Paper by David Watson and Luciano Floridi: “Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research….(More)”
Best Government Emerging Technologies
Report released at the World Government Summit (Dubai): “… the “Best Government Emerging Technologies” recognises governments that are experimenting with emerging technologies to provide government services more e ciently, e ectively and have proven results showing how they have created greater public value and transformed people›s lives.
For this purpose, the Prime Minister’s Office has joined forces with Indra to analyse and identify 29 Emerging Technologies, grouped in 9 categories that include technologies such as Artificial Intelligence, Blockchain, Cloud Computing, Robotics & Space, Smart Platforms, amongst other.
Wherever possible, case studies have been analysed as example of the use of the technology in public bodies and government, taking into account that some of these technologies may not have been implemented yet in the public sector and therefore have not a ected the lives of citizens. e analysis comprises 73 international case studies from 32 di erent countries.
is document represents an executive summary of the analysis ndings, incorporating a brief description of the main Emerging Technologies where the selected cutting-edge digital technologies are introduced, followed by a number of examples of international case studies in which governments and public bodies have implemented these technologies….
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The chaos of South Africa’s taxi system is being tackled with open data
Lynsey Chutel at Quartz: “On any given day in South Africa’s cities the daily commute can be chaotic and unpredictable. A new open source data platform hopes to bring some order to that—or at least help others get it right.
Contributing to that chaos is a formal public transportation system that is inadequate for a growing urban population and an informal transportation network that whizzes through the streets unregulated. Where Is My Transport has done something unique by finally bringing these two systems together on one map.
Where Is My Transport has mapped Cape Town’s transport systems to create an integrated system, incorporating train, bus and minibus taxi routes. This last one is especially difficult, because the thousands of minibuses that ferry most South Africans are notoriously difficult to pin down.
Minibus taxis seat about 15 people and turn any corner into a bus stop, often halting traffic. They travel within neighborhoods and across the country and are the most affordable means of transport for the majority of South Africans. But they are also often unsafe vehicles, at times involved in horrific road accidents.
Devin De Vries, one of the platform’s co-founders, says he was inspired by the Digital Matatus project in Nairobi. The South African platform differs, however, in that it provides open source information for others who think they may have a solution to South Africa’s troubled public transportation system.
“Transport is a complex ecosystem, and we don’t think any one company will solve it, De Vries told Quartz. “That’s why we made our platform open and hope that many endpoints—apps, websites, et cetera—will draw on the data so people can access it.”
This could lead to trip planning apps like Moovit or Transit for African commuters, or help cities better map their public transportation system, De Vries hopes…(More)”
The Innovation-Friendly Organization
Book by Anna Simpson: “This book explores five cultural traits – Diversity, Integrity, Curiosity, Reflection, and Connection – that encourage the birth and successful development of new ideas, and shows how organizations that are serious about innovation can embrace them.
Innovation – the driver of change and resilience – It is totally dependent on culture, the social environment which shapes how ideas emerge and evolve. Ideas need to breathe, and culture determines the quality of the air. If it’s stuffy and lacks flow, then no idea, however brilliant, will live long enough to fulfil its potential.
Creating these innovation-friendly conditions is one of the key challenges facing organizations today, and one that is especially difficult for them – focused as they are on efficiency and control. Innovation, Anna Simpson argues, begins with diversity of thought and attitude: the opposite of conformity and standardisation.
Likewise, with ongoing pressures to deliver results before yesterday, how can organizations allow sufficient space for the seemingly aimless process of following interesting possibilities and pondering on the impact of various options?Anna Simpson shows how large organizations can adapt their culture to enable the exchange of different perspectives; to support each person to bring their whole self to their work; to embrace the aimlessness that fosters creative experimentation; to take the time to approach change with the care it deserves, and – lastly – to develop the collective strength needed to face the ultimate ‘sledgehammer test’….(More)”.
Embracing Innovation in Government Global Trends
Report by the OECD: “Innovation in government is about finding new ways to impact the lives of citizens, and new approaches to activating them as partners to shape the future together. It involves overcoming old structures and modes of thinking and embracing new technologies and ideas. The potential of innovation in government is immense; however, the challenges governments face are significant. Despite this, governments are transforming the way they work to ensure this potential is met….
Since 2014, the OECD Observatory of Public Sector Innovation (OPSI), an OECD Directorate for Public Governance and Territorial Development (GOV) initiative, has been working to identify the key issues for innovation in government and what can be done to achieve greater impact. To learn from governments on the leading edge of this field, OPSI has partnered with the Government of the United Arab Emirates (UAE) and its Mohammed Bin Rashid Centre for Government Innovation (MBRCGI) , as part of the Middle East and North Africa (MENA)-OECD Governance Programme, to conduct a global review of new ways in which governments are transforming their operations and improving the lives of their people, culminating in this report.
