In design as in politics: who decides?


Joan Subirats at Open Democracy: “Can we keep on organizing decision-making processes as we used to do in the age of the Enlightenment or in a scenario where information only flows from top to bottom? Designers and creators have been questioning this for a long time now, seeking to go beyond the user paradigm which has determined innovation processes in recent decades. Today, their concern is how to put people at the center of new experiences…..

Today, in the world of design, emphasis is being placed on the fact that all those who will want or will be able to use a product or service should be incorporated into the creative process itself. On the other hand, science has shown that we cannot imagine designing a building or constructing an infrastructure without taking into account the materials we use, the impact on the surroundings, and the effects on the environment and on the functioning of the city where the new building is located or the new service is to come into operation. The building, the infrastructure “participates” in a complex environment than cannot be ignored. The design of any object or activity is not immune to all that is around it and to the materials used to build or imagine it – nor is its destruction or disappearance. The design of “things” cannot be only a framework in which participants are to be assumed as data, the design itself has to be “participated”.

In this sense, designers cannot avoid being participants, just as politicians cannot avoid being citizens. In the same way as you cannot complain about a traffic jam where you find yourself stuck as if the whole problem was due to others, for the simple reason that you are part of this traffic and this jam. We need design and policy-making systems that do not have designers sitting in a bubble, seemingly immune to what goes on outside. We need political decision-making systems that invite-incite-engage people, rather than processes that ask people to participate in what others have thought needs to be done. And, surely, to do this, we need a little more humility when it comes to doing politics – and this implies changing power structures and the distribution of responsibilities. In the face of ever more complex problems, with more structural implications and more heterogeneous interests, we need a reconfiguration and an expansion of collective decision-making mechanisms…. (More) (Español).”

How are Italian Companies Embracing Open Data?


open-data-200-italy (1)Are companies embracing the use of open government data? How, why and what data is being leveraged? To answer these questions, the GovLab started a project three years ago, Open Data 500, to map and assess — in a comparative manner, across sectors and countries — the private sector’s use of open data to develop new products and services, and create social value.

Today we are launching Open Data 200 Italy, in partnership with Fondazione Bruno Kessler, which seeks to showcase the breadth and depth of companies using open data in Italy.

OD200 Italy is the first and only platform to map the use of open data by companies in Italy. 

Our findings show there is a growing ecosystem around open data in Italy that goes beyond traditional open data advocates. …

The OD200 Italy project shows the diversity of data being used, which makes it necessary to keep open data broad and sustained.

“The merits and use of open data for businesses are often praised but not supported by evidence. OD200 Italy is a great contribution to the evidence base of who, how and why corporations are leveraging open data,” said Stefaan Verhulst, Co-Founder of The GovLab and Chief Research and Development Officer. “Policy makers, practitioners and researchers can leverage the data generated by this initiative to improve the supply and use of open data, or to generate new insights. As such, OD200 Italy is a new open data set on open data.”…(More)”.

Plato and the Nerd. The Creative Partnership of Humans and Technology


MITPress: “In this book, Edward Ashford Lee makes a bold claim: that the creators of digital technology have an unsurpassed medium for creativity. Technology has advanced to the point where progress seems limited not by physical constraints but the human imagination. Writing for both literate technologists and numerate humanists, Lee makes a case for engineering—creating technology—as a deeply intellectual and fundamentally creative process. Explaining why digital technology has been so transformative and so liberating, Lee argues that the real power of technology stems from its partnership with humans.

Lee explores the ways that engineers use models and abstraction to build inventive artificial worlds and to give us things that we never dreamed of—for example, the ability to carry in our pockets everything humans have ever published. But he also attempts to counter the runaway enthusiasm of some technology boosters who claim everything in the physical world is a computation—that even such complex phenomena as human cognition are software operating on digital data. Lee argues that the evidence for this is weak, and the likelihood that nature has limited itself to processes that conform to today’s notion of digital computation is remote.

Lee goes on to argue that artificial intelligence’s goal of reproducing human cognitive functions in computers vastly underestimates the potential of computers. In his view, technology is coevolving with humans. It augments our cognitive and physical capabilities while we nurture, develop, and propagate the technology itself. Complementarity is more likely than competition….(More)”.

Artificial Intelligence and Public Policy


Paper by Adam D. ThiererAndrea Castillo and Raymond Russell: “There is growing interest in the market potential of artificial intelligence (AI) technologies and applications as well as in the potential risks that these technologies might pose. As a result, questions are being raised about the legal and regulatory governance of AI, machine learning, “autonomous” systems, and related robotic and data technologies. Fearing concerns about labor market effects, social inequality, and even physical harm, some have called for precautionary regulations that could have the effect of limiting AI development and deployment. In this paper, we recommend a different policy framework for AI technologies. At this nascent stage of AI technology development, we think a better case can be made for prudence, patience, and a continuing embrace of “permissionless innovation” as it pertains to modern digital technologies. Unless a compelling case can be made that a new invention will bring serious harm to society, innovation should be allowed to continue unabated, and problems, if they develop at all, can be addressed later…(More)”.

Harnessing the Data Revolution to Achieve the Sustainable Development Goals


Erol Yayboke et al at CSIS: “Functioning societies collect accurate data and utilize the evidence to inform policy. The use of evidence derived from data in policymaking requires the capability to collect and analyze accurate data, clear administrative channels through which timely evidence is made available to decisionmakers, and the political will to rely on—and ideally share—the evidence. The collection of accurate and timely data, especially in the developing world, is often logistically difficult, not politically expedient, and/or expensive.

Before launching its second round of global goals—the Sustainable Development Goals (SDGs)—the United Nations convened a High-Level Panel of Eminent Persons on the Post-2015 Development Agenda. As part of its final report, the Panel called for a “data revolution” and recommended the formation of an independent body to lead the charge.1The report resulted in the creation of the Global Partnership for Sustainable Development Data (GPSDD)—an independent group of countries, companies, data communities, and NGOs—and the SDG Data Labs, a private initiative partnered with the GPSDD. In doing so the United Nations and its partners signaled broad interest in data and evidence-based policymaking at a high level. In fact, the GPSDD calls for the “revolution in data” by addressing the “crisis of non-existent, inaccessible or unreliable data.”As this report shows, this is easier said than done.

This report defines the data revolution as an unprecedented increase in the volume and types of data—and the subsequent demand for them—thanks to the ongoing yet uneven proliferation of new technologies. This revolution is allowing governments, companies, researchers, and citizens to monitor progress and drive action, often with real-time, dynamic, disaggregated data. Much work will be needed to make sure the data revolution reaches developing countries facing difficult challenges (i.e., before the data revolution fully becomes the data revolution for sustainable development). It is important to think of the revolution as a multistep process, beginning with building basic knowledge and awareness of the value of data. This is followed by a more specific focus on public private partnerships, opportunities, and constraints regarding collection and utilization of data for evidence-based policy decisions….

This report provides the following recommendations to the international community to play a constructive role in the data revolution:

  • Don’t fixate on big data alone. Focus on the foundation necessary to facilitate leapfrogs around all types of data: small, big, and everywhere in between.
  • Increase funding for capacity building as part of an expansion of broader educational development priorities.
  • Highlight, share, and support enlightened government-driven approaches to data.
  • Increase funding for the data revolution and coordinate donor efforts.
  • Coordinate UN data revolution-related activities closely with an expanded GPSDD.
  • Secure consensus on data sharing, ownership, and privacy-related international standards….(More)”.

MIT map offers real-time, crowd-sourced flood reporting during Hurricane Irma


MIT News: “As Hurricane Irma bears down on the U.S., the MIT Urban Risk Lab has launched a free, open-source platform that will help residents and government officials track flooding in Broward County, Florida. The platform, RiskMap.us, is being piloted to enable both residents and emergency managers to obtain better information on flooding conditions in near-real time.

Residents affected by flooding can add information to the publicly available map via popular social media channels. Using Twitter, Facebook, and Telegram, users submit reports by sending a direct message to the Risk Map chatbot. The chatbot replies to users with a one-time link through which they can upload information including location, flood depth, a photo, and description.

Residents and government officials can view the map to see recent flood reports to understand changing flood conditions across the county. Tomas Holderness, a research scientist in the MIT Department of Architecture, led the design of the system. “This project shows the importance that citizen data has to play in emergencies,” he says. “By connecting residents and emergency managers via social messaging, our map helps keep people informed and improve response times.”…

The Urban Risk Lab also piloted the system in Indonesia — where the project is called PetaBencana.id, or “Map Disaster” — during a large flood event on Feb. 20, 2017.

During the flooding, over 300,000 users visited the public website in 24 hours, and the map was integrated into the Uber application to help drivers avoid flood waters. The project in Indonesia is supported by a grant from USAID and is working in collaboration with the Indonesian Federal Emergency Management Agency, the Pacific Disaster Centre, and the Humanitarian Open Street Map Team.

The Urban Risk Lab team is also working in India on RiskMap.in….(More)”.

Feeding the Machine: Policing, Crime Data, & Algorithms


Elizabeth E. Joh at William & Mary Bill of Rights J. (2017 Forthcoming): “Discussions of predictive algorithms used by the police tend to assume the police are merely end users of big data. Accordingly, police departments are consumers and clients of big data — not much different than users of Spotify, Netflix, Amazon, or Facebook. Yet this assumption about big data policing contains a flaw. Police are not simply end users of big data. They generate the information that big data programs rely upon. This essay explains why predictive policing programs can’t be fully understood without an acknowledgment of the role police have in creating its inputs. Their choices, priorities, and even omissions become the inputs algorithms use to forecast crime. The filtered nature of crime data matters because these programs promise cutting edge results, but may deliver analyses with hidden limitations….(More)”.

