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Pour dresser le bilan de ses pratiques en début de pandémie, Moisson Montréal a utilisé un nouvel outil d’appréciation des effets de l’action intersectorielle locale, développé par des membres de la Chaire de recherche du Canada Approches communautaires et inégalités de santé. Cet outil interactif offert gratuitement en ligne aide des organismes tels que Moisson Montréal, qui œuvrent en réseau avec de multiples partenaires intersectoriels, à comprendre, modéliser et piloter les actions (tenue d’une activité, production d’un document, représentation, etc.) à entreprendre pour répondre à un besoin social, et à en analyser les retombées.

Cet article rend compte de la manière dont les organisations internationales pourraient s’approprier la démarche délibérative à l’occasion de leurs efforts de régulation éthique de l’IA en présentant le projet de la délibération internationale intitulée « Dialogue inclusif sur l’éthique de l’intelligence artificielle (IA) » (ODAI) menée par Algora Lab - Université de Montréal et Mila - Institut québécois d’intelligence artificielle. Ce projet délibératif portait sur le premier instrument normatif mondial en éthique de l’IA rédigé par l’UNESCO. L’ODAI se démarque par sa portée internationale, le nombre de personnes consultées et sa réalisation en ligne. Après une présentation du cadre méthodologique et théorique de la délibération sur l’éthique de l’IA, nous opérons une analyse critique du processus et nous proposerons finalement des recommandations pratiques pour de futures délibérations en éthique de l’IA.

Although healthcare managers make increasingly difficult decisions about health innovations, the way they may interact with innovators to foster health system sustainability remains underexplored. Drawing on the Responsible Innovation in Health (RIH) framework, this paper analyses interviews ( n=37) with Canadian and Brazilian innovators to identify: how they operationalize inclusive design processes; what influences the responsiveness of their innovation to system-level challenges; and how they consider the level and intensity of care required by their innovation. Our qualitative findings indicate that innovators seek to: 1) engage stakeholders at an early ideation stage through context-specific methods combining both formal and informal strategies; 2) address specific system-level benefits but often struggle with the positioning of their solution within the health system; and 3) mitigate staff shortages in specialized care, increase general practitioners’ capacity or patients and informal caregivers’ autonomy. These findings provide empirical insights on how healthcare managers can promote and organize collaborative processes that harness innovation towards more sustainable health systems. By adopting a RIH-oriented managerial role, they can set in place more inclusive design processes, articulate key system-level challenges, and help innovators adjust the level and intensity of care required by their innovation.

Although healthcare managers make increasingly difficult decisions about health innovations, the way they may interact with innovators to foster health system sustainability remains underexplored. Drawing on the Responsible Innovation in Health (RIH) framework, this paper analyses interviews ( n=37) with Canadian and Brazilian innovators to identify: how they operationalize inclusive design processes; what influences the responsiveness of their innovation to system-level challenges; and how they consider the level and intensity of care required by their innovation. Our qualitative findings indicate that innovators seek to: 1) engage stakeholders at an early ideation stage through context-specific methods combining both formal and informal strategies; 2) address specific system-level benefits but often struggle with the positioning of their solution within the health system; and 3) mitigate staff shortages in specialized care, increase general practitioners’ capacity or patients and informal caregivers’ autonomy. These findings provide empirical insights on how healthcare managers can promote and organize collaborative processes that harness innovation towards more sustainable health systems. By adopting a RIH-oriented managerial role, they can set in place more inclusive design processes, articulate key system-level challenges, and help innovators adjust the level and intensity of care required by their innovation.

Cet article rend compte de la manière dont les organisations internationales pourraient s’approprier la démarche délibérative à l’occasion de leurs efforts de régulation éthique de l’IA en présentant le projet de la délibération internationale intitulée « Dialogue inclusif sur l’éthique de l’intelligence artificielle (IA) » (ODAI) menée par Algora Lab - Université de Montréal et Mila - Institut québécois d’intelligence artificielle. Ce projet délibératif portait sur le premier instrument normatif mondial en éthique de l’IA rédigé par l’UNESCO. L’ODAI se démarque par sa portée internationale, le nombre de personnes consultées et sa réalisation en ligne. Après une présentation du cadre méthodologique et théorique de la délibération sur l’éthique de l’IA, nous opérons une analyse critique du processus et nous proposerons finalement des recommandations pratiques pour de futures délibérations en éthique de l’IA.

