Artificial intelligence in the mining sector is often viewed through contradictory lenses: either as a threat to workers or as an overhyped technology that fails to deliver in real-world conditions. This session seeks to move beyond these opposing views by demonstrating that intelligence, both human and artificial, is fundamentally contextual: operators excel in intuition and process understanding, while digital systems stand out for their large-scale analytical capabilities. Rather than contrasting these strengths, we will show how combining them can drive tangible improvements in mining operations, particularly in terms of process optimization, data reliability, energy management, and multi-site visibility. Through a presentation, use cases, and a panel discussion, participants will learn how to move from a technology-first approach to an integrated one where people, processes, and data are aligned to address key challenges in Quebec\u2019s mining sector.<\/p>\n","protected":false},"excerpt":{"rendered":"
Artificial intelligence in the mining sector is often viewed through contradictory lenses: either as a threat to workers or as an overhyped technology that fails to deliver in real-world conditions. This session seeks to move beyond these opposing views by demonstrating that intelligence, both human and artificial, is fundamentally contextual: operators excel in intuition and […]<\/p>\n","protected":false},"author":45,"featured_media":0,"parent":83192,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"quebecMines-inter.php","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_oasis_is_in_workflow":0,"_oasis_original":0,"_oasis_task_priority":"","footnotes":""},"class_list":["post-104657","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\n