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EXECUTIVE SUMMARY
Artificial intelligence (AI) is an enabling technology impacting the global economy and international trade. Combined with business-process-oriented automation and more efficient data flow exchanges, AI further promises to lift barriers to international trade, stimulate growth in global electronic commerce and allow for better predictions and associations to inform policy decisions.
Ethics and responsibility also play a key role in the design and implementation of AI systems. Ethical AI adheres to fundamental ethical guidelines such as accountability, transparency, privacy and data protection, lawfulness, fairness and non-discrimination. Responsible AI should avoid biases rooted in data and not discriminate against someone because of data attributes that are out of their control.
Many ethics and responsibility challenges present themselves in AI use cases. Data used in training AI models needs to be well sourced, designed, managed and protected. Managing and determining the truthfulness of the high influx of new, AI-generated data can pose a real challenge. Ultimately, AI has the potential to reshape the future workforce structure and impact the global economy through automation and robotization of repeatable routine tasks and processes.
Integrations and synergies are possible between AI and other emerging technologies such as IoT and blockchains. When AI uses blockchain data, the correctness and truthfulness of that data is guaranteed by the blockchain protocol. When AI is responsible for specific decision-making scenarios it can benefit from a complete record history, immutability, and other blockchain features. AI can also use data gathered and produced by networked IoT devices and can enable optimization, improve performance and provide additional business insight into IoT data.
In the supply chain, AI can be used in various scenarios: detecting anomalies, automating and optimizing business processes and physical processes such as route optimization, and extracting key information elements from both physical documents and electronic sources. In e-commerce, AI can detect inaccurate data by analysing the description of the goods, the point of origin, the destination, and any other parameter that we want to function as a control parameter to avoid fraud and delays.
Draft programme of work of the Economic Cooperation and Integration subprogramme for 2025.
Digital and green transformations: exploring the strategic dynamics of experimentation and learning.
Annotated provisional agenda for the seventeenth session.
BUSINESS REQUIREMENTS SPECIFICATION (BRS) - Product Circularity Data use case (version 1.0)
Extension of BRS Traceability and Transparency in the Textile and Leather Sector, Part 2
Approved by UN/CEFACT Bureau on 09 April 2024