Through research and an open Call for Innovations, the review surfaces key trends, challenges, and success factors in innovation today, as well as examples and case studies to illustrate them and recommendations to help support innovation. This report is published in conjunction with the 2017 World Government Summit, which brings together over 100 countries to discuss innovative ways to solve the challenges facing humanity….(More)”
Big data may be reinforcing racial bias in the criminal justice system
Laurel Eckhouse at the Washington Post: “Big data has expanded to the criminal justice system. In Los Angeles, police use computerized “predictive policing” to anticipate crimes and allocate officers. In Fort Lauderdale, Fla., machine-learning algorithms are used to set bond amounts. In states across the country, data-driven estimates of the risk of recidivism are being used to set jail sentences.
Advocates say these data-driven tools remove human bias from the system, making it more fair as well as more effective. But even as they have become widespread, we have little information about exactly how they work. Few of the organizations producing them have released the data and algorithms they use to determine risk.
We need to know more, because it’s clear that such systems face a fundamental problem: The data they rely on are collected by a criminal justice system in which race makes a big difference in the probability of arrest — even for people who behave identically. Inputs derived from biased policing will inevitably make black and Latino defendants look riskier than white defendants to a computer. As a result, data-driven decision-making risks exacerbating, rather than eliminating, racial bias in criminal justice.
Consider a judge tasked with making a decision about bail for two defendants, one black and one white. Our two defendants have behaved in exactly the same way prior to their arrest: They used drugs in the same amount, have committed the same traffic offenses, owned similar homes and took their two children to the same school every morning. But the criminal justice algorithms do not rely on all of a defendant’s prior actions to reach a bail assessment — just those actions for which he or she has been previously arrested and convicted. Because of racial biases in arrest and conviction rates, the black defendant is more likely to have a prior conviction than the white one, despite identical conduct. A risk assessment relying on racially compromised criminal-history data will unfairly rate the black defendant as riskier than the white defendant.
To make matters worse, risk-assessment tools typically evaluate their success in predicting a defendant’s dangerousness on rearrests — not on defendants’ overall behavior after release. If our two defendants return to the same neighborhood and continue their identical lives, the black defendant is more likely to be arrested. Thus, the tool will falsely appear to predict dangerousness effectively, because the entire process is circular: Racial disparities in arrests bias both the predictions and the justification for those predictions.
We know that a black person and a white person are not equally likely to be stopped by police: Evidence on New York’s stop-and-frisk policy, investigatory stops, vehicle searches and drug arrests show that black and Latino civilians are more likely to be stopped, searched and arrested than whites. In 2012, a white attorney spent days trying to get himself arrested in Brooklyn for carrying graffiti stencils and spray paint, a Class B misdemeanor. Even when police saw him tagging the City Hall gateposts, they sped past him, ignoring a crime for which 3,598 people were arrested by the New York Police Department the following year.
Before adopting risk-assessment tools in the judicial decision-making process, jurisdictions should demand that any tool being implemented undergo a thorough and independent peer-review process. We need more transparencyand better data to learn whether these risk assessments have disparate impacts on defendants of different races. Foundations and organizations developing risk-assessment tools should be willing to release the data used to build these tools to researchers to evaluate their techniques for internal racial bias and problems of statistical interpretation. Even better, with multiple sources of data, researchers could identify biases in data generated by the criminal justice system before the data is used to make decisions about liberty. Unfortunately, producers of risk-assessment tools — even nonprofit organizations — have not voluntarily released anonymized data and computational details to other researchers, as is now standard in quantitative social science research….(More)”.
Managing for Social Impact: Innovations in Responsible Enterprise
Book edited by Mary J, Cronin and , Tiziana C. Dearing: “This book presents innovative strategies for sustainable, socially responsible enterprise management from leading thinkers in the fields of corporate citizenship, nonprofit management, social entrepreneurship, impact investing, community-based economic development and urban design. The book’s integration of research and practitioner perspectives with focused best practice examples offers an in-depth, balanced analysis, providing new insights into the social issues that are most relevant to organizational stakeholders. This integrated focus on sustainable social innovation differentiates the book from academic research monographs on stakeholder theory and practitioner guides to managing traditional Corporate Social Responsibility (CSR) programs.
Managing for Social Impact features 15 contributed chapters written by thought leaders, industry analysts, and managers of global and local organizations who are engaged with innovative models of sustainable social impact. The editors also provide a substantive introductory chapter describing a new strategic framework for enhancing the Return on Social Innovation (ROSI) through four pillars of social change: Open Circles, Focused Purpose Sharing, Mutuality of Success, and a Persistent Change Perspective….(More)”.
How to Do Social Science Without Data
Neil Gross in the New York Times: With the death last month of the sociologist Zygmunt Bauman at age 91, the intellectual world lost a thinker of rare insight and range. Because his style of work was radically different from that of most social scientists in the United States today, his passing is an occasion to consider what might be gained if more members of our profession were to follow his example….
