As machine learning and artificial intelligence technologies shape our current era, it is important to note that there is a dire need for regulatory intervention in the field. It isn’t surprising that although the field of AI is supposed to “do good” for the advancements of human problems, there is a downside to all technological innovations. While several AI systems pose minimal risk at present, they need to be assessed. Several regulations/acts have been drafted and released across the world to target the potential risks of the technology.
While the EU AI act was one of the very first regulations to be drafted, 世界其他地方, 包括中国和美国, 是不是落后太多了. The EU AI act is targeted at managing risks with systems related to law enforcement, education and immigration with the regulation aiming to assess them before being put into the market for use. If one were to look at the regulatory impact, companies that fail to comply will be fined 6% of their annual turnover. Nearly 20-25% of the global AI market comes in from the EU region, 因此欧盟人工智能法案不容忽视.
There are many reasons regulatory intervention helps AI systems and their impact on the public. First and foremost, regulation is needed to protect the privacy of users and their data. This is especially true for data-heavy algorithms, with potential to remove bias and discrimination. Regulatory frameworks need to enforce mechanisms whereby bias is not purposefully injected and ensure that naturally occurring biases are removed. Then there are human rights and safety concerns, where deep fakes can be avoided or misinformation is not spread. 最后, it is imperative that AI-led development does not monopolize and favor certain human populations while overlooking the majority whose data isn’t used to train algorithms.
As the saga of regulatory intervention begins, governments around the world will need to collaborate and establish broad regulatory frameworks. There is also a dire need for education and knowledge sharing on developing machine learning techniques and algorithms. 在当前环境下, 关于欧盟人工智能法案, no foundational LLM (Large Language Model) complies with its clauses. 中国’s regulation focuses on control of content and is not too concentrated on the risks. These frameworks need to be inclusive and adaptive, as well as be updated from time to time.
Furthermore, we know that regulation, bills and laws often fail to adapt to changing technology. Machine learning and artificial intelligence is a rapidly evolving field, with new techniques and applications emerging faster than you would imagine. 新的挑战, 风险和机遇不断涌现, and we need to remain agile/flexible enough to deal with them. Keeping up with the advancements and regulating cutting-edge technologies can be challenging for governing bodies. This needs to be factored in as regulatory frameworks for AI continue to evolve.
编者按: For further insights on this topic, read 浙江梅农’s recent Journal article, 新人工智能法规的潜在影响, ISACA杂志，第1卷，2024.
