Jump to content

Government by algorithm

From Wikipedia, the free encyclopedia
(Redirected from Algocracy)
Not to be confused with Regulation of algorithms, e-government or Cyberocracy.
Part of a series on
Algocracy
Examples
Part of a series on
Governance
Models
By level
By field
Measures
Related topics

Government by algorithm[1] (also known as algorithmic regulation,[2] regulation by algorithms, algorithmic governance,[3] algocratic governance, algorithmic legal order or algocracy[4]) is an alternative form of government or social ordering where the usage of computer algorithms is applied to regulations, law enforcement, and generally any aspect of everyday life such as transportation or land registration.[5][6][7][8][9] The term "government by algorithm" has appeared in academic literature as an alternative for "algorithmic governance" in 2013.[10] A related term, algorithmic regulation, is defined as setting the standard, monitoring and modifying behaviour by means of computational algorithms – automation of judiciary is in its scope.[11] In the context of blockchain, it is also known as blockchain governance.[12]

Government by algorithm raises new challenges that are not captured in the e-government literature and the practice of public administration.[13] Some sources equate cyberocracy, which is a hypothetical form of government that rules by the effective use of information,[14][15][16] with algorithmic governance, although algorithms are not the only means of processing information.[17][18] Nello Cristianini and Teresa Scantamburlo argued that the combination of a human society and certain regulation algorithms (such as reputation-based scoring) forms a social machine.[19]

History

[edit]
Computer-generated image of Project Cybersyn operations room
LEGOL Group (1977)
"Blockchain and the future of governance. Let's overcome the hype and understand what can be done." with Andrea Bauer, Boris Moshkovits und Shermin Voshmgir at re:publica

In 1962, the director of the Institute for Information Transmission Problems of the Russian Academy of Sciences in Moscow (later Kharkevich Institute),[20] Alexander Kharkevich, published an article in the journal "Communist" about a computer network for processing information and control of the economy.[21][22] In fact, he proposed to make a network like the modern Internet for the needs of algorithmic governance (Project OGAS). This created a serious concern among CIA analysts.[23] In particular, Arthur M. Schlesinger Jr. warned that "by 1970 the USSR may have a radically new production technology, involving total enterprises or complexes of industries, managed by closed-loop, feedback control employing self-teaching computers".[23]

Between 1971 and 1973, the Chilean government carried out Project Cybersyn during the presidency of Salvador Allende. This project was aimed at constructing a distributed decision support system to improve the management of the national economy.[24][2] Elements of the project were used in 1972 to successfully overcome the traffic collapse caused by a CIA-sponsored strike of forty thousand truck drivers.[25]

Also in the 1960s and 1970s, Herbert A. Simon championed expert systems as tools for rationalization and evaluation of administrative behavior.[26] The automation of rule-based processes was an ambition of tax agencies over many decades resulting in varying success.[27] Early work from this period includes Thorne McCarty's influential TAXMAN project[28] in the US and Ronald Stamper's LEGOL project[29] in the UK. In 1993, the computer scientist Paul Cockshott from the University of Glasgow and the economist Allin Cottrell from the Wake Forest University published the book Towards a New Socialism, where they claim to demonstrate the possibility of a democratically planned economy built on modern computer technology.[30] The Honourable Justice Michael Kirby published a paper in 1998, where he expressed optimism that the then-available computer technologies such as legal expert system could evolve to computer systems, which will strongly affect the practice of courts.[31] In 2006, attorney Lawrence Lessig, known for the slogan "Code is law", wrote:

[T]he invisible hand of cyberspace is building an architecture that is quite the opposite of its architecture at its birth. This invisible hand, pushed by government and by commerce, is constructing an architecture that will perfect control and make highly efficient regulation possible[32]

Since the 2000s, algorithms have been designed and used to automatically analyze surveillance videos.[33]

In his 2006's book Virtual Migration, A. Aneesh developed the concept of algocracy — information technologies constrain human participation in public decision making.[34][35] Aneesh differentiated algocratic systems from bureaucratic systems (legal-rational regulation) as well as market-based systems (price-based regulation).[36]

In 2013, algorithmic regulation was coined by Tim O'Reilly, founder and CEO of O'Reilly Media Inc.:

Sometimes the "rules" aren't really even rules. Gordon Bruce, the former CIO of the city of Honolulu, explained to me that when he entered government from the private sector and tried to make changes, he was told, "That's against the law." His reply was "OK. Show me the law." "Well, it isn't really a law. It's a regulation." "OK. Show me the regulation." "Well, it isn't really a regulation. It's a policy that was put in place by Mr. Somebody twenty years ago." "Great. We can change that!" [...] Laws should specify goals, rights, outcomes, authorities, and limits. If specified broadly, those laws can stand the test of time. Regulations, which specify how to execute those laws in much more detail, should be regarded in much the same way that programmers regard their code and algorithms, that is, as a constantly updated toolset to achieve the outcomes specified in the laws. [...] It's time for government to enter the age of big data. Algorithmic regulation is an idea whose time has come.[37]

In 2017, Ukraine's Ministry of Justice ran experimental government auctions using blockchain technology to ensure transparency and hinder corruption in governmental transactions.[38] "Government by Algorithm?" was the central theme introduced at Data for Policy 2017 conference held on 6–7 September 2017 in London.[39]

Examples

[edit]

Smart cities

[edit]
Architecture of the IoT for home care systems

A smart city is an urban area where collected surveillance data is used to improve various operations. Increase in computational power allows more automated decision making and replacement of public agencies by algorithmic governance.[40] In particular, the combined use of artificial intelligence and blockchains for IoT may lead to the creation of sustainable smart city ecosystems.[41] Intelligent street lighting in Glasgow is an example of successful government application of AI algorithms.[42] A study of smart city initiatives in the US shows that it requires public sector as a main organizer and coordinator, the private sector as a technology and infrastructure provider, and universities as expertise contributors.[43]

The cryptocurrency millionaire Jeffrey Berns proposed the operation of local governments in Nevada by tech firms in 2021.[44] Berns bought 67,000 acres (271 km2) in Nevada's rural Storey County (population 4,104) for $170,000,000 (£121,000,000) in 2018 in order to develop a smart city with more than 36,000 residents that could generate an annual output of $4,600,000,000.[44] Cryptocurrency will be allowed for payments.[44] Blockchains, Inc. "Innovation Zone" was canceled in September 2021 after it failed to secure enough water[45] for the planned 36,000 residents, through water imports from a site located 100 miles away in the neighboring Washoe County.[46] Similar water pipeline proposed in 2007 was estimated to cost $100 million and to would have taken about 10 years to develop.[46] With additional water rights purchased from Tahoe Reno Industrial General Improvement District, "Innovation Zone" would have acquired enough water for about 15,400 homes - meaning that it would have barely covered its planned 15,000 dwelling units, leaving nothing for the rest of the projected city and its 22 million square-feet of industrial development.[46]

