Description: The multistakeholder approach is a collaborative method that involves various stakeholders, such as governments, businesses, non-governmental organizations, and civil society, to address ethical issues and bias in artificial intelligence (AI). This approach recognizes that problems related to AI are complex and multifaceted, and that their solution requires collaboration among different actors who contribute their perspectives and knowledge. By integrating diverse voices, the aim is to ensure that decisions regarding the development and implementation of AI technologies are fair, inclusive, and responsible. The main characteristics of this approach include transparency, active participation of all stakeholders, and the pursuit of a consensus that reflects the concerns and needs of different groups. The relevance of the multistakeholder approach lies in its ability to address the ethical challenges that arise in the use of AI, such as algorithmic bias, data privacy, and accountability in automated decision-making. By fostering open and constructive dialogue among stakeholders, normative frameworks and best practices can be developed to promote the ethical use of AI and minimize its potential risks.
History: The multistakeholder approach has evolved over the past few decades, especially with the rise of the Internet and globalization. It was formalized in international forums such as the World Summit on the Information Society (WSIS) in 2003 and 2005, where issues of Internet governance and the inclusion of multiple stakeholders were discussed. As AI has gained prominence, this approach has adapted to address its ethical challenges, promoting collaboration among governments, businesses, and civil society.
Uses: The multistakeholder approach is used in various areas related to technology governance, including AI regulation, data privacy policy formulation, and ethical standards creation. It is applied in discussion forums, conferences, and working groups where collaboration among different sectors is sought to address complex issues and develop inclusive solutions.
Examples: An example of the multistakeholder approach in action is the OECD AI Ethics Initiative, which brings together governments, businesses, and experts to develop ethical principles for AI. Another case is the work of the European Union’s High-Level Expert Group on Artificial Intelligence, which includes representatives from various sectors to address the ethical and legal challenges of AI in Europe.
