Blog Layout

How Schools and Universities can use Generative AI

Nina Habicht • Dec 29, 2023

This article outlines how schools and universities shall approach the recent generative AI developments.


Why educational institutions are hit by Generative AI?


Many schools and also universities are confronted with students using Generative AI tools like ChatGPT. However, often regulations and rules are not available yet or are in an implementation phase. It is a fact that students cannot be controlled when it comes to using ChatGPT. Some might even already know more than their parents or teachers when it comes to ChatGPT.


Secondly, universities are disrupted by a technology which makes knowledge available. Harvard started building their own Generative AI tutors, avatars emerge in the fields of teaching that can significantly reduce costs and scale online trainings faster.



The World Economic Forum event writes about "Why AI makes traditional education models obsolete"

Create creative tasks for students with the help of Generative AI tool ChatGPT.


How Generative AI can be used by teachers?


Generative AI can be used for different tasks:


1) Analyse student's work: Tools like AI-based grammar and style checkers can help students improve their writing.

2) Content: Generate homework for the students

3) Creativity: Explore new ways of learning + executing homework. See how we prompted ChatGPT to create new ways of homework above.

4) Examination/Grading: AI can grade objective assignments like multiple-choice tests, allowing teachers to spend more time on qualitative feedback.


We experience in our AI trainings that we create a very new way of learning. Rather than focussing on traditional topics (e.g. French, programming, art) students will focus on a real-world project work and execute this with the help of AI. This may again include several "classical" skillsets needed (e.g. translate in French, program a code, design a nice picture for the website with DALL E).


Will ChatGPT replace exams and essays at schools?


There will be a trend towards more experiential assignments based on real-world challenges as described above. Students will learn to embrace changes aand solve a real problem.


WEF refers to a "durable skills-based model" which is better positioned in an AI era:


  • "Resilient to mindless AI use: Active learning techniques (debates, role-play and discussions) are dynamic, social and fast paced, requiring students to show up and interact, as well as creatively and critically “think on their feet”. Authentic and experiential assignments connected to real-world issues also require them to apply their specific skills to address a specific contemporary challenge faced by a specific (local) partner. AI may be able to provide inspiration and suggestions but not be mindlessly used to solve such problems.
  • Cultivates skills AI lacks: AI tools may be impressive, but they still lack genuine creativity, ethical reasoning, emotional intelligence and the ability to work, lead and negotiate with others. By explicitly training students on such skills we ensure they can do what AI cannot. And by training them on still other skills (such as critical thinking), we ensure that they can effectively and ethically use AI as well as critically evaluate its output."



Should schools allow the usage of AI tools and ChatGPT?


It is essential for students to learn about AI tools like ChatGPT and the underlying technology of large language models (LLMs). Those who can utilize AI effectively will have an advantage over those who cannot. Banning such tools could be detrimental to the future of many people as it is expected to be able to work with these tools (as it is in 2022 expected to know how to build a website or google, literally be digital knowledgeable today).


Providing access to learning materials in an equal and inclusive manner is important for the future of humanity.


Is ChatGPT compromising common sense?


It is important to teach students about the fact that ChatGPT and large language models are "calculators for words" and that the better users of such Gen. AI tools are subject manner experts (e.g. in programming or writing), the better they are able to judge the output of such models. Common sense and critical thinking are key elements hat is emphasized in a school or education context. This can be done by integrating ChatGPT and information literacy actively into your lessons.


Practical Exercise in the class: Let students search for the original sources of the mentioned information in a generated text by teachers. Very importantly: discuss the solutions delivered by AI. Do it iteratively: Discuss and question the answers given by the AI together with the class.



Should schools and universities use AI detectors?


A recent Stanford study showed that detecting AI generated text is a very hard task and that detectors are not reliable:


1) Seven AI detectors flagged 20% TOEFL essays as "AI generated" although they were not.
2) AI detectors are "near-perfect” in evaluating essays written by U.S.-born eighth-graders.
3) They can be gamed as many llms can be prompt engineered to make the text more lexical rich in the answers. This cannot be detected yet.

Despite these facts, there are numerous tools available in the market, particularly for addressing fake news:


  1. Fact-Checking Websites: Websites like Snopes, FactCheck.org, and PolitiFact are dedicated to verifying stories and claims.
  2. Media Literacy Tools: Tools like NewsGuard provide browser extensions that rate the credibility of news sites.
  3. AI-Based Tools: AI systems like OpenAI's GPT-3 have been used to develop tools that analyze news for authenticity.
  4. Reverse Image Search: Services like Google Reverse Image Search can verify the source and context of images.
  5. Educational Platforms: Websites like Checkology offer courses to teach users how to identify misinformation.
  6. Social Media Verification: Some social media platforms have their own fact-checking and content review systems.


It's important to use a combination of these tools and to also rely on critical thinking and cross-referencing with reputable sources for the best results in detecting AI generated or fake news. This will become more and more difficult as AI contents fill the internet.



Source: Generative AI in Leadership Training, Isabell Welpe. Image: created with DALLE 3


What are the risks of Generative AI for society that need to be taught at schools?