In Saudi Arabia, the planners of The Line assert that it will be monitored by AI to improve life by using data and predictive modeling.[47]

Reputation systems

[edit]
See also: Credit score
Model of cybernetic thinking about organisation. On the one hand in reality a system is determined. On the other hand, cybernetic factory can be modeled as a control system.[48]

Tim O'Reilly suggested that data sources and reputation systems combined in algorithmic regulation can outperform traditional regulations.[37] For instance, once taxi-drivers are rated by passengers, the quality of their services will improve automatically and "drivers who provide poor service are eliminated".[37] O'Reilly's suggestion is based on control-theoreric concept of feed-back loop—improvements and disimprovements of reputation enforce desired behavior.[19] The usage of feed-loops for the management of social systems is already been suggested in management cybernetics by Stafford Beer before.[49]

These connections are explored by Nello Cristianini and Teresa Scantamburlo, where the reputation-credit scoring system is modeled as an incentive given to the citizens and computed by a social machine, so that rational agents would be motivated to increase their score by adapting their behaviour. Several ethical aspects of that technology are still being discussed.[19]

China's Social Credit System was said to be a mass surveillance effort with a centralized numerical score for each citizen given for their actions, though newer reports say that this is a widespread misconception.[50][51][52]

Smart contracts

[edit]

Smart contracts, cryptocurrencies, and decentralized autonomous organization are mentioned as means to replace traditional ways of governance.[53][54][9] Cryptocurrencies are currencies, which are enabled by algorithms without a governmental central bank.[55] Central bank digital currency often employs similar technology, but is differentiated from the fact that it does use a central bank. It is soon to be employed by major unions and governments such as the European Union and China. Smart contracts are self-executable contracts, whose objectives are the reduction of need in trusted governmental intermediators, arbitrations and enforcement costs.[56][57] A decentralized autonomous organization is an organization represented by smart contracts that is transparent, controlled by shareholders and not influenced by a central government.[58][59][60] Smart contracts have been discussed for use in such applications as use in (temporary) employment contracts[61][62] and automatic transfership of funds and property (i.e. inheritance, upon registration of a death certificate).[63][64][65][66] Some countries such as Georgia and Sweden have already launched blockchain programs focusing on property (land titles and real estate ownership)[38][67][68][69] Ukraine is also looking at other areas too such as state registers.[38]

Algorithms in government agencies

[edit]
See also: Artificial intelligence in government
Team Rubicon in the Rockaways Nov 12, 2012 - Palantir screenshot

According to a study of Stanford University, 45% of the studied US federal agencies have experimented with AI and related machine learning (ML) tools up to 2020.[1] US federal agencies counted the number of artificial intelligence applications, which are listed below.[1] 53% of these applications were produced by in-house experts.[1] Commercial providers of residual applications include Palantir Technologies.[70]

Agency Name Number of Use Cases
Office of Justice Programs 12
Securities and Exchange Commission 10
National Aeronautics and Space Administration 9
Food and Drug Administration 8
United States Geological Survey 8
United States Postal Service 8
Social Security Administration 7
United States Patent and Trademark Office 6
Bureau of Labor Statistics 5
U.S. Customs and Border Protection 4

In 2012, NOPD started a collaboration with Palantir Technologies in the field of predictive policing.[71] Besides Palantir's Gotham software, other similar (numerical analysis software) used by police agencies (such as the NCRIC) include SAS.[72]

In the fight against money laundering, FinCEN employs the FinCEN Artificial Intelligence System (FAIS) since 1995.[73][74]

National health administration entities and organisations such as AHIMA (American Health Information Management Association) hold medical records. Medical records serve as the central repository for planning patient care and documenting communication among patient and health care provider and professionals contributing to the patient's care. In the EU, work is ongoing on a European Health Data Space which supports the use of health data.[75]

US Department of Homeland Security has employed the software ATLAS, which run on Amazon Cloud. It scanned more than 16.5 million of records of naturalized Americans and flagged approximately 124,000 of them for manual analysis and review by USCIS officers regarding denaturalization.[76][77] There were flagged due to potential fraud, public safety and national security issues. Some of the scanned data came from Terrorist Screening Database and National Crime Information Center.

The NarxCare is a US software,[78] which combines data from the prescription registries of various U.S. states[79][80] and uses machine learning to generate various three-digit "risk scores" for prescriptions of medications and an overall "Overdose Risk Score", collectively referred to as Narx Scores,[81] in a process that potentially includes EMS and criminal justice data[78] as well as court records.[82]

In Estonia, artificial intelligence is used in its e-government to make it more automated and seamless. A virtual assistant will guide citizens through any interactions they have with the government. Automated and proactive services "push" services to citizens at key events of their lives (including births, bereavements, unemployment, ...). One example is the automated registering of babies when they are born.[83] Estonia's X-Road system will also be rebuilt to include even more privacy control and accountability into the way the government uses citizen's data.[84]

In Costa Rica, the possible digitalization of public procurement activities (i.e. tenders for public works, ...) has been investigated. The paper discussing this possibility mentions that the use of ICT in procurement has several benefits such as increasing transparency, facilitating digital access to public tenders, reducing direct interaction between procurement officials and companies at moments of high integrity risk, increasing outreach and competition, and easier detection of irregularities.[85]

Besides using e-tenders for regular public works (construction of buildings, roads, ...), e-tenders can also be used for reforestation projects and other carbon sink restoration projects.[86] Carbon sink restoration projects may be part of the nationally determined contributions plans in order to reach the national Paris agreement goals

Government procurement audit software can also be used.[87][88] Audits are performed in some countries after subsidies have been received.

Some government agencies provide track and trace systems for services they offer. An example is track and trace for applications done by citizens (i.e. driving license procurement).[89]

Some government services use issue tracking system to keep track of ongoing issues.[90][91][92][93]

Justice by algorithm

[edit]

Judges' decisions in Australia are supported by the "Split Up" software in case of determining the percentage of a split after a divorce.[94] COMPAS software is used in USA to assess the risk of recidivism in courts.[95][96] According to the statement of Beijing Internet Court, China is the first country to create an internet court or cyber court.[97][98][99] The Chinese AI judge is a virtual recreation of an actual female judge. She "will help the court's judges complete repetitive basic work, including litigation reception, thus enabling professional practitioners to focus better on their trial work".[97] Also Estonia plans to employ artificial intelligence to decide small-claim cases of less than €7,000.[100]

Lawbots can perform tasks that are typically done by paralegals or young associates at law firms. One such technology used by US law firms to assist in legal research is from ROSS Intelligence,[101] and others vary in sophistication and dependence on scripted algorithms.[102] Another legal technology chatbot application is DoNotPay.

