Can the crowd deliver more open government?


  at GovernmentNews: “…Crowdsourcing and policy making was the subject of a lecture by visiting academic Dr Tanja Aitamurto at Victoria’s Swinburne University of Technology earlier this month. Dr Aitamurto wrote “Crowdsourcing for Democracy: New Era in Policy-Making” and led the design and implementation of the Finnish Experiment, a pioneering case study in crowdsourcing policy making.

She spoke about how Scandinavian countries have used crowdsourcing to “tap into the collective intelligence of a large and diverse crowd” in an “open ended knowledge information search process” in an open call for anybody to participate online and complete a task.

It has already been used widely and effectively by companies  such as Proctor and Gamble who offer a financial reward for solutions to their R&D problems.

The Finnish government recently used crowdsourcing when it came to reform the country’s Traffic Act following a rash of complaints to the Minister of the Environment about it. The Act, which regulates issues such as off-road traffic, is an emotive issue in Finland where snow mobiles are used six months of the year and many people live in remote areas.

The idea was for people to submit problems and solutions online, covering areas such as safety, noise, environmental protection, the rights of snowmobile owners and landowners’ rights. Everyone could see what was written and could comment on it.

Dr Aitamurto said crowdsourcing had four stages:

• The problem mapping space, where people were asked to outline the issues that needed solving
• An appeal for solutions
• An expert panel evaluated the comments received based on the criteria of: effectiveness, cost efficiency, ease of implementation and fairness. The crowd also had the chance to evaluate and rank solutions online
• The findings were then handed over to the government for the law writing process

Dr Aitamurto said active participation seemed to create a strong sense of empowerment for those involved.

She said some people reported that it was the first time in their lives they felt they were really participating in democracy and influencing decision making in society. They said it felt much more real than voting in an election, which felt alien and remote.

“Participation becomes a channel for advocacy, not just for self-interest but a channel to hear what others are saying and then also to make yourself heard. People expected a compromise at the end,” Dr Aitamurto said.

Being able to participate online was ideal for people who lived remotely and turned crowdsourcing into a democratic innovation which brought citizens closer to policy and decision making between elections.

Other benefits included reaching out to tap into new pools of knowledge, rather than relying on a small group of homogenous experts to solve the problem.

“When we use crowdsourcing we actually extend our knowledge search to multiple, hundreds of thousands of distant neighbourhoods online and that can be the power of crowdsourcing: to find solutions and information that we wouldn’t find otherwise. We find also unexpected information because it’s a self-selecting crowd … people that we might not have in our networks already,” Dr Aitamurto said.

The process can increase transparency as people interact on online platforms and where the government keeps feedback loops going.

Dr Aitamurto is also a pains to highlight what crowdsourcing is not and cannot be, because participants are self-selecting and not statistically representative.

“The crowd doesn’t make decisions, it provides information. It’s not a method or tool for direct democracy and it’s not a public opinion poll either”.

Crowdsourcing has fed into policy in other countries too, for example, during Iceland’s constitutional reform and in the United States where the federal Emergency Management Agency overhauled its strategy after a string of natural disasters.

Australian government has been getting in on the act using cloud-based software Citizen Space to gain input into a huge range of topics. While much of it is technically consultation, rather than feeding into actual policy design, it is certainly a step towards more open government.

British company Delib, which is behind the software, bills it as “managing, publicising and archiving all of your organisation’s consultation activity”.

One council who has used Citizens Space is Wyong Shire on the NSW Central Coast. The council has used the consultation hub to elicit ratepayers’ views on a number of topics, including a special rate variation, community precinct forums, strategic plans and planning decisions.

One of Citizen Space’s most valuable features is the section ‘we asked, you said, we did’….(More)”

How Startups Are Transforming the Smart City Movement


Jason Shueh at GovTech: “Remember the 1990s visions of the future? Those first incantations of the sweeping “smart city,” so technologically utopian and Tomorrowland-ish in design? The concept and solutions were pitched by tech titans like IBM and Cisco, cost obscene amounts of money, and promised equally outlandish levels of innovation.

It was a drive — as idealistic as it was expedient — to spark a new industry that infused cities with data, analytics, sensors and clean energy. Two-and-a-half decades later, the smart city market has evolved. Its solutions are more pragmatic and its benefits more potent. Evidence brims inSingapore, where officials boast that they can predict traffic congestion an hour in advance with 90 percent accuracy. Similarly, in Chicago, the city has embraced analytics to estimate rodent infestations and prioritizerestaurant inspections. These of course are a few standouts, but as many know, the movement is highly diverse and runs its fingers through cities and across continents.

And yet what’s not as well-known is what’s happened in the last few years. The industry appears to be undergoing another metamorphosis, one that takes the ingenuity inspired by its beginnings and reimagines it with the help of do-it-yourself entrepreneurs….

Asked for a definition, Abrahamson centered his interpretation on tech that enhances quality of life. With the possible exception of health care, finance and education — systems large enough to merit their own categories, Abrahamson explains smart cities by highlighting investment areas at Urban.us. Specific areas are packaged as follows:

Mobility and Logistics: How cities move people and things to, from and within cities.

Built Environment: The public and private spaces in which citizens work and live.

Utilities: Critical resources including water, waste and energy.

Service Delivery: How local governments provide services ranging from public works to law enforcement….

Who’s Investing?

….Here is a sampling of a few types, with examples of their startup investments.

General Venture Capitalists

a16z (Andreessen Horowitz) – Mapillary and Moovit

Specialty Venture Capitalists

Fontinalis – Lyft, ParkMe, LocoMobi

Black Coral Capital – Digital Lumens, Clean Energy Collective, newterra

Govtech Fund – AmigoCloud, Mark43, MindMixer

Corporate Venture Capitalists

Google Ventures – Uber, Skycatch, Nest

Motorola Solutions Venture Capital – CyPhy Works and SceneDoc

BMW i Ventures – Life360 and ChargePoint

Impact/Social Investors

Omidyar Network – SeeClickFix and Nationbuilder

Knight Foundation – Public Stuff, Captricity

Kapor Capital – Uber, Via, Blocpower

1776 – Radiator Labs, Water Lens… (More)

The World of Indicators: The Making of Governmental Knowledge through Quantification


New Book by Richard Rottenburg et al: “The twenty-first century has seen a further dramatic increase in the use of quantitative knowledge for governing social life after its explosion in the 1980s. Indicators and rankings play an increasing role in the way governmental and non-governmental organizations distribute attention, make decisions, and allocate scarce resources. Quantitative knowledge promises to be more objective and straightforward as well as more transparent and open for public debate than qualitative knowledge, thus producing more democratic decision-making. However, we know little about the social processes through which this knowledge is constituted nor its effects. Understanding how such numeric knowledge is produced and used is increasingly important as proliferating technologies of quantification alter modes of knowing in subtle and often unrecognized ways. This book explores the implications of the global multiplication of indicators as a specific technology of numeric knowledge production used in governance. (More)”

Memex Human Trafficking


MEMEX is a DARPA program that explores how next generation search and extraction systems can help with real-world use cases. The initial application is the fight against human trafficking. In this application, the input is a portion of the public and dark web in which human traffickers are likely to (surreptitiously) post supply and demand information about illegal labor, sex workers, and more. DeepDive processes such documents to extract evidential data, such as names, addresses, phone numbers, job types, job requirements, information about rates of service, etc. Some of these data items are difficult for trained human annotators to accurately extract and have never been previously available, but DeepDive-based systems have high accuracy (Precision and Recall in the 90s, which may exceed non-experts). Together with provenance information, such structured, evidential data are then passed on to both other collaborators on the MEMEX program as well as law enforcement for analysis and consumption in operational applications. MEMEX has been featured extensively in the media and is supporting actual investigations. For example, every human trafficking investigation pursued by the Human Trafficking Response Unity in New York City involves MEMEX. DeepDive is the main extracted data provider for MEMEX. See also, 60 minutes, Scientific American, Wall St. Journal, BBC, and Wired. It is supporting actual investigations and perhaps new usecases in the war on terror.

