Policymakers around the world often aim to learn from ordinary people through participatory institutions like consultations, petitions, complaint mechanisms, townhalls, constituent communications, crowdsourcing platforms, participatory budgeting, and citizen assemblies. But when faced with large volumes of complex information inputs, they can struggle with information overload challenges that leave them unable to learn meaningful and actionable information outputs. This book develops and illustrates a new framework for understanding the different types of information that policymakers can learn from ordinary people, the complexity of that information, and the different ways in which it can be processed into meaningful policy knowledge. This framework highlights crucial differences in how information is solicited and processed, and to whom that processing is delegated, that shape policymakers' abilities to learn specific and novel information like new problems, new ideas, or new perspectives. While simple information is more straightforward to solicit and process, achieving the potential benefits of learning from ordinary people often requires complex information instead. This complex information must be solicited in open-ended ways and subsequently processed by filtering, rather than aggregating, public inputs and ensuring adequate roles for domain-specific knowledge to recognize novel values. This framework also helps better understand the potential risks of inaccuracy or bias in participatory institutions, and the potential applications of new technologies like artificial intelligence as well as their limits. Berliner illustrates these with examples drawn from around the world and from diverse forms of public participation in policymaking.This is an open access title available under the terms of a [CC BY-NC-ND 4.0 International] licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations.