{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/156981"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/156981","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Decentralized Data Markets","abstract":"Acquiring access to massive amounts of data has become fundamental to state-of-the-art artificial intelligence systems. However, as data value increases, data owners have challenged current norms and practices of data acquisition. Data marketplaces have been promoted to fairly compensate data producers and incentivize greater data sharing. In this thesis, I describe a decentralized model of data markets to overcome privacy concerns in siloed, data-limited domains such as healthcare. I propose two federated techniques to automatically select a subset of data sellers and datapoints for a buyer given some sample data. I also examine the socio-technical implications of emerging data markets for medical data and synthesize ethical principles for medical data marketplaces. Decentralized data markets have the potential to enable new AI economies through more robust, transparent, and participatory data sharing platforms. Through the contributions in this thesis, I hope to make a positive step towards realizing a future where transformative data-enabled technologies such as general-purpose machine learning systems are developed more responsibly and the benefits are distributed more equitably.","abstract_html":"Acquiring access to massive amounts of data has become fundamental to state-of-the-art artificial intelligence systems. However, as data value increases, data owners have challenged current norms and practices of data acquisition. Data marketplaces have been promoted to fairly compensate data producers and incentivize greater data sharing. In this thesis, I describe a decentralized model of data markets to overcome privacy concerns in siloed, data-limited domains such as healthcare. I propose two federated techniques to automatically select a subset of data sellers and datapoints for a buyer given some sample data. I also examine the socio-technical implications of emerging data markets for medical data and synthesize ethical principles for medical data marketplaces. Decentralized data markets have the potential to enable new AI economies through more robust, transparent, and participatory data sharing platforms. Through the contributions in this thesis, I hope to make a positive step towards realizing a future where transformative data-enabled technologies such as general-purpose machine learning systems are developed more responsibly and the benefits are distributed more equitably.","abstract_has_math":false,"creators":["Lu, Charles"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Program in Media Arts and Sciences (Massachusetts Institute of Technology)","school":null,"contributors":[],"advisors":["Raskar, Ramesh"],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:21:51Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/156981","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Raskar, Ramesh"]},{"key":"dc:contributor.department","label":"Department","values":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"]},{"key":"dc:creator","label":"Author","values":["Lu, Charles"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-09-24T18:24:44Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-09-24T18:24:44Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-05"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Science in Media Arts and Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/156981"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Acquiring access to massive amounts of data has become fundamental to state-of-the-art artificial intelligence systems. However, as data value increases, data owners have challenged current norms and practices of data acquisition. Data marketplaces have been promoted to fairly compensate data producers and incentivize greater data sharing. In this thesis, I describe a decentralized model of data markets to overcome privacy concerns in siloed, data-limited domains such as healthcare. I propose two federated techniques to automatically select a subset of data sellers and datapoints for a buyer given some sample data. I also examine the socio-technical implications of emerging data markets for medical data and synthesize ethical principles for medical data marketplaces. Decentralized data markets have the potential to enable new AI economies through more robust, transparent, and participatory data sharing platforms. Through the contributions in this thesis, I hope to make a positive step towards realizing a future where transformative data-enabled technologies such as general-purpose machine learning systems are developed more responsibly and the benefits are distributed more equitably."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Decentralized Data Markets"]}]}],"canonical_facts":{"dc:contributor.advisor":["Raskar, Ramesh"],"dc:contributor.department":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"],"dc:creator":["Lu, Charles"],"dc:date.accessioned":["2024-09-24T18:24:44Z"],"dc:date.available":["2024-09-24T18:24:44Z"],"dc:date.issued":["2024-05"],"dc:description.abstract":["Acquiring access to massive amounts of data has become fundamental to state-of-the-art artificial intelligence systems. However, as data value increases, data owners have challenged current norms and practices of data acquisition. Data marketplaces have been promoted to fairly compensate data producers and incentivize greater data sharing. In this thesis, I describe a decentralized model of data markets to overcome privacy concerns in siloed, data-limited domains such as healthcare. I propose two federated techniques to automatically select a subset of data sellers and datapoints for a buyer given some sample data. I also examine the socio-technical implications of emerging data markets for medical data and synthesize ethical principles for medical data marketplaces. Decentralized data markets have the potential to enable new AI economies through more robust, transparent, and participatory data sharing platforms. Through the contributions in this thesis, I hope to make a positive step towards realizing a future where transformative data-enabled technologies such as general-purpose machine learning systems are developed more responsibly and the benefits are distributed more equitably."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/156981"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Decentralized Data Markets"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Media Arts and Sciences"]},"updated_at":"2026-07-22T22:21:51Z"}