8 billion – 2018
- Number of messages sent over WhatsApp each day: 65 billion – 2018
- Minutes of voice and video calls made on WhatsApp each day: 2 billion – 2018
- Top 3 most popular messaging apps worldwide: WhatsApp, Facebook Messenger, WeChat – 2019
- Worldwide email users: 2.943 billion – 2019
- Number of emails sent/received per day: 246.5 billion – 2019
- Number of packages shipped by Amazon in a year: 5 billion – 2017
- Total value of payments processed by Venmo in a year: USD 62 billion – 2019
- Based on an independent analysis of public transactions on Venmo in 2017:
- Based on a non-representative survey of 2,436 US consumers between the ages of 21 and 72 on P2P platforms:
- The average volume of transactions handled by Venmo: USD 64.2 billion – 2019
- The average volume of transactions handled by Zelle: USD 122.0 billion – 2019
- The average volume of transactions handled by PayPal: USD 141.8 billion – 2019
- Platform with the highest percent adoption among all consumers: PayPal (48%) – 2019
Internet of Things:
- Number of connected IoT devices worldwide: 8.3 billion – 2018
- Number of new devices connected to the Internet every second: 127 – 2017
- Number of wearable devices: 526 million – 2017
- Based on aggregated and anonymized data of Fitbit users from January 1, 2018 – 2018
- Total steps taken: 27 trillion – 2018
- Total hours slept: 12 billion – 2018
- Total active minutes: 119 billion – 2018
- Top 5 countries/territories with most steps: Hong Kong, Spain, Ireland, Sweden, Germany – 2018
- Top 5 countries that get the most sleep: Finland, New Zealand, Ireland, Belgium, Netherlands – 2018
- Top 5 US locales with the lowest resting heart rate: Bend, OR; Santa Barbara, Santa Maria, and San Luis Obispo, CA; Twin Falls, ID; Monterey-Salinas, CA; Juneau, AK – 2018
- Amount of data produced by an autonomous car in a one and a half hour of driving: – 4,000 GB
- Al-Heeti, Abrar. “WhatsApp: 65B Messages Sent Each Day, and More than 2B Minutes of Calls.” CNET, May 1, 2018. https://www.cnet.com/news/whatsapp-65-billion-messages-sent-each-day-and-more-than-2-billion-minutes-of-calls/.
- Bhuiyan, Johana. “Uber Powered Four Billion Rides in 2017. It Wants to Do More — and Cheaper — in 2018.” Vox, January 5, 2018. https://www.vox.com/2018/1/5/16854714/uber-four-billion-rides-coo-barney-harford-2018-cut-costs-customer-service.
- Blockchain Staff. “Bitcoin Currency Statistics.” Blockchain.com, August 2019. https://www.blockchain.com/stats.
- Carman, Ashley. “Amazon Shipped over 5 Billion Items Worldwide through Prime in 2017.” The Verge, January 2, 2018. https://www.theverge.com/2018/1/2/16841786/amazon-prime-2017-users-ship-five-billion.
- Cisco®. “Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2017–2022 White Paper.” Cisco, February 18, 2019. https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-738429.html.
- Clement, J. “Mobile Share of Website Visits Worldwide 2018.” Statistica, July 22, 2019. https://www.statista.com/statistics/241462/global-mobile-phone-website-traffic-share/.
- ———. “Most Popular Messaging Apps 2019.” Statistica, August 9, 2019. https://www.statista.com/statistics/258749/most-popular-global-mobile-messenger-apps/.
- Desjardins, Jeff. “How Much Data Is Generated Each Day?” World Economic Forum, April 17, 2019. https://www.weforum.org/agenda/2019/04/how-much-data-is-generated-each-day-cf4bddf29f/.
- Do Thi Duc, Hang. “PUBLIC BY DEFAULT – Venmo Stories of 2017.” Public By Default FYI, 2018. https://publicbydefault.fyi.
- Dwyer, Erin. “2017 on Netflix – A Year in Bingeing.” Netflix Media Center, December 11, 2017. https://media.netflix.com/en/press-releases/2017-on-netflix-a-year-in-bingeing.
