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HKCNSA VP Dicky Wong shared thought on how the cybersecurity industry should respond to the development of artificial intelligence

With the rapid development of artificial intelligence (AI), its application in the field of cybersecurity has become increasingly widespread, and the associated security issues are becoming more prominent. As a crucial force in safeguarding the digital world, the cybersecurity industry needs to actively address the challenges and opportunities brought about by the development of AI. The Hong Kong China Network Security Association (HKCNSA) is honored to invite Mr. Dicky Wong, the vice president and Director of the Infrastructure and Network Security Committee of the HKCNSA, to discuss the security issues brought about by the development of artificial intelligence, and to share the valuable experience and insights accumulated in the field of cybersecurity.


The cybersecurity industry needs to have a comprehensive understanding of the current and potential capabilities and limitations of AI. It is essential to recognize both its potential as a tool and the potential threats it may bring. AI has a wide range of applications in cybersecurity, such as threat analysis, anomaly detection, incident response, and risk management. However, AI can also be used for deception, manipulation, and attacking network systems, such as creating false data, impersonating identities, exploiting vulnerabilities, and evading defenses. Therefore, the cybersecurity industry needs to carefully evaluate the strengths and weaknesses of AI and design and implement appropriate countermeasures and safeguards.


Here are several measures that the cybersecurity industry should take to respond to the development of AI:

1. The cybersecurity industry needs to adopt proactive and adaptive approaches to address the dynamics and complexities of AI. AI can learn and develop over time and adapt to different situations and environments.

2. The cybersecurity industry needs to anticipate potential scenarios and outcomes of AI and be prepared for them. It should continuously monitor and update AI behavior and performance.

3. The cybersecurity industry needs to test and verify its AI solutions and services and ensure transparency, accountability, and ethics.

4. The cybersecurity industry needs to collaborate and coordinate with various stakeholders, including governments, regulatory agencies, customers, partners, and competitors, to establish and maintain a secure and trustworthy AI ecosystem.

5. The cybersecurity industry needs to share information and best practices and adjust and coordinate its standards and policies regarding the development and deployment of AI.

6. The cybersecurity industry needs to educate and raise awareness among the public and users, increasing their understanding of the benefits and risks of AI.

Framework for AI Governance:

When we talk about AI regulations or "regulations," the focus is generally on what we are prohibited from doing, but the emphasis on what we should enforce is lacking. Regulation should be two-way, and the world and many countries have established laws and regulations to protect and maintain social order, achieving the same goal of economic development.

As long as we use AI correctly and follow the right principles in selection and implementation, it can be a tool that creates value and promotes economic development in multiple fields.

Principles for AI Governance:

The governance framework for AI should be based on a set of values and goals that reflect the perspectives and objectives of relevant stakeholders (e.g., developers, users, regulatory bodies, and society as a whole). These principles should provide guidance and direction for the design, implementation, and evaluation of AI systems, as well as the roles and responsibilities allocation among participants. Some common principles include:

  • Human dignity and rights: AI should respect and protect human dignity and rights, such as privacy, autonomy, equality, and non-discrimination.

  • Beneficence and non-maleficence: AI should contribute to human and societal well-being and avoid or minimize harm and negative impacts.

  • Justice and fairness: AI should be fair and inclusive, avoiding or mitigating bias and discrimination.

  • Accountability and responsibility: AI should be accountable for its behavior and outcomes and accept appropriate supervision and remedial mechanisms.

  • Transparency and explain ability: AI should be transparent and explainable, providing meaningful information and justifications for its decisions and actions.

  • Trustworthiness and reliability: AI should be trustworthy and reliable, ensuring its security, reliability, and robustness.

Components of AI Governance:

  • Policies and regulations: These rules and standards define the legal and ethical boundaries and obligations for the use and development of AI, as well as their enforcement and compliance mechanisms.

  • Codes of conduct and best practices: These are voluntary and self-regulatory guidelines and recommendations aimed at promoting ethical and responsible behavior and culture among AI stakeholders.

  • Assessment and certification: Assessing and verifying the quality and performance of AI systems and providing assurance and recognition of their compliance with principles and standards.

  • Audit and monitoring: Processes and mechanisms for reviewing and monitoring the activities and outcomes of AI systems and identifying and addressing any potential issues.

  • Education and awareness: Initiatives aimed at educating AI stakeholders to understand the benefits and risks of AI and the rights and responsibilities of users and developers.

  • Privacy and data protection: Principles and practices for protecting individuals' and the public's personal and sensitive data and respecting their rights and preferences regarding the collection, storage, and use of their data by AI systems.

  • Security and reliability: Standards and measures ensuring that AI systems are protected against unauthorized access, malicious attacks, and unintended errors and ensuring consistency and accuracy in their performance and outputs.

  • Accountability and responsibility: Frameworks and mechanisms for allocating and enforcing the roles and obligations of AI stakeholders and the legal and ethical consequences of their actions and inactions concerning AI systems.

  • Fairness and justice: Values and goals guiding the design, development, and deployment of AI systems and evaluating and mitigating their impact on users and the public, particularly vulnerable and marginalized groups.

With the rapid development of AI, the cybersecurity industry needs to anticipate and respond appropriately to a range of potential risks posed by AI to ensure the stable development of businesses under the influence of AI. In the future, HKCNSA will continue to focus on the latest trends and developments in cybersecurity, providing more information on cybersecurity to its members and jointly promoting the stable development of cybersecurity.


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