Patient Power: Crowdsourcing in Cancer


Bonnie J. Addario at the HuffPost: “…Understanding how to manage and manipulate vast sums of medical data to improve research and treatments has become a top priority in the cancer enterprise. Researchers at the University of North Carolina Chapel Hill are using IBM’s Watson and its artificial intelligence computing power to great effect. Dr. Norman Sharpless told Charlie Rose from CBS’ 60 Minutes that Watson is reading tens of millions of medical papers weekly (8,000 new cancer research papers are published every day) and regularly scanning the web for new clinical trials most people, including researchers, are unaware of. The task is “essentially undoable” he said, for even the best, well-informed experts.

UNC’s effort is truly wonderful albeit a macro approach, less tailored and accessible only to certain medical centers. My experience tells me what the real problem is: How does a patient newly diagnosed with lung cancer, fragile and scared find the most relevant information without being overwhelmed and giving up? If the experts can’t easily find key data without Watson’s help, and Google’s first try turns up millions upon millions of semi-useful results, how do we build hope that there are good online answers for our patients?

We’ve thought about this a lot at the Addario Lung Cancer Foundation and figured out that the answer lies with the patients themselves. Why not crowdsource it with people who have lung cancer, their caregivers and family members?

So, we created the first-ever global Lung Cancer Patient Registry that simplifies the collection, management and distribution of critical health-related information – all in one place so that researchers and patients can easily access and find data specific to lung cancer patients.

This is a data-rich environment for those focusing solely on finding a cure for lung cancer. And it gives patients access to other patients to compare notes and generally feel safe sharing intimate details with their peers….(More)”

Unnatural Surveillance: How Online Data Is Putting Species at Risk


Adam Welz at YaleEnvironment360: “…The burgeoning pools of digital data from electronic tags, online scientific publications, “citizen science” databases and the like – which have been an extraordinary boon to researchers and conservationists – can easily be misused by poachers and illegal collectors. Although a handful of scientists have recently raised concerns about it, the problem is so far poorly understood.

Today, researchers are surveilling everything from blue whales to honeybees with remote cameras and electronic tags. While this has had real benefits for conservation, some attempts to use real-time location data in order to harm animals have become known: Hunters have shared tips on how to use VHF radio signals from Yellowstone National Park wolves’ research collars to locate the animals. (Although many collared wolves that roamed outside the park have been killed, no hunter has actually been caught tracking tag signals.) In 2013, hackers in India apparently successfully accessed tiger satellite-tag data, but wildlife authorities quickly increased security and no tigers seem to have been harmed as a result. Western Australian government agents used a boat-mounted acoustic tag detector to hunt tagged white sharks in 2015. (At least one shark was killed, but it was not confirmed whether it was tagged). Canada’s Banff National Park last year banned VHF radio receivers after photographers were suspected of harassing tagged animals.

While there is no proof yet of a widespread problem, experts say it is often in researchers’ and equipment manufacturers’ interests to underreport abuse. Biologist Steven Cooke of Carleton University in Canada lead-authored a paper this year cautioning that the “failure to adopt more proactive thinking about the unintended consequences of electronic tagging could lead to malicious exploitation and disturbance of the very organisms researchers hope to understand and conserve.” The paper warned that non-scientists could easily buy tags and receivers to poach animals and disrupt scientific studies, noting that “although telemetry terrorism may seem far-fetched, some fringe groups and industry players may have incentives for doing so.”…(More)”.

The Use of Big Data Analytics by the IRS: Efficient Solutions or the End of Privacy as We Know It?


Kimberly A. Houser and Debra Sanders in the Vanderbilt Journal of Entertainment and Technology Law: “This Article examines the privacy issues resulting from the IRS’s big data analytics program as well as the potential violations of federal law. Although historically, the IRS chose tax returns to audit based on internal mathematical mistakes or mismatches with third party reports (such as W-2s), the IRS is now engaging in data mining of public and commercial data pools (including social media) and creating highly detailed profiles of taxpayers upon which to run data analytics. This Article argues that current IRS practices, mostly unknown to the general public are violating fair information practices. This lack of transparency and accountability not only violates federal law regarding the government’s data collection activities and use of predictive algorithms, but may also result in discrimination. While the potential efficiencies that big data analytics provides may appear to be a panacea for the IRS’s budget woes, unchecked, these activities are a significant threat to privacy. Other concerns regarding the IRS’s entrée into big data are raised including the potential for political targeting, data breaches, and the misuse of such information. This Article intends to bring attention to these privacy concerns and contribute to the academic and policy discussions about the risks presented by the IRS’s data collection, mining and analytics activities….(More)”.