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Artificial Intelligence Governance and Practice of Sustainable Development

This white paper comprehensively summarizes Alibaba’s practice in the field of AI governance and sustainable development, focusing on the current hot issues in AI application, and systematically introduces our practice ideas and methods from the aspects of data, technology, management and multi-collaboration. At the same time, it is explained with some special topics, hoping to provide useful reference for all sectors of society.

At present, artificial intelligence technology is developing vigorously, widely empowering thousands of industries, and bringing profound changes to human production and life. While artificial intelligence promotes social development, there are also risks and challenges.

A large number of artificial intelligence governance and development principles have been formed all over the world. The next step is to put the abstract principles into practice. As an important force in the research and development and application of enterprise artificial intelligence technology, it is urgent to explore a set of artificial intelligence governance practice system suitable for its own business development, implement all governance requirements into the whole life cycle of artificial intelligence, and lay the foundation for the release of artificial intelligence dividends with effective governance, thus accelerating the realization of sustainable development vision.

AI001: White Paper on Artificial Intelligence Core Technology Industry

AI 002: 2021 Love to analyze the application trend report of artificial intelligence

AI003: Data Security Risks and Governance of Artificial Intelligence

AI 004: Ten Technological Advances of Artificial Intelligence in 2020

AI 005: 2020 Panoramic Report of Artificial Intelligence Manufacturers in China

AI 006: 2020 China Artificial Intelligence Business Landing

AI007: White Paper on the New Generation of Artificial Intelligence

AI008: The Way to Win in the Future of Artificial Intelligence

AI009: White Paper on New Infrastructure Development of Artificial Intelligence

AI010: Tencent Artificial Intelligence White Paper

Typical case of ai 011: 5 Gai

AI 012: AI+White Paper on the Development and Application of Higher Education

AI013: China AI+ Retail Industry Development Research Report

AI014: China AI+ Retail Industry Development Research Report

AI 015: Panorama of AI Industry

AI 016: 2020 China AI Application Trend Report

AI 017: 2021 AI Intelligent Manufacturing Research Report

018: 2021 China AI Commercial Landing Market Research Report

AI 19: 2021 Research Report on the Development of Cognitive Intelligence

AI020: Shanghai Artificial Intelligence Innovation and Development Exploration and Practice Case Set

AI 021: 2021 AI China-Taiwan White Paper

AI 022: 2021 Global Research Report on the Application of Artificial Intelligence Education

AI 023: 2021 White Paper on Trusted Artificial Intelligence

AI024: China AI+ Security Industry Development Research Report

AI 25: 2021 White Paper on Intelligence in the Cloud

AI 26: 2021 Research Report on Artificial Intelligence+Medical and Life Sciences Industry in China

AI027: China Cloud Native AI Development Platform White Paper

AI028:2021 Application Research of AIoT in China Smart City

AI029: White Paper on Empowering Urban Space Management in China AI Middle and Taiwan

AI030: White Paper on Cognitive Neural Basis of Artificial Intelligence

AI031: Path, Method and Leading Practice of Enterprise Intelligence

AI 032: White Paper on the Development of AI Framework (2022)

AI033: White Paper on Artificial Intelligence (2022)

AI 034: 2022 Top Ten Trends Report of Deep Synthesis

AI035: China AI Digital Commerce Industry Outlook 2021-2025

AI036: Explainable AI Development Report 2022

AI 037: 2022 White Paper on Baidu Artificial Intelligence Patent

038: Development status, application scenarios and typical enterprises of AI+digital twins

AI 039: 2022 Global Artificial Intelligence Industry Research Report

AI040: Digital Innovation of Neuroscience in China (2022)

AI041: White Paper on the Supporting Environment of Artificial Intelligence Education in Global Primary and Secondary Schools

AI 042: 2022 China Knowledge Map Industry Research Report

AI043: Panorama of Knowledge Points of Artificial Intelligence

AI044: Artificial Intelligence Generated Content (AIGC) White Paper

AI 045: 2022 China AI Commercial Landing Research Report

AI046: China AI Technology Application Scenarios Market Research and Selection Evaluation

AI 047: 2022 Financial AI Development Research Report

AI048: Report on the Ecological Development of Trusted Artificial Intelligence Industry (2022)

AI 049: 2022 China Dialogue AI Industry Development White Paper
AI050: White Paper on Application Practice of Artificial Intelligence Technology
AI051: White Paper on Artificial Intelligence Standardization (2021 Edition)
AI052: Annual Report on Ethical Governance of Artificial Intelligence in Shang Tang (2022)
AI053: An Efficient Investigation Report of Artificial Intelligence Deep Learning Course
AI 054: 2022 White Paper on the Development of Artificial Intelligence

AI 055: 2022 White Paper on Medical AI Industry Research

AI056: White Paper on Practice of Artificial Intelligence Governance and Sustainable Development

The following is part of the report.

Red Hat and IBM Research Institute released AI community project to lower the threshold of enterprise IT automation.

Red Hat recently announced the cooperation with IBM Research to launch the first community project "Project Wisdom", which aims to build intelligent functions and natural language processing capabilities for Ansible and IT automation industries. This project uses artificial intelligence (AI) model to improve the productivity of IT automation developers, and helps IT professionals with different skills and backgrounds to practice and understand IT automation.

According to the survey of IDC, a market research organization, by 2026, 85% of enterprises will combine human skills with AI, machine learning (ML), natural language processing (NLP) and graphic recognition to build forward-looking thinking, and improve the productivity and efficiency of employees by 25%. In addition, technologies such as machine learning, deep learning, natural language processing, graphic recognition and knowledge map are also providing insights, predictions and suggestions that are more accurate and scene-aware.

However, becoming an automation expert requires a lot of effort and resources over time, and needs to explore different fields by using the learning curve. Therefore, the two parties jointly launched Project Wisdom project, which aims to eliminate the gap between Ansible YAML program code and human language. Users can generate program code with correct grammar and automatic functions only by simple English sentences.

Project Wisdom is derived from IBM’s AI basic model "AI for Code". Users only need to input simple English sentences to generate instructions. Project Wisdom then parses sentences and builds automated workflow required by users, and wrITes it in Ansible Playbook form to automatically perform any number of IT tasks.

At the same time, Project Wisdom can assist the system administrators who usually provide local services, and use natural language to generate Playbook instructions, so as to create, configure and operate across domains in other environments. Developers who are familiar with how to build applications, but are not familiar with their cloud computing configuration, can also use Project Wisdom to improve their proficiency in related fields and realize business transformation. In addition, novices in different departments can immediately produce content without relying on the traditional teaching mode, while still accumulating basic knowledge.

According to Red Hat, unlike other AI-driven program code tools, Project Wisdom does not focus on application development, but helps enterprises solve enterprise IT challenges that have become increasingly complex due to the expansion of hybrid cloud adoption. Enterprises can lower barriers to entry and solve the challenge of gradually expanding skill gap through intelligent solutions.