Algorithms in education

[edit]
Further information: Ofqual exam results algorithm

Due to the COVID-19 pandemic in 2020, in-person final exams were impossible for thousands of students.[103] The public high school Westminster High employed algorithms to assign grades. UK's Department for Education also employed a statistical calculus to assign final grades in A-levels, due to the pandemic.[104]

Besides use in grading, software systems like AI were used in preparation for college entrance exams.[105]

AI teaching assistants are being developed and used for education (e.g., Georgia Tech's Jill Watson)[106][107] and there is also an ongoing debate on whether perhaps teachers can be entirely replaced by AI systems (e.g., in homeschooling).[108]

AI politicians

[edit]
See also: Chatbot § Politics

In 2018, an activist named Michihito Matsuda ran for mayor in the Tama city area of Tokyo as a human proxy for an artificial intelligence program.[109] While election posters and campaign material used the term robot, and displayed stock images of a feminine android, the "AI mayor" was in fact a machine learning algorithm trained using Tama city datasets.[110] The project was backed by high-profile executives Tetsuzo Matsumoto of Softbank and Norio Murakami of Google.[111] Michihito Matsuda came third in the election, being defeated by Hiroyuki Abe.[112] Organisers claimed that the 'AI mayor' was programmed to analyze citizen petitions put forward to the city council in a more 'fair and balanced' way than human politicians.[113]

In 2018, Cesar Hidalgo presented the idea of augumented democracy.[114] In an augumented democracy, legislation is done by digital twins of every single person.

In 2019, AI-powered messenger chatbot SAM participated in the discussions on social media connected to an electoral race in New Zealand.[115] The creator of SAM, Nick Gerritsen, believes SAM will be advanced enough to run as a candidate by late 2020, when New Zealand has its next general election.[116]

In 2022, the chatbot "Leader Lars" or "Leder Lars" was nominated for The Synthetic Party to run in the 2022 Danish parliamentary election,[117] and was built by the artist collective Computer Lars.[118] Leader Lars differed from earlier virtual politicians by leading a political party and by not pretending to be an objective candidate.[119] This chatbot engaged in critical discussions on politics with users from around the world.[120]

In 2023, In the Japanese town of Manazuru, a mayoral candidate called "AI Mayer" hopes to be the first AI-powered officeholder in Japan in November 2023. This candidacy is said to be supported by a group led by Michihito Matsuda [121]

In the 2024 United Kingdom general election, a businessman named Steve Endacott ran for the constituency of Brighton Pavilion as an AI avatar named "AI Steve",[122] saying that constituents could interact with AI Steve to shape policy. Endacott stated that he would only attend Parliament to vote based on policies which had garnered at least 50% support.[123] AI Steve placed last with 179 votes.[124]

Management of infection

[edit]
See also: Digital contact tracing, Disease surveillance, and COVID-19 apps
A schematic of app-based COVID-19 contact tracing[125]

In February 2020, China launched a mobile app to deal with the Coronavirus outbreak[126] called "close-contact-detector".[127] Users are asked to enter their name and ID number. The app is able to detect "close contact" using surveillance data (i.e. using public transport records, including trains and flights)[127] and therefore a potential risk of infection. Every user can also check the status of three other users. To make this inquiry users scan a Quick Response (QR) code on their smartphones using apps like Alipay or WeChat.[128] The close contact detector can be accessed via popular mobile apps including Alipay. If a potential risk is detected, the app not only recommends self-quarantine, it also alerts local health officials.[129]

Alipay also has the Alipay Health Code which is used to keep citizens safe. This system generates a QR code in one of three colors (green, yellow, or red) after users fill in a form on Alipay with personal details. A green code enables the holder to move around unrestricted. A yellow code requires the user to stay at home for seven days and red means a two-week quarantine. In some cities such as Hangzhou, it has become nearly impossible to get around without showing one's Alipay code.[130]

In Cannes, France, monitoring software has been used on footage shot by CCTV cameras, allowing to monitor their compliance to local social distancing and mask wearing during the COVID-19 pandemic. The system does not store identifying data, but rather allows to alert city authorities and police where breaches of the mask and mask wearing rules are spotted (allowing fining to be carried out where needed). The algorithms used by the monitoring software can be incorporated into existing surveillance systems in public spaces (hospitals, stations, airports, shopping centres, ...) [131]

Cellphone data is used to locate infected patients in South Korea, Taiwan, Singapore and other countries.[132][133] In March 2020, the Israeli government enabled security agencies to track mobile phone data of people supposed to have coronavirus. The measure was taken to enforce quarantine and protect those who may come into contact with infected citizens.[134] Also in March 2020, Deutsche Telekom shared private cellphone data with the federal government agency, Robert Koch Institute, in order to research and prevent the spread of the virus.[135] Russia deployed facial recognition technology to detect quarantine breakers.[136] Italian regional health commissioner Giulio Gallera said that "40% of people are continuing to move around anyway", as he has been informed by mobile phone operators.[137] In USA, Europe and UK, Palantir Technologies is taken in charge to provide COVID-19 tracking services.[138]

Prevention and management of environmental disasters

[edit]
See also: Early warning system

Tsunamis can be detected by Tsunami warning systems. They can make use of AI.[139][140] Floodings can also be detected using AI systems.[141] Wildfires can be predicted using AI systems.[142][143] Wildfire detection is possible by AI systems (i.e. through satellite data, aerial imagery, and GPS phone personnel position) and can help in the evacuation of people during wildfires,[144] to investigate how householders responded in wildfires[145] and spotting wildfire in real time using computer vision.[146][147] Earthquake detection systems are now improving alongside the development of AI technology through measuring seismic data and implementing complex algorithms to improve detection and prediction rates.[148][149][150] Earthquake monitoring, phase picking, and seismic signal detection have developed through AI algorithms of deep-learning, analysis, and computational models.[151] Locust breeding areas can be approximated using machine learning, which could help to stop locust swarms in an early phase.[152]

Reception

[edit]

Benefits

[edit]
See also: Techno-progressivism

Algorithmic regulation is supposed to be a system of governance where more exact data, collected from citizens via their smart devices and computers, is used to more efficiently organize human life as a collective.[153][154] As Deloitte estimated in 2017, automation of US government work could save 96.7 million federal hours annually, with a potential savings of $3.3 billion; at the high end, this rises to 1.2 billion hours and potential annual savings of $41.1 billion.[155]

Criticism

[edit]

There are potential risks associated with the use of algorithms in government. Those include algorithms becoming susceptible to bias,[156] a lack of transparency in how an algorithm may make decisions,[157] and the accountability for any such decisions.[157] According to a 2016's book Weapons of Math Destruction, algorithms and big data are suspected to increase inequality due to opacity, scale and damage.[158]

There is also a serious concern that gaming by the regulated parties might occur, once more transparency is brought into the decision making by algorithmic governance, regulated parties might try to manipulate their outcome in own favor and even use adversarial machine learning.[1][19] According to Harari, the conflict between democracy and dictatorship is seen as a conflict of two different data-processing systems—AI and algorithms may swing the advantage toward the latter by processing enormous amounts of information centrally.[159]

