Because of the unsupervised nature of their development, generative systems may “hallucinate,” meaning they generate untrue responses. Of course, whether this is a problem depends on how the user is interacting with the system. If they asked the system to write a short fictional story, Yakov Livshits then untruth is not an issue; in fact it is expected. However, if the user was asking a factual question for research, a hallucination is a failure case. Because of the multi-use nature of many generative AI systems, it can be hard for system developers to address this issue.
That societal implications of LLMs reach across different domains beyond education and that these implications also call for deeper exploration. Moreover, we bear in mind continued and emerging regulatory efforts in implementing “Responsible AI” as well as developments with multimodal AI, which we envision will shape our endeavors moving forward. Insights explored during the workshop raise issues that may merit further inquiry to better understand and address the societal implications of LLMs on education. Dealing with free expression and ideas requires that regulators exercise caution. While there are currently only a few firms in the marketplace – which may lend itself to a sandbox approach – more competitors could mean that education and public engagement might become more important than guardrails. Based on these discussions we identified key themes and areas for further inquiry.
The chatbot would produce perfect sentences that exhibited top-quality teaching techniques, such as positive reinforcement, but fail to get to the right mathematical answer. Ran Liu, chief AI scientist at Amira Learning, said that AI has the potential to support learners’ self-confidence. Teachers commonly encourage class participation by insisting that there is no such thing as a stupid question. However, for most students, fear of judgment from their peers holds them back from fully engaging in many contexts.
Chatbot Life’s 2019 chatbot report shows that education is the third biggest industry benefiting from chatbots.5 Check out our conversational AI in education article and learn the top use cases. At the Ednovate group of six charter schools in Los Angeles where Ballaret works, teachers share tips in a group chat and are encouraged to use generative AI in “every single piece of their instructional practice,” says senior director of academics Lanira Murphy. • Creating engaging and interactive learning activities, such as games and simulations, to help students understand complex concepts. • Generating questions for students to answer based on their current level of understanding and achievement. Goodman demonstrated that AI can produce coherent text that is completely erroneous. His lab trained a virtual tutor that was tasked with solving and explaining algebra equations in a chatbot format.
As Liu explained, children who believe themselves to be behind are the least likely to engage in these settings. Liang suggested that students must learn about how the world works from first principles – this could be basic addition or sentence structure. However, they no longer need to be fully proficient – in other words, doing all computation by hand or writing all essays without AI support. By focussing on the responsible and appropriate use of GenAI, we should consider why we are assessing Yakov Livshits students, what we want students to learn, and how students can demonstrate their learning. Building on UNESCO’s 2021 Recommendation on the Ethics of Artificial Intelligence and the 2019 Beijing Consensus on Artificial Intelligence in Education, the guidance promotes human agency, inclusion, equity, gender equality and cultural and linguistic diversity. The Guidance also responds to the concerns expressed at the first global ministerial roundtable on generative AI convened by UNESCO in May 2023.
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.
People may be surprised and upset to learn that information about them or content they created is being used to train or teach an AI system. If the generative AI system uses existing data corpuses with a clear use case of training AI systems this may be less of a concern. Additionally, the data that is inputted or created during interaction with the system, whether that be the outputs from the data or search terms and queries provided to the system, may be sensitive as well. A student asking for resources around gender and sexuality may be placed at risk if their teachers or school administrators get access to these queries and the student is outed to their family and community. Generative AI may exacerbate these considerations if those terms feed more heavily into the development and evolution of the system than they do for traditional search engines.
Generative AI is a digital technology that can quickly create new and realistic visual, textual, and animated content. In other articles, we investigated its use cases in different sectors, such as healthcare and banking. While other technologies like conversational AI and robotic process automation (RPA) are implemented in education, generative AI is not properly implemented in education. This article explains the top 6 potential ways to use generative AI in education. Generative AI has the potential to be incredibly useful, but societal norms for when and how it should be used are still very much in flux.
You will likely only have time for one or two of these “teaching moments.” You will need to edit these slides to remove the instructions and to provide your own examples. Slides with a stone-coloured background provide guidance for the educator and should be deleted. This lecture could be delivered live in induction week, later in term 1 within a core module, or circulated to students as an asynchronous video. So, is generative AI a fad or a critical enabler of future institutional success? This article will examine the past, present, and future of generative AI in education. Our goal is to provide you with everything you need to explore and understand generative AI, from comprehensive online courses to weekly newsletters that keep you up to date with the latest developments.
You should delete the categories that do not apply to your module/programme. The section also includes guidance for students on how to acknowledge their use of GenAI, if this has been permitted in the module/programme. Option 1 (slides 13-14) is an example mentimeter discussion of student perspectives on the use of different tools in their disciplinary context.