White Paper: The AI Regulatory Challenge - Balancing Innovation and Inclusivity
A. INTRODUCTION
The current landscape of AI regulatory practices has seen vital stakeholders such as small businesses, the medical/healthcare sector, manufacturing, and community colleges, among others, significantly side-lined. Unfortunately, this exclusion has led to a scenario where elite groups and significant tech corporations predominantly dictate regulation. These stakeholders and others who are potentially impacted must have a voice in the global shaping of policies and technologies – and they should regain their voices in the AI discourse.
Looking back at the purpose of the regulation, the term "regulate" traces its origins to the Latin words "regular" and "regular." "Regulare" signifies 'to control,' whereas "regula" refers to 'ruler' (Jackson, 1997). Regulation encompasses both the act or procedure of control and the condition of being controlled (Harpet, 2012). In this vein, any pursuit of regulation should be balanced, considering all stakeholders' practical realities and diverse concerns, not just a subset.
In the context of AI developments, this misalignment in regulation signals a need to reorientate the regulatory agenda grounded in the practical realities and concerns of a broader range of stakeholders. AI systems often rely on datasets reflecting human biases. By excluding the diverse perspectives stakeholders can offer, AI development risks continuing to embed and amplify these biases, leading to unfair and discriminatory outcomes for various groups. AI advancements directly impact many stakeholders excluded in this dialogue, including manufacturing companies, educational institutions like community colleges, and small businesses. They should have a significant voice in shaping AI regulations. After all, their insights and experiences are crucial in identifying and addressing the tangible challenges AI poses in the workforce, information integrity, public safety, and healthcare.
Although there is some engagement of diverse experts in government discussions on AI, these interactions often need more visibility and influence of industry-led dialogues. Under these circumstances, there is an urgent call for elevating critical voices, including those highlighting bias and inequality in AI, to ensure a robust and comprehensive policy discourse. Analyzing and then addressing the challenges of inclusion in the AI landscape, this white paper critically examines the challenges and opportunities in AI regulation, advocating for more inclusive and equitable practices by involving a diverse range of stakeholders to ensure AI development is responsible, innovative, and beneficial for all sectors of society.
