The emergence of artificial intelligence (AI) has promised to bring substantial change to societies. Some good, some bad, and some neither. Nonetheless, all of these changes need to be considered and prepared for. In our previous reports, based on roundtables organised by AI Singapore, we outlined discussions on AI responsibility. As these systems become more complex, allocating responsibility between developer, deployer, and user becomes an essential aspect of managing risk. This calls for a collaborative approach to AI development that will require continuous engagement and actions taken throughout the AI lifecycle, such as quality control measures, limitations on deployment, and other forms of external regulation. Another report has discussed the question of transparency/explainability. Given AI’s revolutionising capacity as decision-makers, transparency and explainability become central to upholding ethical standards in the sector. Yet, how organisations and corporations operationalise transparency and explainability differs from use-case to use-case; there is no one-size-fits-all. This question calls for an audience-centric approach, whereby transparency and explainability differ based on who it needs to be transparent towards. These are regulatory standards that have yet to be set. 

This third report will take a step back from these questions and instead focus on deployment, specifically how AI can be deployed responsibly to create sustainable growth. It is no secret that AI solutions can help supercharge economies, but questions of economic growth are not the only ones important to ask. Given that AI is likely to be a game-changer in most, if not all, industries and use cases, responsibly deploying and using AI requires both long-term and lateral thinking beyond matters of the economy. Only through a responsible deployment can AI’s economic impact lead to sustainable growth.