- Fisher, Christine. “Apple Music Now Has 60 Million Paid Subscribers.” Engadget, June 27, 2019. https://www.engadget.com/2019/06/27/apple-music-60-million-paid-subscribers/.
- Instagram. “700 Million.” Instagram Press (blog), April 26, 2017. https://instagram-press.com/blog/2017/04/26/700-million/.
- Jonsson, Peter, Stephen Carson, Andres Torres, Per Lindberg, Kati Öhman, Athanasios Karapantelakis, Shamil Bajgin, et al. “Ericsson Mobility Report.” Stockholm, Sweden: Ericsson, 2019. https://www.ericsson.com/49d1d9/assets/local/mobility-report/documents/2019/ericsson-mobility-report-june-2019.pdf.
- Lasse Lueth, Knud. “State of the IoT 2018: Number of IoT Devices Now at 7B – Market Accelerating,” August 8, 2018. https://iot-analytics.com/state-of-the-iot-update-q1-q2-2018-number-of-iot-devices-now-7b/.
- Levenson, Josh, and Parker Hall. “Apple Music vs. Spotify.” Digital Trends, August 7, 2019. https://www.digitaltrends.com/music/apple-music-vs-spotify/.
- LinkedIn. “About Us.” LinkedIn, 2019. https://news.linkedin.com/about-us.
- Patel, Mark, Jason Shangkuan, and Christopher Thomas. “What’s New with the Internet of Things? | McKinsey.” McKinsey & Company, May 2017. https://www.mckinsey.com/industries/semiconductors/our-insights/whats-new-with-the-internet-of-things.
- Trefis Research Team. “Estimating Lyft’s Valuation.” Trefis, 2019. https://dashboards.trefis.com/no-login-required/zrRBRShU/Estimating-Lyft’s-Valuation.
- Rooney, Kate. “PayPal’s Venmo Had a Break-out Quarter with Payments Surging 80%.” CNBC, January 31, 2019. https://www.cnbc.com/2019/01/31/venmo-had-a-break-out-quarter-but-wont-make-money-for-paypal-until-at-mid-2019–.html.
- Shevlin, Ron. “Fintech Adoption in the US: The Opportunity for Banks and Credit Unions.” Scottsdale, AZ: Cornerstone Advisors, 2018. https://www.q2ebanking.com/wp-content/uploads/2019/01/20181107-Q2-Fintech-Adoption-Index.pdf.
- Smith. “Fitbit’s Fittest: The Countries (And Cities) That Stepped It Up and Slept More In 2018.” Fitbit Blog, January 12, 2019. https://blog.fitbit.com/fitbit-year-in-review-2018/.
- Snap, Inc. “Snap Inc. Reports Fourth Quarter and Full Year 2017 Results.” Snap, February 6, 2018. https://investor.snap.com/~/media/Files/S/Snap-IR/reports-and-presentations/q4-17-earnings-slides.pdf.
- Spotify. “Music – FAQ.” Spotify, 2019. https://artists.spotify.com/faq/music.
- ———. “Spotify Reports Second Quarter 2019 Earnings.” Spotify, July 31, 2019. https://newsroom.spotify.com/2019-07-31/spotify-reports-second-quarter-2019-earnings/.
- Sullivan, Danny. “Google Now Handles at Least 2 Trillion Searches per Year.” Search Engine Land, May 24, 2016. https://searchengineland.com/google-now-handles-2-999-trillion-searches-per-year-250247.
- The Radicati Group, Inc. “Email Statistics Report, 2015-2019: Executive Summary.” The Radicati Group, Inc, March 2015. https://www.radicati.com/wp/wp-content/uploads/2015/02/Email-Statistics-Report-2015-2019-Executive-Summary.pdf.
- Tinder Press Team. “Tinder Press and Brand Assets.” Tinder, 2019. https://tinder.com.
- Tinder Staff. “This Is What Happened On Tinder In 2018.” Swipe Life, December 5, 2018. https://swipelife.tinder.com/post/tinder-2018.
- Twitter, Inc. “Twitter for Business.” Twitter, 2019. https://business.twitter.com/en.html.
