标题： 加拿大众议院关于人工智能技术对加拿大劳动力影响研究的简报：生成式人工智能颠覆AI和劳动力模型 显示英文标题

标题： Brief for the Canada House of Commons Study on the Implications of Artificial Intelligence Technologies for the Canadian Labor Force: Generative Artificial Intelligence Shatters Models of AI and Labor

摘要： 生成性人工智能（AI）的令人兴奋的进步引发了对就业、教育、生产力和工作未来的担忧。与过去的技术一样，生成性AI可能不会导致大规模失业。但与过去的技术不同，生成性AI具有创造性、认知性和潜在的普遍性，这使得自动化预测的一般假设不适合当今的情况。现有的预测表明，生成性AI将影响那些以前被认为不受自动化影响的职业中的工人。随着AI的全部能力和应用逐渐显现，政策制定者应该促进工人的职业适应能力。实现这一目标需要改善关于当地和职业头衔的就业分离和失业的数据，以便识别出面临劳动中断的工人早期指标。此外，审慎的政策应激励教育项目适应以AI作为工具的学习，同时为学生准备好未来工作的需求。 显示英文摘要

摘要： Exciting advances in generative artificial intelligence (AI) have sparked concern for jobs, education, productivity, and the future of work. As with past technologies, generative AI may not lead to mass unemployment. But, unlike past technologies, generative AI is creative, cognitive, and potentially ubiquitous which makes the usual assumptions of automation predictions ill-suited for today. Existing projections suggest that generative AI will impact workers in occupations that were previously considered immune to automation. As AI's full set of capabilities and applications emerge, policy makers should promote workers' career adaptability. This goal requires improved data on job separations and unemployment by locality and job titles in order to identify early-indicators for the workers facing labor disruption. Further, prudent policy should incentivize education programs to accommodate learning with AI as a tool while preparing students for the demands of the future of work.