In 2018, the Netherlands employed an algorithmic system SyRI (Systeem Risico Indicatie) to detect citizens perceived being high risk for committing welfare fraud, which quietly flagged thousands of people to investigators.[160] This caused a public protest. The district court of Hague shut down SyRI referencing Article 8 of the European Convention on Human Rights (ECHR).[161]

The contributors of the 2019 documentary iHuman expressed apprehension of "infinitely stable dictatorships" created by government AI.[162]

Due to public criticism, the Australian government announced the suspension of Robodebt scheme key functions in 2019, and a review of all debts raised using the programme.[163]

In 2020, algorithms assigning exam grades to students in the UK sparked open protest under the banner "Fuck the algorithm."[104] This protest was successful and the grades were taken back.[164]

In 2020, the US government software ATLAS, which run on Amazon Cloud, sparked uproar from activists and Amazon's own employees.[165]

In 2021, Eticas Foundation has launched a database of governmental algorithms called Observatory of Algorithms with Social Impact (OASI).[166]

Algorithmic bias and transparency

[edit]
Main article: Algorithmic bias

An initial approach towards transparency included the open-sourcing of algorithms.[167] Software code can be looked into and improvements can be proposed through source-code-hosting facilities.

Public acceptance

[edit]

A 2019 poll conducted by IE University's Center for the Governance of Change in Spain found that 25% of citizens from selected European countries were somewhat or totally in favor of letting an artificial intelligence make important decisions about how their country is run.[168] The following table lists the results by country:

Country Percentage
France 25%
Germany 31%
Ireland 29%
Italy 28%
Netherlands 43%
Portugal 19%
Spain 26%
UK 31%

Researchers found some evidence that when citizens perceive their political leaders or security providers to be untrustworthy, disappointing, or immoral, they prefer to replace them by artificial agents, whom they consider to be more reliable.[169] The evidence is established by survey experiments on university students of all genders.

A 2021 poll by IE University indicates that 51% of Europeans are in favor of reducing the number of national parliamentarians and reallocating these seats to an algorithm. This proposal has garnered substantial support in Spain (66%), Italy (59%), and Estonia (56%). Conversely, the citizens of Germany, the Netherlands, the United Kingdom, and Sweden largely oppose the idea.[170] The survey results exhibit significant generational differences. Over 60% of Europeans aged 25-34 and 56% of those aged 34-44 support the measure, while a majority of respondents over the age of 55 are against it. International perspectives also vary: 75% of Chinese respondents support the proposal, whereas 60% of Americans are opposed.[170]

[edit]

The novels Daemon and Freedom™ by Daniel Suarez describe a fictional scenario of global algorithmic regulation.[171] Matthew De Abaitua's If Then imagines an algorithm supposedly based on "fairness" recreating a premodern rural economy.[172]

See also

[edit]