While ChatGPT may be enticing to utilize, it is important for teachers and students to be aware of the potential risks involved. ChatGPT acts like a "word calculator" and is not primarily designed to solve math problems, which means it still can provide incorrect answers. Thus, it is important to develop critical thinking skills at schools.


Since LLMs predict the next likely word based on an understanding of the preceding sentences, they can still convey incorrect information that might appear plausible at first glance.


Address Fake news: it is an issue that must be addressed during lessons. Additionally, fictitious influencers - AI assistants designed to accumulate followers and provide entertainment - already exist. It is essential to inform students, parents, and relatives about the presence of virtual assistants on phone calls and social media platforms.


The state of Gen. AI Governance in education


Fewer than 10% of schools (n =450) and universities currently have formal guidelines on AI according to UNESCO. Its new guidance suggests eight specific measures educational institutions could adopt to ensure “quality education, social equity and inclusion". This full guideline can be downloaded here.

Do you need support with Generative AI trainings in your class or school?


We are here to support you: contact us today.


Need support with your Generative Ai Strategy and Implementation?

🚀 AI Strategy, business and tech support 

🚀 ChatGPT, Generative AI & Conversational AI (Chatbot)

🚀 Support with AI product development

🚀 AI Tools and Automation

Get in touch
Top ChatGPT Prompts and Prompt Engineering for Product Managers
By Nina Habicht 10 May, 2024
Top ChatGPT Prompts and Prompt Engineering for Product Managers
How Does Perplexity AI Work?
By Nina Habicht 04 May, 2024
Article about Perplexity AI and how to properly use it. We highlight the difference between ChatGPT and Perplexity AI.
How to choose between ChatGPT, Claude, Copilot and Gemini
By Nina Habicht 04 May, 2024
How to choose between ChatGPT, Claude, Copilot and Gemini. Please find our ultimate guideline on how the models differ and which llm is strong at which task.
How to strategically use GPTs from OpenAI
By Nina Habicht 03 May, 2024
This blog explains how gpts can be used as a part of your Generative AI journey and exploration towards your Ai strategy.
Why implementing ai tools is not an ai strategy
By Nina Habicht 03 May, 2024
This post explains why implementing ai tools without any strategy and business view can be detrimental and lead to not successful ai projects.
Generative AI in 2024, Investment areas in 2024
By Nina Habicht 01 Jan, 2024
This post is abou the major generative AI trends and investment areas in 2024
Supports with the definition of GPTs, alternatives and options to build own chatbots or assistant
By Nina Habicht 25 Dec, 2023
A comprehensive Guide to Alternatives of GPTs and Assistant API from OpenAI
By Nina Habicht 26 Nov, 2023
Many companies are reluctant when implementing llm-based products because they fear bein confronted with high costs. Especially for medium-sized companies which have not the ressouces or enough capacity to deploy and oprimize their AI models nor to set up an own infrastructure with MLOps. As described in our article about sustainability of Gen. AI applications , cloud and performance costs of running an llm can become very high. What are the cost types when implementing OpenAI or other llms? T here are four types of costs related to llms: Inference Costs Setup and Maintenance Costs Costs depending on the Use Case Other Costs related to Generative AI products What are inference costs? An llm has been trained on a huge library of books, articles, and websites. Now, when you ask it something, it uses all that knowledge to make its best guess or create something new that fits what you asked for. That process of coming up with answers or creating new text based on what it has learned is called inference in LLMs . Usually, developers would call a large language model like GPT-4. But here comes the "but": usually not only large language models account to the total costs when running the final product. To explain: LLMs can be used to classify data (e.g undestand that the text talks about "searching a new car insurance"), for summarization, for translation and for many other tasks. Download the ultimative Gen. AI Task Overview to learn where llms make sense:
Checklist to implement Generative AI in your company
By Nina Habicht 24 Nov, 2023
this article helps companies like enterprises and sme to successfully implement generative AI by providing best-in-breed frameworks.
By Nina Habicht 01 Nov, 2023
In this blog you will learn about the alternatives to ChatGPT and OpenAI. Where is Bard better than ChatGPT? Bard is the response to OpenAI's ChatGPT. What makes Bard so different to OpenAI? It is free! So you can try it out here whereas ChatGPT costs $20 per month. Another advantage is the microphone on the desktop version to directly speak in your question and get a response. Bard has internet access whereas ChatGPT you need to jump from one service (Web Browsing) to the other Bard covers far more languages (265 as of October 2023) Some drawbacks: it is not able to generate pictures. With ChatGPT DALL E-3 you can generate pictures. Bard only offers you a nice description. Where is Claude better than ChatGPT? Claude is the version of ChatGPT developed by the company Anthropic. This tool is currently accessible only in the UK and US, and not yet available in Switzerland. You might consider using Nord VPN to explore its functionality in your country. Claude has one big advantage to ChatGPT: It can process more "context" ( Generative AI from A to Z ), meaning the input token (100 token equals around 75 words) can be up to 100'000 tokens (75'000 words!). GPT-3 has a limit of 4096 tokens (3072 words) and GPT-4 of 8192 tokens (= 6000 words). So when you want to upload huge files, use Claude.
Show More
Share by: