{"id":34402,"date":"2018-11-13T18:28:35","date_gmt":"2018-11-13T23:28:35","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/operation-love-serenade-fighting-corruption-in-brazil-with-an-open-source-machine-learning-powered-robot\/"},"modified":"2018-11-13T18:28:35","modified_gmt":"2018-11-13T23:28:35","slug":"operation-love-serenade-fighting-corruption-in-brazil-with-an-open-source-machine-learning-powered-robot","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/operation-love-serenade-fighting-corruption-in-brazil-with-an-open-source-machine-learning-powered-robot\/","title":{"rendered":"Operation Love Serenade: Fighting corruption in Brazil with an open-source, Machine Learning-powered robot"},"content":{"rendered":"

Uncommon affair for robots, common affair for politicians<\/b><\/h3>\n

The Toblerone Affair. <\/b>In 1995, the Swedish newspaper Expressen revealed that Mona Sahlin, who was then serving as Deputy Prime Minister, \u00a0had used her professional credit card for personal purchases, including grocery shopping. The case became known as \u201cThe Toblerone Affair\u201d due to the inclusion of the famed chocolate bars on her credit card statement. <\/span>[1]<\/p>\n

Serenata de Amor. <\/b>Toblerone bars are relatively expensive in Brazil, so most people resort to cheaper alternatives to satiate their cravings, such as the Serenata de Amor (Portuguese for \u201clove serenade\u201d) candy.<\/span><\/p>\n

\"\"<\/a><\/p>\n

Desire for chocolate is not the only similarity between Brazil and other countries, however. Brazilian politicians have also been involved in corruption scandals, albeit in a widespread scale rarely seen in most other countries. In 2016, motivated to fight corruption, tech-savvy citizens led by Irio Musskopf used crowdfunding to start a non-profit, open-source project that uses data science for the purpose of monitoring public spending in Brazil. Inspired by the Toblerone Affair, the project was named Operation Serenata de Amor and is maintained by a dedicated team of 10 people, alongside hundreds of volunteers. <\/span>[2]<\/p>\n

 <\/p>\n

Enter Rosie, an anti-corruption robot aimed at politicians<\/b><\/h3>\n

\"\"<\/a><\/p>\n

The \u201ccivic tech\u201d project gave birth to Rosie, an application powered by machine learning and trained to identify suspicious uses of public funds. Rosie analyzes every reimbursement claimed by members of the Congress in Brazil (who are each entitled to monthly expense as much as 46 times the minimum wage in Brazil). Subsequently, it automatically identifies potential irregularities and exposes the reasons for suspicion. <\/span>[3]<\/p>\n

How it works. <\/b>Technically, Rosie is an open-source, Github-hosted Python application that applies unsupervised learning algorithms to estimate a \u201cprobability of corruption\u201d for each reimbursement receipt submitted by politicians in Brazil. For instance, one of Rosie\u2019s functionalities is applying clustering algorithms to identify outliers among meal expense reimbursements. <\/span>[4] [5]<\/p>\n

The organization decided to use Machine Learning instead of traditional algorithms because of three key reasons: the necessity to analyze diverse and dynamic datasets adaptively, without the need to \u201chard code\u201d a tailored application for each task; the ability to extract the most important features from the data set (i.e., the variables more likely to suggest frauds); and the requirement to scale efficiently given the large size of the datasets. Besides, the team decided to make it open-source to be able to leverage the contributions of other citizens and make the technology available for use in other contexts.<\/span>[6] [7] [8] [9]<\/p>\n

Expanding the project: Twitter, Jarbas and Perfil Pol\u00edtico. <\/b>Since 2017, Rosie\u2019s suspicion results are posted regularly on Twitter (@RosieDaSerenata). The project was covered by more than 90 journalistic vehicles, including the most respected in Brazil. <\/span>[10] To amplify the project\u2019s impact in the medium term, the team developed new ways to use data to help citizens take action, such as Jarbas, a visualization tool that organizes the scattered public spending database into a searchable, organized dashboard. Another new service is Perfil Pol\u00edtico (Portuguese for \u201cpolitical profile\u201d), a platform for profiling and comparing candidates in Brazil\u2019s elections.<\/span><\/p>\n