Citations

[edit]
  1. ^ a b c d e "Government by Algorithm: A Review and an Agenda". Stanford Law School. Retrieved 20 March 2020.
  2. ^ a b Medina, Eden (2015). "Rethinking algorithmic regulation" (PDF). Kybernetes. 44 (6/7): 1005–1019. doi:10.1108/K-02-2015-0052.
  3. ^ Engin, Zeynep; Treleaven, Philip (March 2019). "Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies". The Computer Journal. 62 (3): 448–460. doi:10.1093/comjnl/bxy082.
  4. ^ Danaher, John (1 September 2016). "The Threat of Algocracy: Reality, Resistance and Accommodation". Philosophy & Technology. 29 (3): 245–268. doi:10.1007/s13347-015-0211-1. ISSN 2210-5441. S2CID 146674621. Retrieved 26 January 2022.
  5. ^ Yeung, Karen (December 2018). "Algorithmic regulation: A critical interrogation". Regulation & Governance. 12 (4): 505–523. doi:10.1111/rego.12158. S2CID 157086008.
  6. ^ Katzenbach, Christian; Ulbricht, Lena (29 November 2019). "Algorithmic governance". Internet Policy Review. 8 (4). doi:10.14763/2019.4.1424. hdl:10419/210652. ISSN 2197-6775. Retrieved 19 March 2020.
  7. ^ Abril, Rubén Rodríguez. "DERECOM. Derecho de la Comunicación. - An approach to the algorithmic legal order and to its civil, trade and financial projection". www.derecom.com (in European Spanish). Retrieved 20 May 2020.
  8. ^ "Rule by Algorithm? Big Data and the Threat of Algocracy". ieet.org. Retrieved 20 May 2020.
  9. ^ a b Werbach, Kevin (24 September 2018), The Siren Song: Algorithmic Governance By Blockchain, Social Science Research Network, SSRN 3578610.
  10. ^ Williamson, Ben (January 2013). "Decoding identity: Reprogramming pedagogic identities through algorithmic governance". British Educational Research Association Conference. Archived from the original on 24 June 2021. Retrieved 26 December 2020.
  11. ^ Hildebrandt, Mireille (6 August 2018). "Algorithmic regulation and the rule of law". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 376 (2128): 20170355. Bibcode:2018RSPTA.37670355H. doi:10.1098/rsta.2017.0355. hdl:2066/200765. PMID 30082301.
  12. ^ Lumineau, Fabrice; Wang, Wenqian; Schilke, Oliver (1 March 2021). "Blockchain Governance—A New Way of Organizing Collaborations?". Organization Science. 32 (2): 500–521. doi:10.1287/orsc.2020.1379. ISSN 1047-7039. S2CID 225123270.
  13. ^ Veale, Michael; Brass, Irina (2019). "Administration by Algorithm? Public Management Meets Public Sector Machine Learning". Social Science Research Network. SSRN 3375391.
  14. ^ David Ronfeldt (1991). "Cyberocracy, Cyberspace, and Cyberology:Political Effects of the Information Revolution" (PDF). RAND Corporation. Retrieved 12 Dec 2014.
  15. ^ David Ronfeldt (1992). "Cyberocracy is Coming" (PDF). RAND Corporation. Retrieved 12 Dec 2014.
  16. ^ Ronfeldt, David; Varda, Danielle (1 December 2008), The Prospects for Cyberocracy (Revisited), Social Science Research Network, SSRN 1325809.
  17. ^ Shah, Bimal Pratap (July 4, 2019). "Transparency in governance, through cyberocracy". The Kathmandu Post. Retrieved 25 April 2020.
  18. ^ Hudson, Alex (28 August 2019). "'Far more than surveillance' is happening and could change how government is run". Metro. Retrieved 25 April 2020.
  19. ^ a b c d Cristianini, Nello; Scantamburlo, Teresa (8 October 2019). "On social machines for algorithmic regulation". AI & Society. 35 (3): 645–662. arXiv:1904.13316. Bibcode:2019arXiv190413316C. doi:10.1007/s00146-019-00917-8. ISSN 1435-5655. S2CID 140233845.
  20. ^ "Organisations: Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute): Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow, Russia". www.mathnet.ru. Retrieved 24 March 2021.
  21. ^ "Machine of communism. Why the USSR did not create the Internet". csef.ru (in Russian). Retrieved 21 March 2020.
  22. ^ Kharkevich, Aleksandr Aleksandrovich (1973). Theory of information. The identification of the images. Selected works in three volumes. Volume 3. Information and technology: Moscow: Publishing House "Nauka", 1973. - Academy of Sciences of the USSR. Institute of information transmission problems. pp. 495–508.
  23. ^ a b Gerovitch, Slava (9 April 2015). "How the Computer Got Its Revenge on the Soviet Union". Nautilus. Archived from the original on 22 September 2021. Retrieved 19 September 2021.
  24. ^ "IU professor analyzes Chile's 'Project Cybersyn'". UI News Room. Archived from the original on 10 September 2009. Retrieved 27 May 2013.
  25. ^ Medina, Eden (1 January 2015). "Rethinking algorithmic regulation". Kybernetes. 44 (6/7): 1005–1019. doi:10.1108/K-02-2015-0052.
  26. ^ Freeman Engstrom, David; Ho, Daniel E.; Sharkey, Catherine M.; Cuéllar, Mariano-Florentino (2020). "Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies" (PDF). Archived from the original (PDF) on 2022-08-15. Retrieved 2020-03-26.
  27. ^ Margretts, Helen (1999). Information technology in government : Britain and America. New York: Routledge. ISBN 9780203208038.
  28. ^ McCarty, L. Thorne. Reflections on" Taxman: An Experiment in Artificial Intelligence and Legal Reasoning. Harvard Law Review (1977): 837–893.
  29. ^ Stamper, Ronald K. The LEGOL 1 prototype system and language. The Computer Journal 20.2 (1977): 102-108.
  30. ^ Cockshott, W. Paul (1993). Towards a new socialism. Nottingham, England: Spokesman. ISBN 978-0851245454.
  31. ^ Kirby, Michael (1998). "The Future of Courts - Do They Have One". Journal of Law and Information Science. 9: 141. Retrieved 12 April 2020.
  32. ^ Lawrence, Lessig (2006). Code (Version 2.0 ed.). Basic Books. ISBN 978-0-465-03914-2.
  33. ^ Sodemann, Angela A.; Ross, Matthew P.; Borghetti, Brett J. (November 2012). "A Review of Anomaly Detection in Automated Surveillance". IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews. 42 (6): 1257–1272. doi:10.1109/TSMCC.2012.2215319. S2CID 15466712.
  34. ^ Kelty, Christopher (2009). "Explaining IT". Political and Legal Anthropology Review. 32 (1): 156–160. doi:10.1111/j.1555-2934.2009.01035.x. ISSN 1081-6976. JSTOR 24497537. Retrieved 26 January 2022.
  35. ^ Danaher, John (September 2016). "The Threat of Algocracy: Reality, Resistance and Accommodation". Philosophy & Technology. 29 (3): 245–268. doi:10.1007/s13347-015-0211-1. S2CID 146674621.
  36. ^ Aneesh, A. (2006). Virtual Migration: the Programming of Globalization. Duke University Press. ISBN 978-0-8223-3669-3.
  37. ^ a b c O’Reilly, Tim (2013). "Open Data and Algorithmic Regulation". In Goldstein, B.; Dyson, L. (eds.). Beyond Transparency: open Data and the Future of Civic Innovation. San Francisco: Code for America Press. pp. 289–300.
  38. ^ a b c Chavez-Dreyfuss, Gertrude (17 April 2017). "Ukraine launches big blockchain deal with tech firm Bitfury". Reuters. Retrieved 15 August 2021.
