{"id":3368,"date":"2025-10-21T21:29:20","date_gmt":"2025-10-21T21:29:20","guid":{"rendered":"https:\/\/hederav2stg.wpenginepowered.com\/?page_id=3368"},"modified":"2025-12-19T02:16:03","modified_gmt":"2025-12-19T07:16:03","slug":"artificial-intelligence","status":"publish","type":"page","link":"https:\/\/hedera.com\/use-cases\/artificial-intelligence\/","title":{"rendered":"Artificial Intelligence"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\t\tartificial intelligence (ai)\n\t\t\t\t\t\t<\/p>\n\t\t\t\t\t\t\t

\n\t\n\t\t\tThe trust layer for AI\n\t\t<\/h1>\n\t\t\t\t
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AI systems often operate as “black boxes” that are difficult to verify or audit. Hedera adds a much needed layer of trust, enabling AI agents to act transparently with tamper-proof data, real-time verification and automation built in.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\n\t\t\tDLT delivers data integrity to AI\n\t\t<\/h2>\n\t\t\t\t<\/div>\n\t\t\t\t
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AI issue<\/td>\n DLT solution<\/td>\n <\/tr>\n <\/thead>\n
Lack of accountability and ownership<\/strong>
\n AI models can produce harmful or biased outcomes without clear accountability or responsible ownership.<\/span>\n <\/td>\n 		Clear governance<\/strong>
\n DLT records all actions and updates, providing clear accountability and ownership.\n <\/td>\n <\/tr>\n
Data quality and security concerns<\/strong>
\n AI models require large amounts of high-quality and sensitive data to function effectively, which can be prone to breaches.<\/span>\n <\/td>\n 		Data provenance<\/strong>
\n DLT encrypts messages, ensures traceable data origins, and securely records AI model updates.\n <\/td>\n <\/tr>\n
Opaque decision-making<\/strong>
\n AI models often operate as \u2018black boxes,\u2019 raising trust and accountability concerns.<\/span>\n <\/td>\n 		Transparent and tamper-proof decision-making<\/strong>
\nDLT provides an immutable audit trail of AI model decisions and uses consensus to verify the model functions as intended.\n <\/td>\n <\/tr>\n
Biased datasets<\/strong>
\n AI models trained on biased data can amplify misinformation and generate hallucinations.<\/span>\n <\/td>\n 		Fairness<\/strong>
\n DLT addresses bias at the source by tracking the origin of the information used to train the model.\n <\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n