 <\/p>\n

The challenge ahead: from data to actions<\/b><\/h3>\n

Despite its potential, Rosie has faced substantial barriers to its deployment. Only dozens of cases resulted in politicians giving money back to public accounts (out of thousands identified). A key challenge is that the Congress itself has to analyze the complaints but it may refuse to do so if the value is seen as \u201clow\u201d (which in some cases corresponds to a threshold of as much as US$ 20,000). Another hurdle for Rosie is that the Congress website has \u201ccaptchas\u201d to prevent massive downloads of its data sets, which hinders the scaling of a tool that is supposed to work without any human dependence. <\/span>[11]<\/p>\n

In order to overcome such obstacles, the Operation Serenata de Amor may consider focusing on three key areas. First, they should uncover and publicize a high-profile, clear-cut case of ill-intentioned reimbursement. This will increase the credibility of the project, attract media coverage and reduce the likelihood of future cases being ignored by the Congress. Secondly, it should go beyond Twitter (which is not very popular in Brazil) and amplify its presence in other social media channels to reach more people. Thirdly, they should be less centered on the <\/span>how<\/span><\/i> and more centered on the <\/span>what <\/span><\/i>and the <\/span>why<\/span><\/i>. The current messaging is complex and full of jargon, and should be simplified to reach a larger audience.<\/span><\/p>\n

Despite the undeniable progress since 2016, these challenges make it clear that open questions still remain and could determine the project\u2019s success in the future: How can the organization circumvent the mechanisms that are currently hindering Rosie\u2019s deployment? Does making it an open-source application facilitate the creation of barriers for its use? What are other potential applications of Rosie\u2019s algorithms, in the public realm and in other contexts? <\/span><\/p>\n

(799 words)<\/span><\/p>\n

 <\/p>\n

References:<\/b><\/p>\n

[1] Stephen Kinzer, \u201cThe Shame of a Swedish Shopper (a Morality Tale)\u201d, <\/span>New York Times, <\/span><\/i>November 14, 1995, https:\/\/www.nytimes.com\/1995\/11\/14\/world\/stockholm-journal-the-shame-of-a-swedish-shopper-a-morality-tale.html, accessed November 2018.<\/span><\/p>\n

[2] Opera\u00e7\u00e3o Serenata de Amor, \u201cAbout\u201d, https:\/\/serenata.ai\/en\/about\/, accessed November 2018.<\/span><\/p>\n

[3] Chamber of Deputies, \u201cParliamentary Activity Charge\u201d, http:\/\/www2.camara.leg.br\/comunicacao\/assessoria-de-imprensa\/cota-parlamentar, accessed November 2018.<\/span><\/p>\n

[4] Opera\u00e7\u00e3o Serenata de Amor, \u201cNon-tech crash course into Opera\u00e7\u00e3o Serenata de Amor\u201d, https:\/\/github.com\/okfn-brasil\/serenata-de-amor, accessed November 2018.<\/span><\/p>\n

[5] Opera\u00e7\u00e3o Serenata de Amor, \u201cFAQ\u201d, https:\/\/serenata.ai\/en\/faq\/, accessed November 2018.<\/span><\/p>\n

[6] Ibid.<\/span><\/p>\n

[7] Erik Brynjolfsson and Andrew McAfee, \u201cWhat\u2019s driving the machine learning explosion?\u201d, <\/span>性视界 Business Review Digital Articles <\/span><\/i>(July 18, 2017).<\/span><\/p>\n

[8] J. Wilson, S. Sachdev, and A. Alter, \u201cHow companies are using machine learning to get faster and more efficient\u201d, <\/span>性视界 Business Review Digital Articles <\/span><\/i>(May 3, 2016).<\/span><\/p>\n

[9] Mike Yeomans, \u201cWhat every manager should know about machine learning\u201d, <\/span>性视界 Business Review Digital Articles <\/span><\/i>(July 7, 2015).<\/span><\/p>\n

[10] Opera\u00e7\u00e3o Serenata de Amor, \u201cAbout\u201d, https:\/\/serenata.ai\/en\/about\/, accessed November 2018.<\/span><\/p>\n

[11] Bruno Pazzim, \u201cComo est\u00e1 acontecendo a hackaton de den\u00fancias da Opera\u00e7\u00e3o Serenata de Amor?\u201d, January 12, 2017, https:\/\/medium.com\/data-science-brigade\/como-est%C3%A1-acontecendo-a-hackaton-de-den%C3%BAncias-da-opera%C3%A7%C3%A3o-serenata-de-amor-a8bd193e0c76, accessed November 2018.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

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