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AbstractA survey of the literature on the economics of natural resources. Extractive resources are classified as renewable or non-renewable, depending on whether they exhibit economically significant rates of regeneration. A unified model of optimal extraction over time is developed, drawing on a number of contributions to the literature. Special features are developed for the renewable and non-renewable cases, and extensions and applications are noted, as well as needs for further research. Policy issues are treated, chief among these being the extent to which the market can be trusted to generate the right rate of extraction. Finally the empirical evidence is reviewed on whether we are running out of extractive resources.

Access to financing for young and innovative firms in the seed stage is a challenge due to the difficulty of assessing their growth potential. Our analysis focuses on the characteristics of the market for start-up rating agencies in France by studying their ability to offer a better understanding of this potential. Our methodology is based on a qualitative and exploratory research through eighteen semi-directive interviews with stakeholders from the start-up and rating ecosystems. We show that, in order to offer a real added value and simultaneously limit information and knowledge asymmetries between managers and financiers, the rating construction process requires a high degree of reliability of the data collected as well as increased transparency. The credibility of the rating presupposes the development of a standard based on three pillars, “human, market and governance”. The rating thus constructed could make it possible to diversify the sources of financing for young and innovative firms in the seed stage and thus support their development.

Keywords: Notation, Start-up, Asymétrie d'information, Asymétrie de connaissance, Scoring, Young and innovative firms, Information asymmetries, Knowledge asymmetries, Calificación, Empresas jóvenes e innovadoras, Asimetrías de información, Asimetrías de conocimiento

This article expounds the competencies that are essential for managing artificial intelligence (AI) in organizations, with emphasis on ethics, but also including the issues from a managerial, technical, human, inclusive and responsible point of view. In the context of change associated with digital transformation, organizations that are digitizing, by integrating AI, need to identify the ethical issues and the associated required competencies to manage AI projects. The issues related to the development and management of AI projects are complex and different from those related to traditional IT project management. This complexity raises ethical, legal and social responsibility questions regarding AI, from an equity, diversity and inclusion perspective. These will have implications for the competencies expected of AI project managers in the future. Our research aimed to identify these competency issues and describe them, which is done through interviews and focus groups with experts from the AI community, in the broader context of a research on AI management. This article focuses primarily on the ethical issues emerging from our review of written works and meetings with AI experts, and their resonance in the Quebec AI ecosystem. We therefore here focus on questions of ethics, labour market transformation, governance and social responsibility. This article is organized in seven parts: introduction, issues, literature review, methodology, results, discussion and conclusion. The current challenges of AI in Quebec are given in terms of ethical management of innovative technologies, as well as the transformation of labour markets associated with AI. These key issues were identified in our 25 research interviews and three focus groups. In conclusion is a set of recommendations to promote change while considering ethical issues linked to turning towards AI.

Keywords: Gouvernance et éthique de l’IA, compétence en éthique, EDI (équité, diversité et inclusion), gestion de l’IA, écosystème québécois d’IA