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| Foteini serves as Co-Chair of the Government of Canada’s Advisory Council on Artificial Intelligence, advising the federal government on how to build on Canada’s strengths and global leadership in AI. </p> | | Foteini serves as Co-Chair of the Government of Canada’s Advisory Council on Artificial Intelligence, advising the federal government on how to build on Canada’s strengths and global leadership in AI. </p> |
− | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_AI Building the future with responsible AI]</strong></p> | + | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_Artificial_Intelligence Building the future with responsible Artificial Intelligence]</strong></p> |
| <p style="margin-bottom:20px;">Follow: [https://twitter.com/fagrafioti @fagrafioti on Twitter] | [https://www.linkedin.com/in/agrafioti/ on LinkedIn]</p> | | <p style="margin-bottom:20px;">Follow: [https://twitter.com/fagrafioti @fagrafioti on Twitter] | [https://www.linkedin.com/in/agrafioti/ on LinkedIn]</p> |
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| <p class="jobtitle">Acting Director of data and artificial intelligence, Treasury Board of Canada Secretariat</p> | | <p class="jobtitle">Acting Director of data and artificial intelligence, Treasury Board of Canada Secretariat</p> |
| <p>Benoit studied computer science at Carleton University in Ottawa. He is acting Director of Data and Artificial Intelligence at the Treasury Board of Canada Secretariat (TBS). He directs the development of the Directive on Automated Decision-Making and the Algorithmic Impact Assessment (AIA). These policy tools ensure that Automated Decision Systems are deployed in a manner that reduces risks to Canadians and federal institutions, and lead to more efficient, accurate, consistent, and interpretable decisions. </p> | | <p>Benoit studied computer science at Carleton University in Ottawa. He is acting Director of Data and Artificial Intelligence at the Treasury Board of Canada Secretariat (TBS). He directs the development of the Directive on Automated Decision-Making and the Algorithmic Impact Assessment (AIA). These policy tools ensure that Automated Decision Systems are deployed in a manner that reduces risks to Canadians and federal institutions, and lead to more efficient, accurate, consistent, and interpretable decisions. </p> |
− | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_AI Building the future with responsible AI]</strong></p> | + | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_Artificial_Intelligence Building the future with responsible Artificial Intelligence]</strong></p> |
| <p style="margin-bottom:20px;">Follow: [https://twitter.com/MrDeshaies @MrDeshaies on Twitter]</p> | | <p style="margin-bottom:20px;">Follow: [https://twitter.com/MrDeshaies @MrDeshaies on Twitter]</p> |
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| In early 2018 Sevgui has spearheaded the creation of a machine learning (ML)/AI solutions Hub within Statistics Canada, i.e. the Data Science Accelerator (DSA). Its purpose: to build data science capacity within the organization by solving concrete problems & delivering practical results that enable clients to move forward confidently with big & unstructured data. The DSA operated as a start-up, entirely business needs driven, on a cost-recovery basis, taking advantage of entrepreneurship best practices, catalyzing culture change through delivery of small wins, building confidence and trust in the new methods. In Sep 2019, Sevgui was appointed as the Senior Director of the new Data Science Division, created to provide an R&D nucleus for the exploration and the application of data science within the Agency. The division deploys specialized multidisciplinary expertise in the latest open source, hardware and cloud service techniques to tackle projects employing deep learning, Natural Language Processing (NLP), image processing, privacy preserving technics and information retrieval methods. </p> | | In early 2018 Sevgui has spearheaded the creation of a machine learning (ML)/AI solutions Hub within Statistics Canada, i.e. the Data Science Accelerator (DSA). Its purpose: to build data science capacity within the organization by solving concrete problems & delivering practical results that enable clients to move forward confidently with big & unstructured data. The DSA operated as a start-up, entirely business needs driven, on a cost-recovery basis, taking advantage of entrepreneurship best practices, catalyzing culture change through delivery of small wins, building confidence and trust in the new methods. In Sep 2019, Sevgui was appointed as the Senior Director of the new Data Science Division, created to provide an R&D nucleus for the exploration and the application of data science within the Agency. The division deploys specialized multidisciplinary expertise in the latest open source, hardware and cloud service techniques to tackle projects employing deep learning, Natural Language Processing (NLP), image processing, privacy preserving technics and information retrieval methods. </p> |
− | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_AI Building the future with responsible AI (moderator)]</strong></p> | + | <p>Participating in <strong>[https://wiki.gccollab.ca/Data_Conference_2022_Agenda#Building_the_future_with_responsible_Artificial_Intelligence Building the future with responsible Artificial Intelligence (moderator)]</strong></p> |
| <p style="margin-bottom:20px;">Follow : [https://www.linkedin.com/in/sevgui-erman-9527a91/ on LinkedIn]</p> | | <p style="margin-bottom:20px;">Follow : [https://www.linkedin.com/in/sevgui-erman-9527a91/ on LinkedIn]</p> |
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