How does the Assurance Chain build trust? An overview of the Building Trustworthy Artificial Intelligence white paper
Artificial intelligence (AI) is used in every aspect of our lives and is expected to be the most transformative technology trend in our lifetimes. In addition, AI is also crucial to the long-term development of the Metaverse, which we believe is a vast virtual world created through computers that closely integrates the virtual world with our real world. The metaverse can enable humans to live and interact in a parallel or superimposed space between the real world and the digital world.
However, if we believe that AI systems are not trustworthy, we will miss out on all the advantages they may bring. Mass adoption of Metaverse applications will have to rely on trusted AI principles, no different than any other digital transformation. Assessing the trustworthiness of AI systems will help avoid potential harm.
So, how do you build trustworthy AI?
How does the Assurance Chain build trust?
Is this also a question you are seeking answers to?
Based on the research on artificial intelligence in the past few years, the white paper "Building Trustworthy Artificial Intelligence (AI): How the Assurance Chain Builds Trust" compiled by Arm (click at the end of the article to read the original text and obtain the white paper information) outlines the so-called assurance chain. This will require companies in the AI supply chain to state the ethical risks they have identified relevant to the company and describe their risk mitigation strategies. At the same time, Arm has also conducted research on emerging technologies that may help, with a focus on promoting the development of security and privacy technologies such as trusted execution environments, and how to use security and privacy technologies to provide assurance chains and thereby Build trustworthy artificial intelligence systems.
Developing a chain of assurance will help increase the tech industry’s trust in artificial intelligence to establish a gateway to the metaverse. Whatever the specific form of the regulatory approach, such mechanisms are likely to play a key role in helping companies adequately meet future regulatory requirements. In this white paper, Arm conducted an in-depth discussion on the six key areas of building trustworthy artificial intelligence : security, reliability, privacy, fairness, explainability, and accountability, and outlined the requirements for the correct implementation of each trustworthy artificial intelligence principle. Challenges faced, and relevant suggestions were put forward in response to these challenges and issues in terms of network security, data traceability, and confidential computing .
Figure: Trustworthy AI Principles and Recommendations
If you want to learn more about how to build trustworthy artificial intelligence, please click "Read the original text" to get the white paper "Building Trustworthy Artificial Intelligence (AI): How Assurance Chains Build Trust" .
Click "Read the original text" below to obtain the white paper information