  39. ^ "Data for Policy 2017". Data for Policy CIC. Retrieved 23 January 2021.
  40. ^ Brauneis, Robert; Goodman, Ellen P. (1 January 2018). "Algorithmic Transparency for the Smart City". Yale Journal of Law & Technology. 20 (1): 103. Archived from the original on 15 August 2022. Retrieved 20 September 2020.
  41. ^ Singh, Saurabh; Sharma, Pradip Kumar; Yoon, Byungun; Shojafar, Mohammad; Cho, Gi Hwan; Ra, In-Ho (1 December 2020). "Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city". Sustainable Cities and Society. 63: 102364. doi:10.1016/j.scs.2020.102364. ISSN 2210-6707. S2CID 225022879. Retrieved 24 March 2021.
  42. ^ Gardner, Allison. "Don't write off government algorithms – responsible AI can produce real benefits". The Conversation. Retrieved 1 April 2021.
  43. ^ Morrow, Garrett (2022). The Robot in City Hall: The Limitations, Structure, and Governance of Smart City Technology Regimes (PDF) – via ProQuest.
  44. ^ a b c "Nevada smart city: A millionaire's plan to create a local government". BBC News. 18 March 2021. Retrieved 24 March 2021.
  45. ^ Independent, Daniel Rothberg | The Nevada. "Blockchains, Inc. withdraws 'Innovation Zone' plan for Storey County". www.nnbw.com. Retrieved 2022-11-07.
  46. ^ a b c "Months before a company lobbied the Legislature to create its own county, it purchased faraway water rights that could fuel future growth". The Nevada Independent. 12 February 2021. Retrieved 2022-11-07.
  47. ^ "Saudi Arabia is planning a 100-mile line of car-free smart communities". Engadget. Retrieved 18 May 2022.
  48. ^ "XVI". Cybernetic and Management. English Universities Press. 1959.
  49. ^ Beer, Stafford (1975). Platform for change : a message from Stafford Beer. J. Wiley. ISBN 978-0471948407.
  50. ^ "China's social credit score – untangling myth from reality | Merics". merics.org. 11 February 2022. Retrieved 2022-08-10.
  51. ^ Daum, Jeremy (8 October 2021). "Far From a Panopticon, Social Credit Focuses on Legal Violations". China Brief. 21 (19). Retrieved 10 October 2021.
  52. ^ "China's Social Credit System: Speculation vs. Reality". The Diplomat. Archived from the original on 30 March 2021.
  53. ^ Bindra, Jaspreet (30 March 2018). "Transforming India through blockchain". Livemint. Retrieved 31 May 2020.
  54. ^ Finn, Ed (10 April 2017). "Do digital currencies spell the end of capitalism?". The Guardian. Retrieved 31 May 2020.
  55. ^ Reiff, Nathan. "Blockchain Explained". Investopedia. Retrieved 31 May 2020.
  56. ^ Szabo, Nick (1997). "View of Formalizing and Securing Relationships on Public Networks". First Monday. doi:10.5210/fm.v2i9.548. S2CID 33773111. Archived from the original on 2022-04-10. Retrieved 2020-05-31.
  57. ^ Fries, Martin; P. Paal, Boris (2019). Smart Contracts (in German). Mohr Siebeck. ISBN 978-3-16-156911-1. JSTOR j.ctvn96h9r.
  58. ^ "What is DAO - Decentralized Autonomous Organizations". BlockchainHub. Archived from the original on 24 May 2020. Retrieved 31 May 2020.
  59. ^ Prusty, Narayan (27 Apr 2017). Building Blockchain Projects. Birmingham, UK: Packt. p. 9. ISBN 9781787125339.
  60. ^ Chohan, Usman W. (4 December 2017), The Decentralized Autonomous Organization and Governance Issues, Social Science Research Network, SSRN 3082055.
  61. ^ Oranburg, Seth; Palagashvili, Liya (October 22, 2018). "The Gig Economy, Smart Contracts, and Disruption of Traditional Work Arrangements". doi:10.2139/ssrn.3270867. SSRN 3270867 – via Social Science Research Network.
  62. ^ "A Blockchain-Based Decentralized System for Proper Handling of Temporary Employment Contracts".
  63. ^ How blockchain technology could change our lives
  64. ^ Official, Illuminates (September 11, 2019). "Business inheritance in blockchain".
  65. ^ "Blockchain and AI are coming to kill these 4 business verticals".
  66. ^ "Silent Notary - Blockchain Notary Service 100% events falsification protection". silentnotary.com.
  67. ^ "The Bitfury Group and Government of Republic of Georgia Expand Blockchain Pilot" (PDF).
  68. ^ A BLOCKCHAIN - Journals Gateway
  69. ^ "Digital Transformation: Blockchain and Land Titles" (PDF).
  70. ^ "Leaked Palantir Doc Reveals Uses, Specific Functions And Key Clients". TechCrunch. Retrieved 22 April 2020.
  71. ^ Winston, Ali (27 February 2018). "Palantir has secretly been using New Orleans to test its predictive policing technology". The Verge. Retrieved 23 April 2020.
  72. ^ Haskins, Caroline (July 12, 2019). "300 Californian Cities Secretly Have Access to Palantir".
  73. ^ Senator, Ted E.; Wong, Raphael W.H.; Marrone, Michael P.; Llamas, Winston M.; Klinger, Christina D.; Khan, A.F. Umar; Cottini, Matthew A.; Goldberg, Henry G.; Wooton, Jerry. "The FinCEN Artificial Intelligence System: Identifying Potential Money Laundering from Reports of Large Cash Transactions". AAAI. Retrieved 10 September 2022.
  74. ^ Goldberg, H. G.; Senator, T. E. (1998). "The FinCEN AI System: Finding Financial Crimes in a Large Database of Cash Transactions". Agent Technology: Foundations, Applications, and Markets. Springer. pp. 283–302. doi:10.1007/978-3-662-03678-5_15. ISBN 978-3-642-08344-0.
  75. ^ "Press corner". European Commission - European Commission.
  76. ^ Biddle, Sam; Saleh, Maryam (August 25, 2021). "Little-Known Federal Software Can Trigger Revocation of Citizenship". The Intercept. Retrieved 21 September 2021.
  77. ^ "Cuccinelli Announces USCIS' FY 2019 Accomplishments and Efforts to Implement President Trump's Goals". USCIS. 16 October 2019. Retrieved 21 September 2021.
  78. ^ a b Szalavitz 2021, p. 41.
  79. ^ Szalavitz 2021, p. 40.
  80. ^ Romo, Vanessa (2018-05-08). "Walmart Will Implement New Opioid Prescription Limits By End Of Summer". NPR. Retrieved 2021-10-06.
  81. ^ Oliva 2020, p. 847.
  82. ^ Oliva 2020, p. 848.
  83. ^ See section on smart contracts; this is possible by means of a digital birth certificate, triggering a smart contract
  84. ^ "Exclusive: Estonia's vision for an 'invisible government'". March 20, 2019.
  85. ^ "Enhancing the use of competitive tendering in Costa Rica's Public Procurement System" (PDF).
  86. ^ "Procurement at Forestry Commission". GOV.UK.
  87. ^ "Best Government Audit Software - 2023 Reviews & Comparison". sourceforge.net.
  88. ^ Audit app: an effective tool for government procurement assurance
  89. ^ "Track your driving licence application". GOV.UK.
  90. ^ "Track progress of a reported road fault or issue | nidirect". www.nidirect.gov.uk. May 18, 2018.
  91. ^ "Senate Tracker Help – The Florida Senate". flsenate.gov. Retrieved 2021-01-17.
  92. ^ "Legislative Search Results". congress.gov. Retrieved 2021-01-17.
