brazilian government
Brazil publishes national artificial intelligence strategy
The Brazilian government has published the country's artificial intelligence (AI) strategy to guide actions around research, innovation and the development of related technologies to tackle the country's greatest challenges, as well as ethics. The publication of the strategy follows a process of over a year since the launch of the consultation to gather input for the plan in late 2019, after a period of engagement with AI consulting firms and an international benchmarking process. According to the Brazilian government, the consultation lasted until March 2020 and more than 1,000 contributions were received. According to the Brazilian minister of Science, Technology and Innovation, Marcos Pontes, the publication is "the fulfillment of a dream" and a big step for Brazil, since the government considers AI is as "essential" for the development of many other technologies, such as innovations around the Internet of Things approach. Pontes also noted the Brazilian government is also making progress around the national AI research center network.
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Brazil to Create National Artificial Intelligence Strategy
The plan aims to use AI to boost competitiveness and productivity and address issues such as social inequality. The Brazilian government has taken another step towards the creation of public policies around artificial intelligence (AI). A national AI strategy will be created as a response to the worldwide race for leadership in the field and the need to discuss the future of work, education, tax, research and development as well as ethics as the application of related technologies becomes more pervasive. A public consultation has been launched to gather input around how AI can solve the country's main issues, identify priority areas of focus for the development and use of the technologies, as well as limits for it. According to the summary on the purpose of the consultation, which ends on January 31, 2020, the government understands that AI can bring improvements to the country's competitiveness and productivity, as well as the provision of public services, quality of life and to reduce social inequality in the southern hemisphere's biggest economy.
Brazil to create national artificial intelligence strategy ZDNet
The Brazilian government has taken another step towards the creation of public policies around artificial intelligence (AI). A national AI strategy will be created as a response to the worldwide race for leadership in the field and the need to discuss the future of work, education, tax, research and development as well as ethics as the application of related technologies becomes more pervasive. A public consultation has been launched to gather input around how AI can solve the country's main issues, identify priority areas of focus for the development and use of the technologies, as well as limits for it. According to the summary on the purpose of the consultation, which ends on January 31, 2020, the government understands that AI can bring improvements to the country's competitiveness and productivity, as well as the provision of public services, quality of life and to reduce social inequality in the southern hemisphere's biggest economy. Brazil adheres to the Organisation for Economic Co-operation and Development (OECD)'s human-centred AI Principles, which provide for recommendations around areas such as transparency and explainability.
Correspondence Analysis of Government Expenditure Patterns
Hsu, Hsiang, Calmon, Flavio P., Filho, José Cândido Silveira Santos, Calmon, Andre P., Salamatian, Salman
We analyze expenditure patterns of discretionary funds by Brazilian congress members. This analysis is based on a large dataset containing over $7$ million expenses made publicly available by the Brazilian government. This dataset has, up to now, remained widely untouched by machine learning methods. Our main contributions are two-fold: (i) we provide a novel dataset benchmark for machine learning-based efforts for government transparency to the broader research community, and (ii) introduce a neural network-based approach for analyzing and visualizing outlying expense patterns. Our hope is that the approach presented here can inspire new machine learning methodologies for government transparency applicable to other developing nations.
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