- Wiener, Janet, and Nathan Bronson. “Facebook’s Top Open Data Problems.” Facebook Research (blog), October 22, 2014. https://research.fb.com/blog/2014/10/facebook-s-top-open-data-problems/.
- Winter, Kathy. “For Self-Driving Cars, There’s Big Meaning Behind One Big Number: 4 Terabytes.” Intel Newsroom, April 14, 2017. https://newsroom.intel.com/editorials/self-driving-cars-big-meaning-behind-one-number-4-terabytes/.
- YouMail. “YouMail Robocall Index: July 2019 Nationwide Robocall Data.” Robocall Index, 2019. https://robocallindex.com/.
- YouTube Press Team. “Press – YouTube.” YouTube, August 2019. https://www.youtube.com/yt/about/press/.
- Zavazava, Cosmas, Rati Skhirtladze, Vanessa Gray, Esperanza Magpantay, Daniela Pokorna, Martin Schaaper, and Ivan Vallejo. “Measuring the Information Society Report 2018 – Volume 1.” Geneva, Switzerland: International Telecommunication Union, 2018. https://www.itu.int/en/ITU-D/Statistics/Documents/publications/misr2018/MISR-2018-Vol-1-E.pdf.
Essay by Richard A. Clarke And Rob Knake in Foreign Affairs: “The early days of the Internet inspired a lofty dream: authoritarian states, faced with the prospect of either connecting to a new system of global communication or being left out of it, would choose to connect. According to this line of utopian thinking, once those countries connected, the flow of new information and ideas from the outside world would inexorably pull them toward economic openness and political liberalization. In reality, something quite different has happened. Instead of spreading democratic values and liberal ideals, the Internet has become the backbone of authoritarian surveillance states all over the world. Regimes in China, Russia, and elsewhere have used the Internet’s infrastructure to build their own national networks. At the same time, they have installed technical and legal barriers to prevent their citizens from reaching the wider Internet and to limit Western companies from entering their digital markets.
But despite handwringing in Washington and Brussels about authoritarian schemes to split the Internet, the last thing Beijing and Moscow want is to find themselves relegated to their own networks and cut off from the global Internet. After all, they need access to the Internet to steal intellectual property, spread propaganda, interfere with elections in other countries, and threaten critical infrastructure in rival countries. China and Russia would ideally like to re-create the Internet in their own images and force the world to play by their repressive rules. But they haven’t been able to do that—so instead they have ramped up their efforts to tightly control outside access to their markets, limit their citizens’ ability to reach the wider Internet, and exploit the vulnerability that comes with the digital freedom and openness enjoyed in the West.
The United States and its allies and partners should stop worrying about the risk of authoritarians splitting the Internet. Instead, they should split it themselves, by creating a digital bloc within which data, services, and products can flow freely…(More)”.
Article by Priceonomics Data Studio: “For all the talk of how data is the new oil and the most valuable resource of any enterprise, there is a deep dark secret companies are reluctant to share — most of the data collected by businesses simply goes unused.
This unknown and unused data, known as dark data comprises more than half the data collected by companies. Given that some estimates indicate that 7.5 septillion (7,700,000,000,000,000,000,000) gigabytes of data are generated every single day, not using most of it is a considerable issue.
In this article, we’ll look at this dark data. Just how much of it is created by companies, what are the reasons this data isn’t being analyzed, and what are the costs and implications of companies not using the majority of the data they collect.
Before diving into the analysis, it’s worth spending a moment clarifying what we mean by the term “dark data.” Gartner defines dark data as:
“The information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).
To learn more about this phenomenon, Splunk commissioned a global survey of 1,300+ business leaders to better understand how much data they collect, and how much is dark. Respondents were from IT and business roles, and were located in Australia, China, France, Germany, Japan, the United States, and the United Kingdom. across various industries. For the report, Splunk defines dark data as: “all the unknown and untapped data across an organization, generated by systems, devices and interactions.”
While the costs of storing data has decreased overtime, the cost of saving septillions of gigabytes of wasted data is still significant. What’s more, during this time the strategic importance of data has increased as companies have found more and more uses for it. Given the cost of storage and the value of data, why does so much of it go unused?