  93. ^ "GovTrack.us: Tracking the U.S. Congress". govtrack.us. Retrieved 2021-01-17.
  94. ^ Stranieri, Andrew; Zeleznikow, John (2 December 1995). "Levels of reasoning as the basis for a formalisation of argumentation". Proceedings of the fourth international conference on Information and knowledge management - CIKM '95. Association for Computing Machinery. pp. 333–339. doi:10.1145/221270.221608. ISBN 0897918126. S2CID 12179742. Retrieved 5 February 2022.
  95. ^ Sam Corbett-Davies; Emma Pierson; Avi Feller; Sharad Goel (October 17, 2016). "A computer program used for bail and sentencing decisions was labeled biased against blacks. It's actually not that clear". The Washington Post. Retrieved January 1, 2018.
  96. ^ Aaron M. Bornstein (December 21, 2017). "Are Algorithms Building the New Infrastructure of Racism?". Nautilus. No. 55. Archived from the original on January 3, 2018. Retrieved January 2, 2018.
  97. ^ a b "Beijing Internet Court launches online litigation service center". english.bjinternetcourt.gov.cn. Retrieved 13 April 2020.
  98. ^ "China Now Has AI-Powered Judges". RADII | Culture, Innovation, and Life in today's China. 16 August 2019. Retrieved 13 April 2020.
  99. ^ Fish, Tom (6 December 2019). "AI shock: China unveils 'cyber court' complete with AI judges and verdicts via chat app". Express.co.uk. Retrieved 13 April 2020.
  100. ^ "Can AI Be a Fair Judge in Court? Estonia Thinks So". Wired. Retrieved 13 April 2020.
  101. ^ "ROSS Intelligence Lands Another Law Firm Client." The American Lawyer. N.p., n.d. Web. 16 June 2017. <http://www.americanlawyer.com/id=1202769384977/ROSS-Intelligence-Lands-Another-Law-Firm-Client>.
  102. ^ CodeX Techindex. Stanford Law School, n.d. Web. 16 June 2017. <https://techindex.law.stanford.edu/ Archived 2022-03-31 at the Wayback Machine>.
  103. ^ Broussard, Meredith (8 September 2020). "Opinion | When Algorithms Give Real Students Imaginary Grades". The New York Times.
  104. ^ a b "Skewed Grading Algorithms Fuel Backlash Beyond the Classroom". Wired. Retrieved 26 September 2020.
  105. ^ Smith, Craig S. (December 18, 2019). "The Machines Are Learning, and So Are the Students". The New York Times – via NYTimes.com.
  106. ^ "Could Artificial Intelligence Replace Our Teachers? | Education World".
  107. ^ Leopold, Todd. "A professor built an AI teaching assistant for his courses — and it could shape the future of education". Business Insider.
  108. ^ Robot, Roybi (September 23, 2018). "The Future of Homeschooling: How Robots are Changing In-Home Education".
  109. ^ Matsuda, Michihito (14 July 2018). "POLITICS 2028: WHY ARTIFICIAL INTELLIGENCE WILL REPLACE POLITICIANS". SlideShare. Retrieved 22 September 2019.
  110. ^ Johnston, Lachlan (12 April 2018). "There's an AI Running for the Mayoral Role of Tama City, Tokyo". OTAQUEST. Archived from the original on 5 December 2021. Retrieved 22 September 2019.
  111. ^ "AI党 | 多摩市議会議員選挙2019". AI党 | 多摩市議会議員選挙2019.
  112. ^ "Werden Bots die besseren Politiker?". Politik & Kommunikation (in German). Retrieved 31 October 2020.
  113. ^ O'Leary, Abigail; Verdon, Anna (April 17, 2018). "Robot to run for mayor in Japan promising 'fairness and balance' for all". mirror.
  114. ^ Perez, Oren (31 January 2020). "Collaborative е-Rulemaking, Democratic Bots, and the Future of Digital Democracy". Digital Government: Research and Practice. 1 (1): 1–13. doi:10.1145/3352463. ISSN 2691-199X. S2CID 211519367.
  115. ^ Sarmah, Harshajit (28 January 2019). "World's First AI-powered Virtual Politician SAM Joins The Electoral Race In New Zealand". Analytics India Magazine. Retrieved 11 April 2020.
  116. ^ "Meet SAM, world's first AI politician that hopes to run for New Zealand election in 2020". Hindustan Times. 26 November 2017. Archived from the original on November 26, 2017. Retrieved 11 April 2020.
  117. ^ Sternberg, Sarah (20 June 2022). "Danskere vil ind på den politiske scene med kunstig intelligens" [Danes want to enter the political scene with artificial intelligence]. Jyllands-Posten. Retrieved 2022-06-20.
  118. ^ Diwakar, Amar (2022-08-22). "Can an AI-led Danish party usher in an age of algorithmic politics?". TRT World. Retrieved 2022-08-22.
  119. ^ Xiang, Chloe (13 October 2022). "This Danish Political Party Is Led by an AI". Vice: Motherboard. Retrieved 2022-10-13.
  120. ^ Hearing, Alice (14 October 2022). "A.I. chatbot is leading a Danish political party and setting its policies. Now users are grilling it for its stance on political landmines". Fortune.
  121. ^ "Danskere vil ind den politiske scene med kunstig intelligens" [AI Mayer run to the election in Manazuru Town]. Tokyo Sports. 2023-11-07. Retrieved 2023-11-25.
  122. ^ Grierson, Jamie (2024-06-10). "Brighton general election candidate aims to be UK's first 'AI MP'". The Guardian. ISSN 0261-3077. Retrieved 2024-06-15.
  123. ^ "Meet AI Steve, the avatar standing as a candidate in the UK election". euronews. 2024-06-13. Retrieved 2024-06-15.
  124. ^ "Results - General Election 4 July 2024". Brighton & Hove City Council. Retrieved 8 July 2024.
  125. ^ Ferretti, Luca; Wymant, Chris; Kendall, Michelle; Zhao, Lele; Nurtay, Anel; Abeler-Dörner, Lucie; Parker, Michael; Bonsall, David; Fraser, Christophe (8 May 2020). "Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing". Science. 368 (6491): eabb6936. doi:10.1126/science.abb6936. ISSN 0036-8075. PMC 7164555. PMID 32234805.
  126. ^ "China launches coronavirus 'close contact' app". BBC News. 11 February 2020. Retrieved 7 March 2020.
  127. ^ a b "China launches coronavirus 'close contact detector' platform". South China Morning Post. February 12, 2020.
  128. ^ "China launches coronavirus 'close contact detector' app". BBC News. February 11, 2020.
  129. ^ Chen, Angela. "China's coronavirus app could have unintended consequences". MIT Technology Review. Retrieved 7 March 2020.
  130. ^ Mozur, Paul; Zhong, Raymond; Krolik, Aaron (March 2, 2020). "In Coronavirus Fight, China Gives Citizens a Color Code, With Red Flags". The New York Times.
  131. ^ "Coronavirus France: Cameras to monitor masks and social distancing". BBC News. May 4, 2020.
  132. ^ Manancourt, Vincent (10 March 2020). "Coronavirus tests Europe's resolve on privacy". POLITICO. Retrieved 20 March 2020.
  133. ^ Ivan Watson; Sophie Jeong (28 February 2020). "Coronavirus mobile apps are surging in popularity in South Korea". CNN.
  134. ^ Tidy, Joe (17 March 2020). "Coronavirus: Israel enables emergency spy powers". BBC News. Retrieved 18 March 2020.
  135. ^ Paksoy, Yunus. "German telecom giant shares private data with government amid privacy fears". trtworld. Retrieved 20 March 2020.