Context Partnership between patients and health-care professionals (HCPs) is a concept that needs a valid, practical measure to facilitate its use by patients and HCPs. Objective To co-construct a tool for measuring the degree of partnership between patients and HCPs. Design The CADICEE tool was developed in four steps: (1) generate key dimensions of patient partnership in clinical care; (2) co-construct the tool; (3) assess face and content validity from patients’ and HCPs’ viewpoints; and (4) assess the usability of the tool and explore its measurement performance. Results The CADICEE tool comprises 24 items under 7 dimensions: 1) relationship of Confidence or trust between the patient and the HCPs; 2) patient Autonomy; 3) patient participation in Decisions related to care; 4) shared Information on patient health status or care; 5) patient personal Context; 6) Empathy; and 7) recognition of Expertise. Assessment of the tool's usability and measurement performance showed, in a convenience sample of 246 patients and relatives, high face validity, acceptability and relevance for both patients and HCPs, as well as good construct validity. Conclusions The CADICEE tool is developed in co-construction with patients to evaluate the degree of partnership in care desired by patients in their relationship with HCPs. The tool can be used in various clinical contexts and in different health-care settings. Patient or Public Contribution Patients were involved in determining the importance of constructing this questionnaire. They co-constructed it, pre-tested it and were part of the entire questionnaire development process. Three patients participated in the writing of the article.

Context Partnership between patients and health-care professionals (HCPs) is a concept that needs a valid, practical measure to facilitate its use by patients and HCPs. Objective To co-construct a tool for measuring the degree of partnership between patients and HCPs. Design The CADICEE tool was developed in four steps: (1) generate key dimensions of patient partnership in clinical care; (2) co-construct the tool; (3) assess face and content validity from patients’ and HCPs’ viewpoints; and (4) assess the usability of the tool and explore its measurement performance. Results The CADICEE tool comprises 24 items under 7 dimensions: 1) relationship of Confidence or trust between the patient and the HCPs; 2) patient Autonomy; 3) patient participation in Decisions related to care; 4) shared Information on patient health status or care; 5) patient personal Context; 6) Empathy; and 7) recognition of Expertise. Assessment of the tool's usability and measurement performance showed, in a convenience sample of 246 patients and relatives, high face validity, acceptability and relevance for both patients and HCPs, as well as good construct validity. Conclusions The CADICEE tool is developed in co-construction with patients to evaluate the degree of partnership in care desired by patients in their relationship with HCPs. The tool can be used in various clinical contexts and in different health-care settings. Patient or Public Contribution Patients were involved in determining the importance of constructing this questionnaire. They co-constructed it, pre-tested it and were part of the entire questionnaire development process. Three patients participated in the writing of the article.

This article explores how health innovation designers articulate are and responsibility when designing new health technologies. Towards this end, we draw on Tronto’s ethic of care framework and Responsible Research and Innovation (RRI) scholarship to analyse interviews with Canadian health innovators (n ¼ 31). Our findings clarify how respondents: 1) direct their attention to needs and ways to improve care; 2) mobilise their skill set to take care of problems; 3) engage in what we call ‘care-making’ practices by prioritising key material qualities; and 4) operationalise responsiveness to caregivers and care-receivers through user-centred design. We discuss the inclusion of health innovation designers within the care relationship as ‘caremakers’ as well as the tensions underlying their ways of caring and their conflicting responsibilities.

This article explores how health innovation designers articulate are and responsibility when designing new health technologies. Towards this end, we draw on Tronto’s ethic of care framework and Responsible Research and Innovation (RRI) scholarship to analyse interviews with Canadian health innovators (n ¼ 31). Our findings clarify how respondents: 1) direct their attention to needs and ways to improve care; 2) mobilise their skill set to take care of problems; 3) engage in what we call ‘care-making’ practices by prioritising key material qualities; and 4) operationalise responsiveness to caregivers and care-receivers through user-centred design. We discuss the inclusion of health innovation designers within the care relationship as ‘caremakers’ as well as the tensions underlying their ways of caring and their conflicting responsibilities.

