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DTSTAMP:20250428T014948Z
DESCRIPTION:\n\nDATE: Thursday\, December 5th 2024\n\nHOURS: 8:30 AM to 6:3
 0 PM\n\nLOCATION : ´ó·¢²ÊƱƽ̨ Faculty Club\, 3450 rue McTavish\, Montreal\n\n
 \nOverview: The ´ó·¢²ÊƱƽ̨ Collaborative for AI & Society (McCAIS) is celebrat
 ing its 1-year anniversary on December 5th 2024\, and we cordially invite 
 members of the ´ó·¢²ÊƱƽ̨ community to celebrate with us. Taking place at the 
 Faculty Club at the ´ó·¢²ÊƱƽ̨ Downtown Campus\, this full-day event will brin
 g together leading voices to discuss the evolving role of AI in society. T
 he day will feature a keynote address\, panel discussions\, presentations 
 from the recipients of our Interdisciplinary Research Development Awards\,
  and a poster session from the recipients of our BMO Responsible AI Resear
 ch Awards. In addition to insightful sessions\, the event will include bre
 akfast\, lunch\, refreshments\, and an evening cocktail reception\, offeri
 ng ample opportunities for networking and dialogue with other leaders in t
 he field.  \n\nDue to limited seating\, please make sure to register below
  to reserve your place. For more information\, please contact our administ
 rative team at mccais.science [at] mcgill.ca . \n\nRegister Here\n\n\nItin
 erary\n\n8:30 AM - 9:00 AM | Registration Confirmation & Breakfast Recepti
 on\n\n9:00 AM - 9:15 AM | Welcome Address by McCAIS Co-Directors and Vice-
 President of Research & Innovation\, Dominique Bérubé.\n\n9:15 AM - 10:15 
 AM | Keynote Presentation by Dr. Elsa Vasseur and Dr. Abdoulaye Banire Dia
 llo.\n\n\n	WELL-E : Research and Innovation Chair in Animal Welfare and Art
 ificial Intelligence\n\n	\n		\n			\n			\n			 Overview: Responsible AI that properly ad
 dresses real-world stakeholder needs is at the heart of Co-Chairholders El
 sa Vasseur and Abdoulaye Baniré Diallo’s work. They work to carefully inte
 grate domain expert knowledge with cutting-edge AI and IoT methods and too
 ls for the improvement of animal (and human) welfare. Scientific evidence 
 shows that farm animal welfare and cow longevity go hand in hand\, guiding
  the industry's interest in improving animal welfare\, as increasing longe
 vity is seen as an answer to economic\, social and environmental sustainab
 ility concerns in the dairy industry. The WELL-E initiative consists of a 
 Digital Living Laboratory\, focused on the needs of animals and end-users\
 , primarily in the Canadian dairy sector. Grounded in industry partnership
 s\, members of the dairy community sit on both the scientific and manageme
 nt committees\, where they contribute to research orientations\, leading t
 o the co-creation of research projects and initiatives.\n			\n			\n			Launched in 2
 023\, our team has been conducting pilot research and working to build fun
 ctional and resilient data collection infrastructure for implementation on
  dairy farms in 2025. This deployment will ensure robust continuous monito
 ring across a network of farms\, while respecting data confidentiality and
  cybersecurity. We have also developed a framework for the study of animal
  behaviours and emotions\, presenting a paradigm shift for both annotation
  and data analysis based on continuous and heterogeneous data sources. Our
  approach relies on the use of IoT\, computer vision and machine learning 
 to improve our ability to detect and monitor changes in animal welfare and
  longevity earlier than possible with visual methods\, and to generate pre
 dictions to aid on-farm decision-making\, ensuring that resources and effo
 rts are focused on the animals most likely to succeed in the long term. Th
 is research combining animal welfare and technological development will he
 lp the end-users’ community develop evidence-based practices and provide n
 ew keys to the entire livestock value chain to ensure its sustainability.
