Trustworthy AI refers to

artificial intelligence Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of re ...

systems designed and deployed to be transparent, robust and respectful of data privacy. Trustworthy AI makes use of a number of

Privacy-enhancing technologies Privacy-enhancing technologies (PET) are technologies that embody fundamental data protection principles by minimizing personal data use, maximizing data security, and empowering individuals. PETs allow online users to protect the privacy of their ...

(PETs), including

homomorphic encryption Homomorphic encryption is a form of encryption that allows computations to be performed on encrypted data without first having to decrypt it. The resulting computations are left in an encrypted form which, when decrypted, result in an output th ...

federated learning Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients) collaboratively train a model while keeping their data Decentralized computing, decentralized, ra ...

secure multi-party computation Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their ...

differential privacy Differential privacy (DP) is a mathematically rigorous framework for releasing statistical information about datasets while protecting the privacy of individual data subjects. It enables a data holder to share aggregate patterns of the group while ...

zero-knowledge proof In cryptography, a zero-knowledge proof (also known as a ZK proof or ZKP) is a protocol in which one party (the prover) can convince another party (the verifier) that some given statement is true, without conveying to the verifier any information ...

.
The concept of trustworthy AI also encompasses the need for AI systems to be explainable, accountable, and robust. Transparency in AI involves making the processes and decisions of AI systems understandable to users and stakeholders. Accountability ensures that there are protocols for addressing adverse outcomes or

biases Bias is a disproportionate weight ''in favor of'' or ''against'' an idea or thing, usually in a way that is inaccurate, closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individ ...

that may arise, with designated responsibilities for oversight and remediation. Robustness and security aim to ensure that AI systems perform reliably under various conditions and are safeguarded against malicious attacks.

ITU standardization

Trustworthy AI is also a work programme of the

International Telecommunication Union The International Telecommunication Union (ITU)In the other common languages of the ITU: * * is a list of specialized agencies of the United Nations, specialized agency of the United Nations responsible for many matters related to information ...

, an agency of the

United Nations The United Nations (UN) is the Earth, global intergovernmental organization established by the signing of the Charter of the United Nations, UN Charter on 26 June 1945 with the stated purpose of maintaining international peace and internationa ...

, initiated under its AI for Good programme. Its origin lies with the ITU-WHO Focus Group on Artificial Intelligence for Health, where strong need for privacy at the same time as the need for analytics, created a demand for a standard in these technologies. When AI for Good moved online in 2020, the TrustworthyAI seminar series was initiated to start discussions on such work, which eventually led to the standardization activities.

Multi-Party Computation

Secure multi-party computation Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their ...

(MPC) is being standardized under "Question 5" (the incubator) of

ITU-T Study Group 17 The ITU-T Study Group 17 (SG17) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with security. The group is concerned with a broad range of security-related standardization issues such as cybersecurity, ...

Homomorphic Encryption

Homomorphic encryption Homomorphic encryption is a form of encryption that allows computations to be performed on encrypted data without first having to decrypt it. The resulting computations are left in an encrypted form which, when decrypted, result in an output th ...

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.

GDPR The General Data Protection Regulation (Regulation (EU) 2016/679), abbreviated GDPR, is a European Union regulation on information privacy in the European Union (EU) and the European Economic Area (EEA). The GDPR is an important component of ...

). ITU has been collaborating since the early stage of the ''HomomorphicEncryption.org'' standardization meetings, which has developed a standard on homomorphic encryption. The 5th homomorphic encryption meeting was hosted at ITU HQ in

Geneva Geneva ( , ; ) ; ; . is the List of cities in Switzerland, second-most populous city in Switzerland and the most populous in French-speaking Romandy. Situated in the southwest of the country, where the Rhône exits Lake Geneva, it is the ca ...

Federated Learning

Zero-sum masks as used by

for privacy preservation are used extensively in the multimedia standards of

ITU-T Study Group 16 The ITU-T Study Group 16 (SG16) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with multimedia coding, systems and applications, such as video coding standards. It is responsible for standardization of ...

(

VCEG The Video Coding Experts Group or Visual Coding Experts Group (VCEG, also known as Question 6) is a working group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with standards for compression coding of video, images, audio ...

) such as

JPEG JPEG ( , short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography. The degr ...

MP3 MP3 (formally MPEG-1 Audio Layer III or MPEG-2 Audio Layer III) is a coding format for digital audio developed largely by the Fraunhofer Society in Germany under the lead of Karlheinz Brandenburg. It was designed to greatly reduce the amount ...

, and H.264, H.265 (aka

MPEG The Moving Picture Experts Group (MPEG) is an alliance of working groups established jointly by International Organization for Standardization, ISO and International Electrotechnical Commission, IEC that sets standards for media coding, includ ...

Zero-knowledge proof

Previous pre-standardization work on the topic of

has been conducted in the ITU-T Focus Group on Digital Ledger Technologies.

Differential privacy

The application of

in the preservation of privacy was examined at several of the "Day 0" machine learning workshops at AI for Good Global Summits.

References

{{reflist 2020 establishments Information privacy United Nations Economic and Social Council International Telecommunication Union Artificial intelligence associations Regulation of artificial intelligence