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ATELIER CIREQ: Perspectives interdisciplinaires sur l’IA en tant qu’agent de changement

APERÇU

Cet atelier souligne les changements importants dans l’économie et la société provoqués par les nouveaux algorithmes d’intelligence artificielle et leur adoption croissante. Les participants rassembleront des perspectives issues de divers domaines tels que l’informatique, l’économie, l’industrie et l’éthique.

SITE DE L’ÉVÉNEMENT

McGill University
855, rue Sherbrooke Ouest
salle Leacock 232
Montréal (Québec) H3A 2T7
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INSCRIPTION

Cet événement est gratuit et ouvert à toute personne intéressée par le sujet. Les places étant limitées, l’inscription est obligatoire.

La période d’inscription est maintenant terminée. (2024-03-21)

CONFÉRENCIERS

Jackie Cheung 
CIFAR AI Chair, Mila; School of Computer Science, McGill University
Co-adapting with Large Language Models: On the Capabilities and Uses of Generative AI for Natural Language
Résumé: Generative AI models of natural language have captured our popular imagination for their potential impact on society and the world. In this talk, I give a brief overview of currently popular techniques, and describe the opportunities and challenges that the use of generative AI engenders with illustrative application scenarios. What are some current and potential use cases of this technology? What are their limitations? And what is the deal with model « hallucinations »? I argue for a need for co-adaptation between large language model capabilities and the uses to which we put them.

Remi Duquette
Vice President, Innovation & Industrial AI, Maya HTT
Practical Examples of the Impacts of AI on the Industrial and Manufacturing Workforce
Résumé: The age of implementation of AI technologies in industrial and manufacturing processes underway is leading to significant changes in the nature of jobs and required skill sets, and it is changing the way human labor is leveraged to financially benefit the enterprise. While automation is streamlining repetitive tasks and increasing efficiency and sometimes removing the human in the loop, it’s also creating new jobs and augmenting the value of humans in the loop, and not just in roles that require advanced technical skills such as data analysis, programming, and machine learning. The labor shortage for tedious manual tasks in industrial and manufacturing environments, especially in Western European countries and in North America, is also driving a much faster adoption of AI technologies, not to replace humans, but to simply get the repetitive tasks done, as well as augmenting the value of the humans taking care of more complex tasks. In general, we have yet to see a reduction of the overall workforce in our industrial and manufacturing clients where we have implemented AI tech. Often, thanks to the AI-based efficiency gains per human workers materialized after adoption, it is in fact the counter-intuitive increase in workforce to further increase the throughput and related company profits that we are witnessing.

Avi Goldfarb
Rotman School of Management, University of Toronto
Pause AI Research?
Résumé: Artificial intelligence (AI) may be the next general purpose technology. General purpose technologies, such as the steam engine and computing, can have an outsized impact on productivity through a positive feedback loop between producing and application industries. Along with the discussion of AI’s potential to improve productivity come a number of policy concerns related to AI’s potential to automate jobs and to create existential risk for humanity. Because of these worries, in March 2023, a widely circulated petition called for a pause in AI research.

That letter asked several questions about AI’s potential impact on society. This talk examines those questions through an economic lens. It highlights reasons to be optimistic about the long-run impact of AI, while underscoring short-run risks. Economic models provide an understanding of where the ambiguity lies and where it does not. Such models suggest no ambiguity on whether there will be jobs and little ambiguity on long-term productivity growth if AI diffuses widely. In contrast, there is substantial ambiguity on the implications of AI’s diffusion for inequality.

ANIMATEURS DE LA TABLE RONDE

Fabian Lange
Economics, McGill University, CIRANO, CIREQ

Victoria Zinde-Walsh
Economics, McGill University, CIREQ

COMMENTATEURS DE LA TABLE RONDE

Jackie Cheung 
CIFAR AI Chair, Mila; School of Computer Science, McGill University

Remi Duquette
Vice President, Innovation & Industrial AI, Maya HTT

Avi Goldfarb
Rotman School of Management, University of Toronto

Jocelyn Maclure
Philosophy, McGill University

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