 \n			\n			    \n			\n			                               \n	\n\n\n \n\n10:15 AM - 10:30 A
 M| Morning Break\n\n10:30 AM - 12:00 PM | Interdisciplinary Research Devel
 opment Awards Lightning Presentations\n\n\n	ED PreVisit: A Multilingual AI 
 Solution for Pre-ED Visit Consultation\, Enhanced Demand Forecasting\, and
  Improved Patient Experience in Emergency Departments \n\n	\n		Presented by: 
 Dr. Yichuan Ding\n			Project Abstract: The 'ED PreVisit' web application is a
 n innovative AI-driven tool designed for patients planning a visit to an E
 mergency Department (ED)\, allowing them to undergo a preliminary self-tri
 age prior to their physical arrival. With data sourced from renowned hospi
 tals such as Jewish General Hospital\, the application identifies symptom 
 patterns\, anticipates potential outcomes\, and tailors its questioning to
  pinpoint the patient's chief complaint. With a user-friendly bilingual in
 terface\, patients input vital details and describe symptoms\, while the a
 pp transforms this data into the IT system of the target ED. This proactiv
 e approach not only expedites the registration and triage process\, but al
 so avoid unnecessary ED visits by directing non-urgent patients to general
  practitioners or pharmacists. Moreover\, it provides ED managers with fut
 ure information about patient arrivals\, which can be used for better dema
 nd forecasting and resource planning. This app can also offer estimated wa
 iting times for various EDs\, allowing patients to choose one with the sho
 rtest wait. Once a patient selects an ED and submits the questionnaire\, t
 he app will also provide tailored preparation instructions for the ED visi
 t\, based on the patient’s profile and chief complaint. Spanning from Janu
 ary 1 2025 to December 31\, 2025\, the project's focus is the development 
 and internal evaluation of the app\, ensuring its efficacy and ease of use
 . \n	\n\n	How can generative AI be used to optimize content creation for sec
 ondary math use? An exploratory project.\n\n	\n		Presented by: Dr. Nikki G. L
 obczowski\n			Project Abstract: As students enter high school\, math topics t
 end to become more abstract\, which proves difficult for many students and
  requires additional instructional support. Teachers of advanced mathemati
 cs need more resources to support their students' learning\, but their opt
 ions are currently limited. Even with the growth of online resources\, man
 y do not provide personalized support or are not connected to specific sec
 ondary math curricula. Some teachers are starting to turn to generative AI
  to help create new content\, but little is known about how they should do
  so. Specifically\, generative AI (genAI)\, such as ChatGPT\, has not typi
 cally been created for educational purposes and given that many are based 
 large language models (LLMs)\, there is a growing need to understand how t
 hese tools can be used to optimize teaching and learning in mathematics. I
 n this project\, we will use an interdisciplinary approach to explore thre
 e main areas: 1) Why and how teachers are (or are not) using generative AI
 \, 2) Teachers needs with regard to content/resource generation\, and  3) 
 The scope of existing genAI tools.  \n	\n\n	AI-Powered Aerial-Ground Collabo
 rative Mobile System for Precision Spraying to Enhance Sustainable Agricul
 ture\n\n	\n		Presented by: Dr. Shangpeng Sun\n			Project Abstract: Remarkable in
 creases in the use of synthetic herbicides have been reported for weed con
 trol. However\, up to 98% of crop spray does not stay on the plants and fl
 ows into the environment\, causing soil and water pollution. Therefore\, r
 educing herbicide use is critically needed to develop resilient and sustai
 nable agriculture\, and it has significant positive impacts on public heal
 th\, society\, and the ecological environment. In this initiative\, we aim
  to develop an AI-powered aerial-ground collaborative mobile system for pr
 ecision spraying to reduce herbicide use. \n	\n\n	Inclusive co-design of AI 
 systems\n\n	\n		Presented by: Dr. Jin Guo\n			Project Abstract: When AI systems 
 are adopted in critical applications\, any failure can pose serious risks 
 to the health\, safety\, and well-being of users or other related stakehol
 ders. Accurate estimation of the severity of the risks and thorough planni
 ng for mitigating them are indispensable but extremely challenging. This i
 s especially true for marginalized and minority communities. Considering s
 uch a gap\, we aim to accelerate the design of inclusive AI systems throug
 h a concrete case study of an accessible form of payment for the elderly p
 opulation. As a first step\, we plan to identify the barriers preventing m
 arginalized users\, in particular the elderly population\, from participat
 ing in the design process of such AI systems. The outcomes from this resea
 rch contribute to improving the existing co-design practices toward the de
 velopment of inclusive AI\, and inform the construction of a shared set of
  vocabulary that technologists and policymakers can use to prevent harms a
 nd risks AI can bring to the minority and marginalized stakeholders of the
  technology at design time.\n	\n\n	Using AI to support Culturally Grounded I
 ndigenous Education\n\n	\n		Presented by: Dr. Joseph Levitan\n			Project Abstrac
 t: Research has shown that culturally grounded education for Indigenous co
 mmunity members supports engagement\, wellbeing\, and learning. However\, 
 implementing culturally grounded education effectively\, particularly in r
 emote areas\, has proven difficult due to the lack of culturally grounded 
 materials and the time it takes to create quality curriculum. Over the pas
 t 6 years our team has been able to develop and implement culturally groun
 ded curriculum in rural Indigenous areas of Peru. However\, it is a challe
 nge to do this work at scale. Artificial intelligence (AI) shows promise f
 or addressing this issue. To demonstrate that AI can create culturally gro
 unded learning materials and curriculum based in community epistemologies\
 , our team will train offline AI software to use community-led\, collabora
 tively gathered knowledge\, such as local plants\, animals\, and cultural 
 practices to foster literary\, numeracy\, and critical thinking skills bas
 ed in communities’ ways of thinking and being. This work will engage in co
 mmunity-based practices and follow First Nations OCAP ethical principles.
 \n	\n\n\n \n\n12:00 PM - 1:30 PM| Lunch Break\n\n1:30 PM - 2:30 PM| Industr
 y Panel - Current Trends and Opportunities for Academic/Industry Collabora
 tions\n\n2:30 PM - 3:00 PM | Student Panel - The Next Generation of AI Res
 earchers\n\n3:00 PM - 3:15 PM | Afternoon Break\n\n3:15 PM - 4:15 PM | Lig
 htning Community Brainstorm Session\n\n4:15 PM - 4:30 PM | Closing Remarks
 \n\n4:30 PM - 6:30 PM | Cocktail Reception & BMO Junior Responsible AI Sch
 olars Poster Showcase\n\n\n	Goktug Bender\n	Leora Klee\n	Sebastian Reinhardt
 \n	Nikki Tye\n	Jocelyn Wong\n\n
DTSTART:20241205T133000Z
DTEND:20241205T233000Z
LOCATION:Faculty Club\, CA\, QC\, Montreal\, H3A 0E5\, 3450 rue McTavish
SUMMARY:´ó·¢²ÊƱƽ̨ Collaborative for AI & Society - Annual Symposium
URL:/cdsi/channels/event/mcgill-collaborative-ai-socie
 ty-annual-symposium-361276
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