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Artificial intelligence (AI) has a range of uses in government. It can be used to further public policy objectives (in areas such as emergency services, health and welfare), as well as assist the public to interact with the government (through the use of virtual assistants , for example).
Most artificial intelligence systems involve some sort of integrated technologies, for example, the integration of speech synthesis technologies with that of speech recognition. However, in recent years, there has been an increasing discussion on the importance of systems integration as a field in its own right.
The Pan-Canadian Artificial Intelligence Strategy (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic ...
The Government has set out its “adaptable” approach to regulating artificial intelligence, as it hopes to build public trust in the rapidly developing technology and tap its economic potential ...
Out of the gate, the EU's proposed rules outlaw a number of forms of AI including those used to categorize people based on characteristics including race, gender, and religion; predictive policing ...
As early as 2016, the Obama administration had begun to focus on the risks and regulations for artificial intelligence. In a report titled Preparing For the Future of Artificial Intelligence, [2] the National Science and Technology Council set a precedent to allow researchers to continue to develop new AI technologies with few restrictions. It ...
While Microsoft's offerings make use of OpenAI's GPT-4 large language model, many others use a proprietary system. Meta AI, for example, is called LLaMA 3, which gathers information from a wide ...
Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...