More access to AI tools means more innovation, but the process of providing this access must be carefully managed.
When company leaders talk about democratizing artificial intelligence (AI), it’s easy to imagine what they have in mind. The more people with access to the raw materials of the knowledge, tools, and data required to build an AI system, the more innovations are bound to emerge. Efficiency improves and engagement increases. Faced with a shortage of technical talent? Microsoft, Amazon, and Google have all released premade drag-and-drop or no-code AI tools that allow people to integrate AI into applications without needing to know how to build machine learning (ML) models.
But as companies move toward democratization, a cautionary tale is emerging. Even the most sophisticated AI systems, designed by highly qualified engineers, can fall victim to bias and can be difficult to explain. An AI system that was built by someone without proper training or that is operated without appropriate controls could create something outright dangerous, introducing discrimination or serious errors. Worse, the problems might not become evident until after a system has been implemented, leaving companies scrambling to reassure stakeholders, undo the damage, and fix the tech.
This is not to say that the democratization of AI is valueless. Making these new technologies more accessible and affordable expands the possibilities of what businesses and governments can accomplish and fuels competition. For example, data sets, models, and research related to the fight against the novel coronavirus have been open source, enabling a large global community to collaborate. The key for company leaders is to avoid getting carried away by the hype and instead focus on clearly identifying exactly what they are going to democratize (will it be something simple, such as data visualization, or something complex, such as model development?), who the users will be, and how their organization can both maximize the benefits and manage the risks with proper training and governance.
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https://www.strategy-business.com/article/Democratizing-artificial-intelligence-is-a-double-edged-sword