The following chart shows the reasons why dark data isn’t currently being harnessed:
By a large margin, the number one reason given for not using dark data is that companies lack a tool to capture or analyze the data. Companies accumulate data from server logs, GPS networks, security tools, call records, web traffic and more. Companies track everything from digital transactions to the temperature of their server rooms to the contents of retail shelves. Most of this data lies in separate systems, is unstructured, and cannot be connected or analyzed.
Second, the data captured just isn’t good enough. You might have important customer information about a transaction, but it’s missing location or other important metadata because that information sits somewhere else or was never captured in useable format.
Additionally, dark data exists because there is simply too much data out there and a lot of is unstructured. The larger the dataset (or the less structured it is), the more sophisticated the tool required for analysis. Additionally, these kinds of datasets often time require analysis by individuals with significant data science expertise who are often is short supply.
The implications of the prevalence are vast. As a result of the data deluge, companies often don’t know where all the sensitive data is stored and can’t be confident they are complying with consumer data protection measures like GDPR. …(More)”.
Book by Nick Couldry: “We are told that progress requires human beings to be connected, and that science, medicine and much else that is good demands the kind massive data collection only possible if every thing and person are continuously connected.
But connection, and the continuous surveillance that connection makes possible, usher in an era of neocolonial appropriation. In this new era, social life becomes a direct input to capitalist production, and data – the data collected and processed when we are connected – is the means for this transformation. Hence the need to start counting the costs of connection.
Capturing and processing social data is today handled by an emerging social quantification sector. We are familiar with its leading players, from Acxiom to Equifax, from Facebook to Uber. Together, they ensure the regular and seemingly natural conversion of daily life into a stream of data that can be appropriated for value. This stream is extracted from sensors embedded in bodies and objects, and from the traces left by human interaction online. The result is a new social order based on continuous tracking, and offering unprecedented new opportunities for social discrimination and behavioral influence. This order has disturbing consequences for freedom, justice and power — indeed, for the quality of human life.
The true violence of this order is best understood through the history of colonialism. But because we assume that colonialism has been replaced by advanced capitalism, we often miss the connection. The concept of data colonialism can thus be used to trace continuities from colonialism’s historic appropriation of territories and material resources to the datafication of everyday life today. While the modes, intensities, scales and contexts of dispossession have changed, the underlying function remains the same: to acquire resources from which economic value can be extracted.
In data colonialism, data is appropriated through a new type of social relation: data relations. We are living through a time when the organization of capital and the configurations of power are changing dramatically because of this contemporary form of social relation. Data colonialism justifies what it does as an advance in scientific knowledge, personalized marketing, or rational management, just as historic colonialism claimed a civilizing mission. Data colonialism is global, dominated by powerful forces in East and West, in the USA and China. The result is a world where, wherever we are connected, we are colonized by data.
Where is data colonialism heading in the long term? Just as historical colonialism paved the way for industrial capitalism, data colonialism is paving the way for a new stage of capitalism whose outlines we only partly see: the capitalization of life without limit. There will be no part of human life, no layer of experience, that is not extractable for economic value. Human life will be there for mining by corporations without reserve as governments look on appreciatively. This process of capitalization will be the foundation for a highly unequal new social arrangement, a social order that is deeply incompatible with human freedom and autonomy.
But resistance is still possible, drawing on past and present decolonial struggles, as well as the on the best of the humanities, philosophy, political economy, information and social science. The goal is to name what is happening and imagine better ways of living together without the exploitation on which today’s models of ‘connection’ are founded….(More)”
Book edited by Masamichi Sasaki: “… deals with conceptual, theoretical and social interaction analyses, historical data on societies, national surveys or cross-national comparative studies, and methodological issues related to trust. The authors are from a variety of disciplines: psychology, sociology, political science, organizational studies, history, and philosophy, and from Britain, the United States, the Czech Republic, the Netherlands, Australia, Germany, and Japan. They bring their vast knowledge from different historical and cultural backgrounds to illuminate contemporary issues of trust and distrust. The socio-cultural perspective of trust is important and increasingly acknowledged as central to trust research. Accordingly, future directions for comparative trust research are also discussed….(More)”.