Weber saw bureaucracies as powerful, but dispiritingly impersonal. Mr. Bauman amended this: Bureaucracy can be inhuman. Bureaucratic structures had deadened the moral sense of ordinary German soldiers, he contended, which made the Holocaust possible. They could tell themselves they were just doing their job and following orders.
Later, Mr. Bauman turned his scholarly attention to the postwar and late-20th-century worlds, where the nature and role of all-encompassing institutions were again his focal point. Craving stability after the war, he argued, people had set up such institutions to direct their lives — more benign versions of Weber’s bureaucracy. You could go to work for a company at a young age and know that it would be a sheltering umbrella for you until you retired. Governments kept the peace and helped those who couldn’t help themselves. Marriages were formed through community ties and were expected to last.
But by the end of the century, under pressure from various sources, those institutions were withering. Economically, global trade had expanded, while in Europe and North America manufacturing went into decline; job security vanished. Politically, too, changes were afoot: The Cold War drew to an end, Europe integrated and politicians trimmed back the welfare state. Culturally, consumerism seemed to pervade everything. Mr. Bauman noted major shifts in love and intimacy as well, including a growing belief in the contingency of marriage and — eventually — the popularity of online dating.
In Mr. Bauman’s view, it all connected. He argued we were witnessing a transition from the “solid modernity” of the mid-20th century to the “liquid modernity” of today. Life had become freer, more fluid and a lot more risky. In principle, contemporary workers could change jobs whenever they got bored. They could relocate abroad or reinvent themselves through shopping. They could find new sexual partners with the push of a button. But there was little continuity.
Mr. Bauman considered the implications. Some thrived in this new atmosphere; the institutions and norms previously in place could be stultifying, oppressive. But could a transient work force come together to fight for a more equitable distribution of resources? Could shopping-obsessed consumers return to the task of being responsible, engaged citizens? Could intimate partners motivated by short-term desire ever learn the value of commitment?…(More)”
Citizen Empowerment and Innovation in the Data-Rich City
Book edited by C. Certomà, M. Dyer, L. Pocatilu and F. Rizzi: “… analyzes the ongoing transformation in the “smart city” paradigm and explores the possibilities that technological innovations offer for the effective involvement of ordinary citizens in collective knowledge production and decision-making processes within the context of urban planning and management. To so, it pursues an interdisciplinary approach, with contributions from a range of experts including city managers, public policy makers, Information and Communication Technology (ICT) specialists, and researchers. The first two parts of the book focus on the generation and use of data by citizens, with or without institutional support, and the professional management of data in city governance, highlighting the social connectivity and livability aspects essential to vibrant and healthy urban environments. In turn, the third part presents inspiring case studies that illustrate how data-driven solutions can empower people and improve urban environments, including enhanced sustainability. The book will appeal to all those who are interested in the required transformation in the planning, management, and operations of data-rich cities and the ways in which such cities can employ the latest technologies to use data efficiently, promoting data access, data sharing, and interoperability….(More)”.
Code-Dependent: Pros and Cons of the Algorithm Age
Janna Anderson and Lee Rainie at PewResearch Center: “Algorithms are instructions for solving a problem or completing a task. Recipes are algorithms, as are math equations. Computer code is algorithmic. The internet runs on algorithms and all online searching is accomplished through them. Email knows where to go thanks to algorithms. Smartphone apps are nothing but algorithms. Computer and video games are algorithmic storytelling. Online dating and book-recommendation and travel websites would not function without algorithms. GPS mapping systems get people from point A to point B via algorithms. Artificial intelligence (AI) is naught but algorithms. The material people see on social media is brought to them by algorithms. In fact, everything people see and do on the web is a product of algorithms. Every time someone sorts a column in a spreadsheet, algorithms are at play, and most financial transactions today are accomplished by algorithms. Algorithms help gadgets respond to voice commands, recognize faces, sort photos and build and drive cars. Hacking, cyberattacks and cryptographic code-breaking exploit algorithms. Self-learning and self-programming algorithms are now emerging, so it is possible that in the future algorithms will write many if not most algorithms.
Algorithms are often elegant and incredibly useful tools used to accomplish tasks. They are mostly invisible aids, augmenting human lives in increasingly incredible ways. However, sometimes the application of algorithms created with good intentions leads to unintended consequences. Recent news items tie to these concerns:
- The British pound dropped 6.1% in value in seconds on Oct. 7, 2016, partly because of currency trades triggered by algorithms.
- Microsoft engineers created a Twitter bot named “Tay” this past spring in an attempt to chat with Millennials by responding to their prompts, but within hours it was spouting racist, sexist, Holocaust-denying tweets based on algorithms that had it “learning” how to respond to others based on what was tweeted at it.
- Facebook tried to create a feature to highlight Trending Topics from around the site in people’s feeds. First, it had a team of humans edit the feature, but controversy erupted when some accused the platform of being biased against conservatives. So, Facebook then turned the job over to algorithms only to find that they could not discern real news from fake news….(More)”.