Here is a detailed description of DeepDive’s role in MEMEX.”

 

Proofreading of legal documents


 at Techcrunch: “.. jEugene…helps the drafters of legal documents catch mistakes that could be fatal to such documents’ validity or enforceability.

The original idea of Harry Zhou, who, as a first-year lawyer, was tasked with proofing a 250-page contract and wanted more than his supervising lawyer’s assurance that “you did great,” jEugene scans through a legal document and highlights in text potential drafting mistakes in the document.

The product is being used by White & Case LLP and is undergoing trial at Fenwick & West LLP. Tens of smaller law firms are accessing jEugene through Clio, a provider of cloud-based legal management software. Other clients are under NDA.

Errors that jEugene currently detects may seem innocuous at times, but could lead to hefty costs. For example, millions of dollars that certain creditors recently failed to recover in a famous bankruptcy case could have been avoided had jEugene been used; and jEugene’s analysis of legal documents disclosed on SEC EDGAR routinely reveals similar errors missed by some of the most sophisticated law firms (they say).

Here’s how it works: A user uploads a document, waits a few seconds, and downloads the resulting file. This emulates handwritten markups that lawyers are used to seeing, and highlights potential drafting mistakes in the document with different colors. The user then reviews the results to determine whether any revision is necessary….(More)”

Anonymization and Risk


Paper by Ira Rubinstein and Woodrow Hartzog: “Perfect anonymization of data sets has failed. But the process of protecting data subjects in shared information remains integral to privacy practice and policy. While the deidentification debate has been vigorous and productive, there is no clear direction for policy. As a result, the law has been slow to adapt a holistic approach to protecting data subjects when data sets are released to others. Currently, the law is focused on whether an individual can be identified within a given set. We argue that the better locus of data release policy is on the process of minimizing the risk of reidentification and sensitive attribute disclosure. Process-based data release policy, which resembles the law of data security, will help us move past the limitations of focusing on whether data sets have been “anonymized.” It draws upon different tactics to protect the privacy of data subjects, including accurate deidentification rhetoric, contracts prohibiting reidentification and sensitive attribute disclosure, data enclaves, and query-based strategies to match required protections with the level of risk. By focusing on process, data release policy can better balance privacy and utility where nearly all data exchanges carry some risk….(More)”

Journal of Technology Science


Technology Science is an open access forum for any original material dealing primarily with a social, political, personal, or organizational benefit or adverse consequence of technology. Studies that characterize a technology-society clash or present an approach to better harmonize technology and society are especially welcomed. Papers can come from anywhere in the world.

Technology Science is interested in reviews of research, experiments, surveys, tutorials, and analyses. Writings may propose solutions or describe unsolved problems. Technology Science may also publish letters, short communications, and relevant news items. All submissions are peer-reviewed.

The scientific study of technology-society clashes is a cross-disciplinary pursuit, so papers in Technology Science may come from any of many possible disciplinary traditions, including but not limited to social science, computer science, political science, law, economics, policy, or statistics.

The Data Privacy Lab at Harvard University publishes Technology Science and its affiliated subset of papers called the Journal of Technology Science and maintains them online at techscience.org and at jots.pub. Technology Science is available free of charge over the Internet. While it is possible that bound paper copies of Technology Science content may be produced for a fee, all content will continue to be offered online at no charge….(More)”

 

Index: Crime and Criminal Justice Data


The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on crime and criminal justice data and was originally published in 2015.

This index provides information about the type of crime and criminal justice data collected, shared and used in the United States. Because it is well known that data related to the criminal justice system is often times unreliable, or just plain missing, this index also highlights some of the issues that stand in the way of accessing useful and in-demand statistics.

