Can we innovate responsibly during a pandemic? Artificial intelligence, digital solutions and SARS-CoV-2✎
Last modified on 24 June 2020
This policy brief was prepared by the In Fieri research team, based at University of Montreal, in collaboration with the International Observatory on the Societal Impacts of AI and digital Tools (OBVIA).
Lehoux, P, Alami, H., Mörch, C., Rivard, L., Oliveira, R.R., Silva, H. (2020). Can we innovate responsibly during a pandemic? Artificial intelligence, digital solutions and SARS-Cov-2.
As deconfinement begins, the potential for artificial intelligence (AI) and digital solutions to accelerate the fight against COVID-19 is increasingly debated. Despite promises and hopes, one may wonder whether the required conditions for innovating responsibly are met?
Although experts and journalists repeatedly assert that the future is uncertain, one can already identify known socioeconomic dynamics and their predictable and undesirable effects. These dynamics predate solutions based on AI and digital tools and largely shape their future trajectories.
This policy brief illustrates and provides examples of societal issues raised by these trajectories and explains how four principles can, as of today, steer a more responsible development of innovations.
These principles are needed in normal times and prioritizing them during a pandemic will help to match the ”right” solutions with the “right” problems so that they may benefit the entire population.
It is important to immediately commit to a responsible innovation pathway because the proposed solutions could bolster or hinder epidemiological surveillance strategies and efforts of the health and social services system aiming to resolve the health crisis.
While a top-down approach was adopted at the outset of the lockdown, from now on public decision-makers should include civil society through bottom-up strategies in order to resolve the health crisis and to ensure a democratic approach to deconfinement.
Developers should organize and remotely participate in interdisciplinary and intersectoral collaborative activities (hackathons, open platforms, Fab labs, etc.) as well as those that aim to gather diverse viewpoints (scientific cafés, focus groups, etc.).
CHALLENGES & RECOMMENDATIONS
For public decision-makers
- Clarifying which innovative paths are best aligned with the common good and determining how to pursue them from now on.
- Encouraging innovations that meet the highest standards of effectiveness, safety and relevance, which are at the heart of the four responsible innovation principles
For AI and digital solutions developers
- Managing both expected and unexpected effects of solutions by examining a range of scenarios that call upon the expertise of social scientists and health scientists.
- Adopting business models and design strategies that meet the four responsible innovation principles in a consistent, inclusive and transparent manner.
(*) For more detailed recommendations please see pdf (page 8)