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The Library of Congress is the largest library in the world, with millions of books, recordings, photographs, newspapers, maps and manuscripts in its collections. These materials are made available th... The Library of Congress is the largest library in the world, with millions of books, recordings, photographs, newspapers, maps and manuscripts in its collections. These materials are made available through various library interfaces for searching and browsing so that patrons may view (or listen to) items from the collection. Over the past few years, the Digital Innovation Labs Section (Labs) of the Digital Strategy Division has undertaken a range of programs aimed at maximizing the use of digital collections and supporting emerging research methods. This work encompasses machine learning and crowdsourcing prototypes, proof-of-concept experiments, and reports with accompanying recommendations to explore the opportunities and challenges of operationalizing emerging technologies at scale. Through various experiments, reports and events, Labs has been committed to exploring methods and approaches that responsibly integrate people and machines. User feedback, transparent and open knowledge sharing, iteration, and combining human expertise with automated methods is a central part of Labs experimental process. Now, the Library of Congress seeks to build on these initial experiments to further examine models that expand access to digital collections by combining digitally-enabled human participation with computational methods, otherwise known as human-in-the-loop approaches. The Library is seeking a contractor to provide at least two experimental prototypes or proofs of concept for at least two human in-the-loop workflows using Library of Congress collections that are presented and tested with users. The goals in creating these prototypes are to model, test, and evaluate different ethical approaches to applying crowdsourcing and machine learning methods to Library digital collections that enhance collection usability, utility, discoverability, and user engagement. Amendment 0001 revises Section C.4, Key Personnel and revises clause LC52.232-2, Schedule of Payments, to include an updated payment schedule. All other terms and conditions remain unchanged. Amendment 0002 corrects the proposal response date as reflected in the original solicitation and revises clause LC52.232-2, Schedule of Payments, to reflect the updated payment schedule. Amendment 0003 provides Attachment J-1 - Responses to Offeror Questions. Amendment 0004 corrects Responses to Offer Questions and extends date to 8/7/20.