Data Collections: National Crime Statistics

  • Number of incident-based crime datasets created by the Federal Bureau of Investigation (FBI): 2
    • Number of U.S. Statistical Agencies: 13
    • How many of those are focused on criminal justice: 1, the Bureau of Justice Statistics (BJS)
    • Number of data collections focused on criminal justice the BJS produces: 61
    • Number of federal-level APIs available for crime or criminal justice data: 1, the National Crime Victimization Survey (NCVS).
    • Frequency of the NCVS: annually
  • Number of Statistical Analysis Centers (SACs), organizations that are essentially clearinghouses for crime and criminal justice data for each state, the District of Columbia, Puerto Rico and the Northern Mariana Islands: 53

Open data, data use and the impact of those efforts

  • Number of datasets that are returned when “criminal justice” is searched for on Data.gov: 417, including federal-, state- and city-level datasets
  • Number of datasets that are returned when “crime” is searched for on Data.gov: 281
  • The percentage that public complaints dropped after officers started wearing body cameras, according to a study done in Rialto, Calif.: 88
  • The percentage that reported incidents of officer use of force fell after officers started wearing body cameras, according to a study done in Rialto, Calif.: 5
  • The percent that crime decreased during an experiment in predictive policing in Shreveport, LA: 35  
  • Number of crime data sets made available by the Seattle Police Department – generally seen as a leader in police data innovation – on the Seattle.gov website: 4
    • Major crime stats by category in aggregate
    • Crime trend reports
    • Precinct data by beat
    • State sex offender database
  • Number of datasets mapped by the Seattle Police Department: 2:
      • 911 incidents
    • Police reports
  • Number of states where risk assessment tools must be used in pretrial proceedings to help determine whether an offender is released from jail before a trial: at least 11.

Police Data

    • Number of federally mandated databases that collect information about officer use of force or officer involved shootings, nationwide: 0
    • The year a crime bill was passed that called for data on excessive force to be collected for research and statistical purposes, but has never been funded: 1994
    • Number of police departments that committed to being a part of the White House’s Police Data Initiative: 21
    • Percentage of police departments surveyed in 2013 by the Office of Community Oriented Policing within the Department of Justice that are not using body cameras, therefore not collecting body camera data: 75

The criminal justice system

  • Parts of the criminal justice system where data about an individual can be created or collected: at least 6
    • Entry into the system (arrest)
    • Prosecution and pretrial
    • Sentencing
    • Corrections
    • Probation/parole
    • Recidivism

Sources

  • Crime Mapper. Philadelphia Police Department. Accessed August 24, 2014.

e-Consultation Platforms: Generating or Just Recycling Ideas?


Chapter by Efthimios TambourisAnastasia Migotzidou, and Konstantinos Tarabanis in Electronic Participation: “A number of governments worldwide employ web-based e-consultation platforms to enable stakeholders commenting on draft legislation. Stakeholders’ input includes arguing in favour or against the proposed legislation as well as proposing alternative ideas. In this paper, we empirically investigate the relationship between the volume of contributions in these platforms and the amount of new ideas that are generated. This enables us to determine whether participants in such platforms keep generating new ideas or just recycle a finite number of ideas. We capitalised on argumentation models to code and analyse a large number of draft law consultations published inopengov.gr, the official e-consultation platform for draft legislation in Greece. Our results suggest that as the number of posts grows, the number of new ideas continues to increase. The results of this study improve our understanding of the dynamics of these consultations and enable us to design better platforms….(More)”

 

Policy makers’ perceptions on the transformational effect of Web 2.0 technologies on public services delivery


Paper by Manuel Pedro Rodríguez Bolívar at Electronic Commerce Research: “The growing participation in social networking sites is altering the nature of social relations and changing the nature of political and public dialogue. This paper contributes to the current debate on Web 2.0 technologies and their implications for local governance, identifying the perceptions of policy makers on the use of Web 2.0 in providing public services and on the changing roles that could arise from the resulting interaction between local governments and their stakeholders. The results obtained suggest that policy makers are willing to implement Web 2.0 technologies in providing public services, but preferably under the Bureaucratic model framework, thus retaining a leading role in this implementation. The learning curve of local governments in the use of Web 2.0 technologies is a factor that could influence policy makers’ perceptions. In this respect, many research gaps are identified and further study of the question is recommended….(More)”