  136. ^ "Moscow deploys facial recognition technology for coronavirus quarantine". Reuters. 21 February 2020. Retrieved 20 March 2020.
  137. ^ "Italians scolded for flouting lockdown as death toll nears 3,000". Pittsburgh Post-Gazette. Retrieved 20 March 2020.
  138. ^ "Palantir provides COVID-19 tracking software to CDC and NHS, pitches European health agencies". TechCrunch. Retrieved 22 April 2020.
  139. ^ Osumi, Magdalena (August 16, 2019). "How AI will help us better understand tsunami risks". www.preventionweb.net.
  140. ^ "Artificially Intelligent Tsunami Early Warning System".
  141. ^ "How Artificial Intelligence Could Help Fight Climate Change-Driven Wildfires and Save Lives". Fortune.
  142. ^ Sayad, Younes Oulad; Mousannif, Hajar; Al Moatassime, Hassan (March 1, 2019). "Predictive modeling of wildfires: A new dataset and machine learning approach". Fire Safety Journal. 104: 130–146. doi:10.1016/j.firesaf.2019.01.006. S2CID 116032143.
  143. ^ "Artificial intelligence for forest fire prediction".
  144. ^ Zhao, Xilei; Lovreglio, Ruggiero; Kuligowski, Erica; Nilsson, Daniel (April 15, 2020). "Using Artificial Intelligence for Safe and Effective Wildfire Evacuations". Fire Technology. 57 (2): 483–485. doi:10.1007/s10694-020-00979-x. S2CID 218801709.
  145. ^ Zhao, Xilei; Xu, Yiming; Lovreglio, Ruggiero; Kuligowski, Erica; Nilsson, Daniel; Cova, Thomas J.; Wu, Alex; Yan, Xiang (2022-06-01). "Estimating wildfire evacuation decision and departure timing using large-scale GPS data". Transportation Research Part D: Transport and Environment. 107: 103277. arXiv:2109.07745. doi:10.1016/j.trd.2022.103277. ISSN 1361-9209.
  146. ^ Rachel Metz (5 December 2019). "How AI is helping spot wildfires faster". CNN. Video by John General.
  147. ^ Holley, Peter. "California has 33 million acres of forest. This company is training artificial intelligence to scour it all for wildfire". The Washington Post.
  148. ^ Mousavi, S. Mostafa; Sheng, Yixiao; Zhu, Weiqiang; Beroza, Gregory C. (2019). "STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI". IEEE Access. 7: 179464–179476. Bibcode:2019IEEEA...7q9464M. doi:10.1109/ACCESS.2019.2947848. ISSN 2169-3536. S2CID 208111095.
  149. ^ Banna, Md. Hasan Al; Taher, Kazi Abu; Kaiser, M. Shamim; Mahmud, Mufti; Rahman, Md. Sazzadur; Hosen, A. S. M. Sanwar; Cho, Gi Hwan (2020). "Application of Artificial Intelligence in Predicting Earthquakes: State-of-the-Art and Future Challenges". IEEE Access. 8: 192880–192923. Bibcode:2020IEEEA...8s2880B. doi:10.1109/ACCESS.2020.3029859. ISSN 2169-3536. S2CID 226292959.
  150. ^ "How Location Intelligence Can Help Protect Lives During Disasters". EHS Daily Advisor. 2022-02-09. Retrieved 2024-01-23.
  151. ^ Mousavi, S. Mostafa; Ellsworth, William L.; Zhu, Weiqiang; Chuang, Lindsay Y.; Beroza, Gregory C. (2020-08-07). "Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking". Nature Communications. 11 (1): 3952. Bibcode:2020NatCo..11.3952M. doi:10.1038/s41467-020-17591-w. ISSN 2041-1723. PMC 7415159. PMID 32770023.
  152. ^ Gómez, Diego; Salvador, Pablo; Sanz, Julia; Casanova, Carlos; Taratiel, Daniel; Casanova, Jose Luis (August 15, 2018). "Machine learning approach to locate desert locust breeding areas based on ESA CCI soil moisture". Journal of Applied Remote Sensing. 12 (3). 036011. Bibcode:2018JARS...12c6011G. doi:10.1117/1.JRS.12.036011. S2CID 52230139.
  153. ^ McCormick, Tim (15 February 2014). "A brief exchange with Tim O'Reilly about "algorithmic regulation" | Tim McCormick". Retrieved 2 June 2020.
  154. ^ "Why the internet of things could destroy the welfare state". The Guardian. 19 July 2014. Retrieved 2 June 2020.
  155. ^ Eggers, illiam D.; Schatsky, David; Viechnick, Peter. "Demystifying artificial intelligence in government". Deloitte Insights. Retrieved 4 April 2020.
  156. ^ Mehr, Hila (August 2017). "Artificial Intelligence for Citizen Services and Government" (PDF). ash.harvard.edu. Retrieved 2018-12-31.
  157. ^ a b Capgemini Consulting (2017). "Unleashing the potential of Artificial Intelligence in the Public Sector" (PDF). www.capgemini.com. Retrieved 2018-12-31.
  158. ^ Verma, Shikha (June 2019). "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy". Vikalpa: The Journal for Decision Makers. 44 (2): 97–98. doi:10.1177/0256090919853933. ISSN 0256-0909. S2CID 198779932.
  159. ^ Harari, Story by Yuval Noah. "Why Technology Favors Tyranny". The Atlantic. Retrieved 11 April 2020.
  160. ^ "Europe Limits Government by Algorithm. The US, Not So Much". Wired. Retrieved 11 April 2020.
  161. ^ Rechtbank Den Haag 5 February 2020, C-09-550982-HA ZA 18-388 (English), ECLI:NL:RBDHA:2020:1878
  162. ^ Wilkinson, Amber. "'iHuman': IDFA Review". Screen. Retrieved 21 April 2020.
  163. ^ Rinta-Kahila, Tapani; Someh, Ida; Gillespie, Nicole; Indulska, Marta; Gregor, Shirley (4 May 2022). "Algorithmic decision-making and system destructiveness: A case of automatic debt recovery". European Journal of Information Systems. 31 (3): 313–338. doi:10.1080/0960085X.2021.1960905. hdl:1885/294609. S2CID 239735326.
  164. ^ Reuter, Markus (17 August 2020). "Fuck the Algorithm - Jugendproteste in Großbritannien gegen maschinelle Notenvergabe erfolgreich". netzpolitik.org (in German). Retrieved 3 October 2020.
  165. ^ "U.S. Government Is Using an Algorithm to Flag American Citizens for Denaturalization: Report". Gizmodo. Retrieved 21 September 2021.
  166. ^ "OASI, the first search engine to find the algorithms that governments and companies use on citizens" (Press release). Retrieved 16 October 2021.
  167. ^ Heald, David (2006-09-07). Transparency: The Key to Better Governance?. British Academy. doi:10.5871/bacad/9780197263839.003.0002. ISBN 978-0-19-726383-9.
  168. ^ "European Tech Insights (2019) | IE CGC" (PDF). Center for the Governance of Change. Retrieved 11 April 2020.
  169. ^ Spatola, Nicolas; Macdorman, Karl F. (11 July 2021). "Why Real Citizens Would Turn to Artificial Leaders". Digital Government: Research and Practice. 2 (3): 26:1–26:24. doi:10.1145/3447954. hdl:1805/30988. ISSN 2691-199X.
  170. ^ a b "EUROPEAN TECH INSIGHTS 2021" (PDF). IE University. 2021. Retrieved 29 June 2024.
  171. ^ Rieger, Frank. "Understanding the Daemon". FAZ.NET (in German). Retrieved 5 April 2020.
  172. ^ Stainforth, Elizabeth and Jo Lindsay Walton. "Computing Utopia: The Horizons of Computational Economies in History and Science Fiction." Science Fiction Studies, vol. 46 no. 3, 2019, p. 471-489. Project MUSE, doi:10.1353/sfs.2019.0084.

General and cited references

[edit]
[edit]
Look up algocracy in Wiktionary, the free dictionary.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Government_by_algorithm&oldid=1233285745"