In this paper, we discuss how universities can become more essential players in the digital innovation and artificial intelligence (DI&AI) ecosystem and increase their capacity to support the “responsible” development and use of these technologies. The four sections of Part I explore the different ways in which universities can change the future of DI&AI and how DI&AI might transform the world of universities. Concrete examples of innovative and inspiring academic practices related to various challenges and opportunities explored in the paper are highlighted throughout. In section 1, we recognize that academics in the social and human sciences (SHS) have started to develop knowledge, tools and methodologies around the concept of responsible DI&AI. However, these have yet to be integrated in organizations and policy, which struggle to anticipate the societal impact of producing and using cutting-edge DI&AI systems. Collaboration between SHS scientists, their Science, Technology, Engineering and Mathematics (STEM) colleagues and non-academic actors in the DI&AI ecosystem is not yet commonplace. We explore some of the impediments to this collaboration, while stressing its increasing importance in the face of growing public mistrust of organizations operating DI&AI and collecting and using personal data. Universities have not yet adopted changes required to capitalize on their status as trust brokers and engage with civil society and other stakeholders on issues of responsible innovation.

In this paper, we discuss how universities can become more essential players in the digital innovation and artificial intelligence (DI&AI) ecosystem and increase their capacity to support the “responsible” development and use of these technologies. The four sections of Part I explore the different ways in which universities can change the future of DI&AI and how DI&AI might transform the world of universities. Concrete examples of innovative and inspiring academic practices related to various challenges and opportunities explored in the paper are highlighted throughout. In section 1, we recognize that academics in the social and human sciences (SHS) have started to develop knowledge, tools and methodologies around the concept of responsible DI&AI. However, these have yet to be integrated in organizations and policy, which struggle to anticipate the societal impact of producing and using cutting-edge DI&AI systems. Collaboration between SHS scientists, their Science, Technology, Engineering and Mathematics (STEM) colleagues and non-academic actors in the DI&AI ecosystem is not yet commonplace. We explore some of the impediments to this collaboration, while stressing its increasing importance in the face of growing public mistrust of organizations operating DI&AI and collecting and using personal data. Universities have not yet adopted changes required to capitalize on their status as trust brokers and engage with civil society and other stakeholders on issues of responsible innovation.

Notion sujette à controverses, l’innovation sociale est appropriée au Québec par divers acteurs ayant le changement social à cœur et finit par constituer son propre écosystème. Il se compose, entre autres, des praticiens qui professionnalisent une démarche d’accompagnement à l’innovation sociale : les consultants. Stimulés par la mise en place de modèles sociétaux alternatifs visant une transformation sociale durable, les processus qu’ils élaborent s’écartent des modèles traditionnels de la consultation en management. Considérant cela, ce projet de recherche aborde la question suivante : en quoi consiste la consultation en innovation sociale? Outre la compréhension des principales approches et questions soulevées dans la littérature par les concepts d’innovation sociale et de consultation, ce mémoire explore les tensions et paradoxes inhérents au champ de l’innovation sociale. Il se consacre plus précisément à une étude comparative des pratiques de consultation mises en œuvre par des praticiens de différentes organisations œuvrant dans le milieu, et le rôle qu’ils jouent dans le changement social.

L’objectif de la démarche de coconstruction et de ses ateliers est notamment permettre d’exemplifier et de mettre à l’épreuve les principes de la Déclaration de Montréal IA Responsable à l’aide de scénarios prospectifs en 2025 permettant de préciser des enjeux éthiques sectoriels, puis de formuler des recommandations prioritaires auprès des gouvernements québécois et canadiens, des parties prenantes et de la communauté de recherche universitaire.

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Le 3 novembre 2017, l’Université de Montréal lançait les travaux de coconstruction de la Déclaration de Montréal pour un développement responsable de l’intelligence artificielle (Déclaration de Montréal). Un an plus tard, nous présentons les résultats du processus de délibération citoyenne. Des dizaines d’événements ont été organisés pour engager la discussion autour des enjeux sociétaux de l’intelligence artificielle (IA), et une quinzaine d’ateliers de délibération ont été tenus en trois mois, faisant participer plus de 500 citoyens, experts et parties prenantes de tous les horizons. La Déclaration de Montréal est une œuvre collective qui a pour objectif de mettre le développement de l’IA au service du bien-être de tout un chacun, et d’orienter le changement social en élaborant des recommandantions.