Recently, an article about mandatory insurance product subscription for high-risk artificial intelligence technology developers has been posted in the insurance research community. The Korea Insurance Research Institute held a seminar on the expansion of the use of artificial intelligence and the challenges of the insurance industry and discussed high-risk artificial intelligence. Here, 'ai in the high-risk field' refers to ai used in fields that have a great influence on individuals, such as hiring, credit rating, and loan review. The problem of subscribing to insurance products for high-risk ai is to prepare for errors that may occur through ai. If the medical community's ai technology causes incorrect results for patients who are subject to the service, the issue of compensating for it through pre-subscribed insurance is being discussed. So today, we're going to look at some of the high-risk areas called AI, and we're going to look at the AI regulation law to prepare for it.
What is high-risk field ai? It mainly represents the potential risks that artificial intelligence can pose when it exceeds a certain level. It can be out of human control, operate in unpredictable ways, or have unintended consequences. This can include many aspects.
1. the control problem of strong artificial intelligence Strong artificial intelligence refers to systems with intelligence beyond the human level. When these systems are out of control, unexpected consequences can occur. For example, robots can arbitrarily interpret human instructions or execute them in an incorrect way.
2. Self-replicating AI With self-replicating capabilities, artificial intelligence can create systems that are similar to them. If this goes out of control, intelligence can continue to grow exponentially, with unexpected consequences.
3. maliciously used ai The ai system used for malicious purposes can be used for a variety of malicious behaviors such as cyberattacks, information manipulation, and personal information infringement.
4. Data bias and bias The ai system relies on training data, which, if biased or inaccurate, can lead to unexpected results. In particular, if biased data is used, ai can enhance or enlarge such a bias.
5. a problem of human interaction When a powerful ai system interacts with humans, communication problems or conflicts with human values and ethics can arise.
Various measures are needed to reduce these risks, such as developing strict ethical regulations and standards, effective control and safety mechanisms. Related research and development are ongoing, and cooperation between industrial academia and government is required.
ai regulatory measures As a result of discussing the potential risks and mitigation measures of artificial intelligence globally
We have adopted a declaration to evaluate scientifically and objectively the risks that may arise from ai and to find ways to safely utilize ai technology.
Currently, AI regulation is necessary to control and safely utilize its ethical, social, and economic impacts as AI technology advances. Below are some general measures for AI regulation.
1. Strengthen transparency and accountability Efforts should be made to increase transparency so that we can understand how the ai system works. Developers and operators should be responsible for the outcome of the ai system.
2. Personal Information Protection Strict privacy policies should be established for the data collected by the ai system. Particular attention should be taken when dealing with sensitive information.
3. Bias and fairness measures In order to ensure that the ai model is not biased, it is necessary to introduce a method of using various data and detecting and correcting bias when developing the model, an effort to prevent discrimination against specific groups or individuals.
4. Safety and Security Regulations Regulations are needed to ensure the safety of the ai system. It is necessary to protect the system from malicious attacks and to strengthen security so that the system does not behave in unexpected ways.
5. Ethical Standards and Education Ethical education for ai developers and users should be strengthened. Guidelines for compliance with ethical standards should be established and actively required.
6. regulatory cooperation Cooperation between regulatory agencies is important internationally and domestically. Due to the nature of AI technology, cross-border cooperation is necessary.
7. Citizen Participation and Transparency Transparency must be maintained to allow citizens to participate in decisions about the ai system. Open feedback and input on regulation and decision-making processes are needed.
This is my personal opinion piece. It may have nothing to do with the facts, and I will end this article here. Thank you.