From utilizing deep learning in tracking devices to help manage sleep routines in infants to computer vision-driven retail stores, AI has found its way into every possible industry sector. This article will cover a couple of highlights in which despite its risks and challenges, AI is transforming society. First up: Education.  

Education and AI

Education and AI have seen extensive press coverage as of late, not just from a curriculum development standpoint but also from the perspective of how Generative AI is being utilized in teaching and learning. 

With the Global AI in the education space expected to grow from  $4.25bn in 2023 to over $20.65bn in 2028 with a predicted Compound Annual Growth Rate (CAGR) of 45.9% between 2023 to 2028, [1] this particular application of AI is going to create a substantial pressure test in amongst an already fragile Computing curriculum. 

ChatGPT (Chat Pre-Trained Generative Transformer), the Generative AI chatbot founded by OpenAI back in November 2022 [2] has been highly controversial in education, with some universities banning the technology over academic integrity fears. [3]  

Despite the dark clouds, ChatGPT in education has many advantages. Take content creation, for example: an integral part of teaching but a highly resource-intensive process. Whether it be creating a lesson plan, practicing problems on a new piece of theory, or explaining abstract topics in a simplified way, ChatGPT is an incredibly powerful tool. Instead of talking about  it, here are some examples:  

A computing science study guide 

Imagine a teacher is preparing their GCSE Computing Science students for an upcoming test and wishes to create a study guide. Simply input the command as follows: 

Here’s ChatGPT’s output (redacted due to its length): 

Whilst for some it may not feel groundbreaking to create something on the surface that looks simple, this use case gives teachers the chance to focus their energies on inspiring the students with the content instead of being bogged down by lesson planning.  

ChatGPT and practice problems 

Following the above study guide idea, teachers can go a step further and ask  ChatGPT to create practice problems in a particular area. Here’s an example set of questions  on the topic of Computer Software:

And the output from ChatGPT gives (redacted due to length): 

From the above, say students have been revising away using the resources created above but some are struggling with certain topic areas in Computer hardware: ChatGPT can help in explaining topics on a more simplistic level. Let’s use the example of Random Access  Memory (RAM):

ChatGPT’s reply is as follows:  

The examples outlined above are just one of many ways ChatGPT has found its way into education, and it’s only a matter of time before leaner and smarter ways of integrating the chatbot into education are discovered. 

What’s key is in ensuring the technology can be deployed whilst upholding the principles of academic integrity. The current worry is the pace of growth in generative AI is outstripping teachers' capability to understand how it can be best brought into a classroom whilst maintaining academic integrity, and with governments only able to provide finite levels of advice academia-industry relations are more important than ever to guide educators what’s going to the challenging period ahead. 

AI in healthcare 

Let’s now turn to another transformative application of AI: Healthcare. With a forecasted  CAGR of 51.9% between 2022 - 2030 and a market size forecasted to reach shy of  $12.22bn by 2030 [4], it’s one of the most exciting spaces AI-application-wise. 

When it comes to life and death decision-making, AI with such a high level of data integrity put into the mixture makes things very interesting. For example, the utilization of AI in medical diagnostics is one of these areas very much in the spotlight. Take breast cancer identification as an example.  

Breast cancer diagnosis 

In 2018, Baidu research announced the development of a deep learning algorithm that from initial testing, outperformed human pathologists in its ability to identify breast cancer metastasis [5]. 

Through the use of Convolutional Neural Networks (CNNs), the network was trained by thousands of tiny images split from 400 images. From this 200,000 of the smaller images were selected at random with analysis conducted to classify each of the smaller photos as well as neighboring cells. [5]  

From the Free-Response Receiver Operating Characteristic (FROC) score (this is a  measurement taking into account the average detection sensitivity with 6 predefined false positive rates per slide), it was found Baidu’s algorithm achieved a score of 80.9: higher than the 72.4 achieved by human pathologists. [5] 

When the findings came to light,  Computer Vision was touted as one of the most important and promising areas of Artificial  Intelligence, and to this day, many more exciting medical applications have come to light.  

Workflow automation 

Medical aspects aside, the COVID-19 pandemic resulted in a transformative shift in how we think of and utilize technology. AI-related, another area where AI is supporting healthcare isn’t clinical, but administrative. 

In summary, workflow automation utilizing AI could result in savings of $18 billion in areas ranging from utilizing voice-to-text transcriptions to prescribing medication and ordering tests [6]. 

For example, a partnership between IBM Watson and Cleveland Clinic saw the use of Natural Language Processing (NLP) to comb through thousands of medical documents to inform patient treatment plans. More recently, the partnership was taken to new heights through the deployment of a quantum computer to push further the boundaries of healthcare research. [7] 

Conclusions and thoughts 

Education and healthcare are just two of many examples of the transformative applications of AI. Within healthcare, as more groundbreaking applications come into play there’ll be increasing pressure in ensuring the protection of patient confidentiality, whilst with education there’ll be an increasingly challenging balancing act of academic integrity and AI. 

How both these areas continue to produce groundbreaking innovation in amongst these challenges will be an exciting story to watch unfold.  


[1] Global AI in Education Market Size: Inc, G.M.E. (2023). Global AI in Education  Market Size & Analysis. [online] GlobeNewswire News Room. Available at: https:// Education-Market-Size-Analysis.html. 

[2] ChatGPT History: Heaven, W.D. (2023). The inside story of how ChatGPT was built from the people who made it. [online] MIT Technology Review. Available at: https:// built-openai/. 

[3] ChatGPT Banned over Plagiarism fears: sciencespo_author, sciencespo_author  (2023). Sciences Po bans the use of ChatGPT without transparent referencing. [online]  Espace Presse Sciences Po. Available at: the-use-of-chatgpt/. 

[4] AI in Healthcare market: Future, M.R. (2023). Artificial Intelligence in Healthcare  Market Size to Hit USD 12.22 Billion by 2030 at 51.9% CAGR – Report by Market  Research Future (MRFR). [online] GlobeNewswire News Room. Available at: https:// Healthcare-Market-Size-to-Hit-USD-12-22-Billion-by-2030-at-51-9-CAGR-Report-by Market-Research-Future-MRFR.html [Accessed 20 Jul. 2023]. 

[5] Baidu Research Cancer Recognition: VentureBeat. (2018). Baidu Research’s breast cancer detection algorithm outperforms human pathologists. [online] Available at: https:// pathologists/. 

[6] Workflow Automation in Healthcare: Marr, B. (n.d.). How Is AI Used In Healthcare -  5 Powerful Real-World Examples That Show The Latest Advances. [online] Forbes.  Available at: healthcare-5-powerful-real-world-examples-that-show-the-latest-advances/? sh=5f99d395dfbe [Accessed 20 Jul. 2023]. 

[7] Cleveland Clinic and IBM Quantum Computer: IBM Newsroom. (n.d.). Cleveland  Clinic and IBM Unveil First Quantum Computer Dedicated to Healthcare Research.  [online] Available at: Unveil-First-Quantum-Computer-Dedicated-to-Healthcare-Research.