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Trustworthy AI
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<h2 id="itu-standardization">ITU standardization</h2> <p>Trustworthy AI is also a work programme of the <a href="/facts/International_Telecommunication_Union/Yn8UKKkw">International Telecommunication Union</a>, an agency of the <a href="/facts/United_Nations/fgXLnmgT">United Nations</a>, initiated under its <a href="/facts/ITU_AI_for_Good/4HEGGTrC">AI for Good</a> programme.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> Its origin lies with the <a href="/facts/ITU-WHO_Focus_Group_on_Artificial_Intelligence_for_Health/FYoLTy8K">ITU-WHO Focus Group on Artificial Intelligence for Health</a>, where strong need for privacy at the same time as the need for analytics, created a demand for a standard in these technologies. </p><p>When <a href="/facts/ITU_AI_for_Good/4HEGGTrC">AI for Good</a> moved online in 2020, the TrustworthyAI seminar series was initiated to start discussions on such work, which eventually led to the standardization activities.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> </p> <h3>Multi-Party Computation</h3> <p><a href="/facts/Secure_multi-party_computation/7xJbbvIo">Secure multi-party computation</a> (MPC) is being standardized under "Question 5" (the incubator) of <a href="/facts/ITU-T_Study_Group_17/I8DNd2B2">ITU-T Study Group 17</a>.<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> </p> <h3>Homomorphic Encryption</h3> <p><a href="/facts/Homomorphic_encryption/pbfGnqBn">Homomorphic encryption</a> allows for computing on encrypted data, where the outcomes or result is still encrypted and unknown to those performing the computation, but can be deciphered by the original encryptor. It is often developed with the goal of enabling use in jurisdictions different from the data creation (under e.g. <a href="/facts/GDPR/RMLY6ohr">GDPR</a>). </p><p>ITU has been collaborating since the early stage of the <i>HomomorphicEncryption.org</i> standardization meetings, which has developed a standard on homomorphic encryption. The 5th homomorphic encryption meeting was hosted at <a href="/facts/World_Triathlon_Aquathlon_Championships/vyJY0ddD">ITU HQ</a> in <a href="/facts/Geneva/14gXxjcq">Geneva</a>. </p> <h3>Federated Learning</h3> <p>Zero-sum masks as used by <a href="/facts/Federated_learning/USkKrLa9">federated learning</a> for privacy preservation are used extensively in the multimedia standards of <a href="/facts/ITU-T_Study_Group_16/5ITW0WzW">ITU-T Study Group 16</a> (<a href="/facts/VCEG/Bzyj7FEY">VCEG</a>) such as <a href="/facts/JPEG/HQ8QS3uB">JPEG</a>, <a href="/facts/MP3/yrBpxUSD">MP3</a>, and <a href="/facts/H.264/soCzKcmJ">H.264</a>, <a href="/facts/H.265/6gp7DC1a">H.265</a> (aka <a href="/facts/MPEG/ygmT7JBB">MPEG</a>). </p> <h3>Zero-knowledge proof</h3> <p>Previous pre-standardization work on the topic of <a href="/facts/Zero-knowledge_proof/38soaPT5">zero-knowledge proof</a> has been conducted in the ITU-T Focus Group on Digital Ledger Technologies. </p> <h3>Differential privacy</h3> <p>The application of <a href="/facts/Differential_privacy/nujcWS4Y">differential privacy</a> in the preservation of privacy was examined at several of the "Day 0" machine learning workshops at AI for Good Global Summits. </p> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/Artificial_Intelligence/lJGauQwX">Artificial Intelligence</a></li> <li><a href="/facts/Privacy-enhancing_technologies/2v8rvT4l">Privacy-enhancing technologies</a></li> <li><a href="/facts/Data_Science/AHYUo0Rn">Data Science</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>"Advancing Trustworthy AI - US Government". National Artificial Intelligence Initiative. Retrieved 2022-10-24. <a href="https://www.ai.gov/strategic-pillars/advancing-trustworthy-ai/" target="_blank">https://www.ai.gov/strategic-pillars/advancing-trustworthy-ai/</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>"TrustworthyAI". ITU. Archived from the original on 2022-10-24. Retrieved 2022-10-24. This article incorporates text from this source, which is by the International Telecommunication Union available under the CC BY 4.0 license. <a href="https://www.itu.int:443/en/ITU-T/Workshops-and-Seminars/2022/0901/Pages/TrustworthyAI.aspx" target="_blank">https://www.itu.int:443/en/ITU-T/Workshops-and-Seminars/2022/0901/Pages/TrustworthyAI.aspx</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>"'Trustworthy AI' is a framework to help manage unique risk". MIT Technology Review. Retrieved 2024-06-01. <a href="https://www.technologyreview.com/2020/03/25/950291/trustworthy-ai-is-a-framework-to-help-manage-unique-risk/" target="_blank">https://www.technologyreview.com/2020/03/25/950291/trustworthy-ai-is-a-framework-to-help-manage-unique-risk/</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>"TrustworthyAI". ITU. Archived from the original on 2022-10-24. Retrieved 2022-10-24. This article incorporates text from this source, which is by the International Telecommunication Union available under the CC BY 4.0 license. <a href="https://www.itu.int:443/en/ITU-T/Workshops-and-Seminars/2022/0901/Pages/TrustworthyAI.aspx" target="_blank">https://www.itu.int:443/en/ITU-T/Workshops-and-Seminars/2022/0901/Pages/TrustworthyAI.aspx</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>"TrustworthyAI Seminar Series". AI for Good. Retrieved 2022-10-24. <a href="https://aiforgood.itu.int/about-ai-for-good/discovery/" target="_blank">https://aiforgood.itu.int/about-ai-for-good/discovery/</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>Shulman, R.; Greene, R.; Glynne, P. (2006-03-21). "Does implementation of a computerised, decision-supported intensive insulin protocol achieve tight glycaemic control? A prospective observational study". Critical Care. 10 (1): P256. doi:10.1186/cc4603. ISSN 1364-8535. PMC 4092631. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092631" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092631</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> </ol>