In this article, we propose the R2GQA system, a Retriever-Reader-Generator Question Answering system, consisting of three main components: Document Retriever, Machine Reader, and Answer Generator. The Retriever module employs advanced information retrieval techniques to extract the context of articles from a dataset of legal regulation documents. The Machine Reader module utilizes state-of-the-art natural language understanding algorithms to comprehend the retrieved documents and extract answers. Finally, the Generator module synthesizes the extracted answers into concise and informative responses to questions of students regarding legal regulations. Furthermore, we built the ViRHE4QA dataset in the domain of university training regulations, comprising 9,758 question-answer pairs with a rigorous construction process. This is the first Vietnamese dataset in the higher regulations domain with various types of answers, both extractive and abstractive. In addition, the R2GQA system is the first system to offer abstractive answers in Vietnamese. This paper discusses the design and implementation of each module within the R2GQA system on the ViRHE4QA dataset, highlighting their functionalities and interactions. Furthermore, we present experimental results demonstrating the effectiveness and utility of the proposed system in supporting the comprehension of students of legal regulations in higher education settings. In general, the R2GQA system and the ViRHE4QA dataset promise to contribute significantly to related research and help students navigate complex legal documents and regulations, empowering them to make informed decisions and adhere to institutional policies effectively. Our dataset is available for research purposes.

When legal regulations get ahead of technological developments, the progress of society may be constrained. Conversely, when technological developments run ahead of legal regulations, unregulated new technologies may harm society, defying technological development's fundamental purpose. This is exactly what has happened in the world in the past decade, as technological developments have far outpaced legal regulations. Worse, traditional legal frameworks focus on the relationship between people, whereas we must develop a legal framework to regulate relations between people and intelligent machines in the current era. Integrating AI technologies into human society imposes unique legal challenges without any precedence.

Various types of simplifications used for the purposes of advertising became the prerequisite for the introduction of regulations. There are situations where the options of Advanced Driver Assistance Systems (ADAS) and the benefits of their use are described in promotional materials in a way that suggests that they enable driving in autonomous mode, without the need for the driver's participation, while the currently offered vehicles do not exceed the L3 level according to the SAE J3016 standard, so they require the attention of the driver. In addition, the context of responsibility for a road accident, which according to legal regulations belongs to the driver, is not without significance.

Consumers often don't understand AI's power and impact. "AI is just everywhere in our lives today and the average consumer has no clue how it works or what undermines the technology," Roetzer told me. We need help understanding what responsible AI looks like. Tech companies don't have all the answers. The burden of building and using AI responsibly falls on technology companies, which don't always have incentives to build systems that prioritize people over profit.

In our understanding, the question of who owns intellectual property rights on AI-related works is also important when determining who is liable for AI-caused harm. For that reason, further development of legislation in that direction is expected. As we mentioned before, one of the main characteristics of AI is the use (collection, analysis) of data. Personal data is included in this. Some experts have opined that AI systems can develop more quickly in jurisdictions where there is less regulation on the use and protection of personal data--or where it is not regulated at all. This is related to the fact that AI needs to use data to achieve the established tasks. The EU is the realm of the General Data Protection Regulation (GDPR), which aims to protect personal data against illegal use. The EU, in light of the GDPR, has already prepared a list of prohibited practices of AI.

Did you miss a session at the Data Summit? Private investors are pouring more money into AI startups than ever before. At the same time, AI systems are becoming more affordable to train -- at least when it comes to certain tasks, like object classification. Troubling, though, language models in the same vein as OpenAI's GPT-3 are exhibiting greater bias and generating more toxic text than the simpler models that preceded them. Those are the top-level findings of the 2022 AI Index report out of Stanford's Institute for Human-Centered AI (HAI), an academic research center focused on the human impact of AI technologies.

The irony of the ethical scandal enveloping Joichi Ito, the former director of the MIT Media Lab, is that he used to lead academic initiatives on ethics. After the revelation of his financial ties to Jeffrey Epstein, the financier charged with sex trafficking underage girls as young as 14, Ito resigned from multiple roles at MIT, a visiting professorship at Harvard Law School, and the boards of the John D. and Catherine T. MacArthur Foundation, the John S. and James L. Knight Foundation, and the New York Times Company. Many spectators are puzzled by Ito's influential role as an ethicist of artificial intelligence. Indeed, his initiatives were crucial in establishing the discourse of "ethical AI" that is now ubiquitous in academia and in the mainstream press. In 2016, then-President Barack Obama described him as an "expert" on AI and ethics. Since 2017, Ito financed many projects through the $27 million Ethics and Governance of AI Fund, an initiative anchored by the MIT Media Lab and the Berkman Klein Center for Internet and Society at Harvard University.

The UK government is among a group of countries that are attempting to thwart plans to formulate and impose a pre-emptive ban on killer robots. Delegates have been meeting at the UN in Geneva all week to discuss potential restrictions under international law to so-called lethal autonomous weapons systems, which use artificial intelligence to help decide when and who to kill. Most states taking part – and particularly those from the global south – support either a total ban or strict legal regulation governing their development and deployment, a position backed by the UN secretary general, António Guterres, who has described machines empowered to kill as "morally repugnant". But the UK is among a group of states – including Australia, Israel, Russia and the US – speaking forcefully against legal regulation. As discussions operate on a consensus basis, their objections are preventing any progress on regulation.