Fully personalised education

In 1984, following an extensive study of contemporary teaching and learning methods, the distinguished educational psychologist Benjamin Bloom discovered a groundbreaking technique for improving learning outcomes by a factor of two standard deviations (two sigma). BloomsIt consisted of two pillars. 

1. The first was called “mastery learning”. This required each student to achieve full mastery of a topic before moving on to a more advanced subject. 

2. The second was simply referred to as “1-on-1 tutoring”. It refers to the process of guiding each student to mastery by prescribing for them specific exercises that would help them fully assimilate the subject.

Despite the forcefulness of Bloom’s findings, his methods have not been generally adopted by educational institutions. Achieving mastery takes a long time. Furthermore, providing every student with the individual tutoring to achieve this mastery requires moving away from the customary hour-long teaching blocks, imposing significant additional costs on education providers.

With the advent of self-paced online courses and tools like ChatGPT, however, this situation is poised to change in the years to come.

“AI is the most obvious solution here," says Lukas Kaminskis. "It enables students to avail themselves of a world-class teacher that makes zero mistakes and is able to teach almost any subject. Furthermore, it can adjust to each student’s goals, level of knowledge, and rate of study to help them get the most out of their education."

Targeted and tailored feedback

Another important characteristic ChatGPT possesses is the ability to accurately evaluate learner's output and provide targeted feedback.

"It can track a students’ learning history and pinpoint specific weaknesses," Lukas explains. "Then it can provide feedback and recommend courses that will close the gaps in their knowledge.”

AI is already successfully closing educational gaps that would otherwise be difficult to spot and properly address. 

For instance, online course providers like Coursera are using AI to register frequently recurring mistakes that students make in their homework assignments. In addition to alerting the course teacher of the difficulty their students are having with the material, it provides the latter with customised hints and immediate feedback. In this way, students gain a correct understanding of the subject without having to wait for the teacher’s input. 

This means tools like ChatGPT will be able to gain a picture of individual students and what their strengths and weaknesses are. Furthermore, it now has the ability to accurately and clearly explain these issues so students understand how to move forward.

Writing assistance

ChatGPT is already being used by students to brainstorm ideas, write and revise outlines for essays, come up with catchy and descriptive titles, and much more. 

Being able to interact with it using natural language provides endless possibilities for reducing the preparatory grunt work that goes into many written projects (for example, compiling a literature review). Learners can then maximising the time spent on high value tasks like analysis. 

Here's how that could work in practice:

• A student writes a prompt for ChatGPT outlining a specific topic or thesis statement and requesting a list of ideas for an essay. This step can be repeated as many times as needed, until the student gets a satisfactory result. 

• With a general idea now at hand, the student could further ask for an outline, listing all the types of information the essay should include. 

• If, on the other hand, the student already has an outline based on the idea suggested in the previous step, the model could be used to generate a rough first draft of the essay itself. 

• Treating this as a starting point, the student could then write a second draft.

• And once the student has a final version of the essay written up, they can request suggestions regarding grammar, clarity and conciseness.

Since ChatGPT remembers its previous interactions with every individual user, it can base its suggestions on common mistakes that each student makes, and can also track each students’ progress in terms of their writing skills.

Foreign language learning

ChatGPT could be used for translating written text between different languages. Although English is preferred, ChatGPT does understand other languages too, and its capacity in this regard will improve over time. 

Students could, therefore, use it for translating foreign-language materials into their native language within seconds. This can assist with comprehension. 

Other language learning applications ChatGPT could be used for include:

• explaining grammar;

• reviewing and correcting written assignments;

• providing vocabulary exercises;

• providing instruction on how to pronounce words;

• re-writing existing articles in Simple English (or other languages);

• generating custom dialogues and stories based on a student’s instructions, which could be helpful in understanding the nuts and bolts of the target language.

Additionally, the model could be used to provide real-time translation during language classes, allowing students to directly converse with native speakers of the target language.

This list is far from exhaustive. And the model’s potential for aspiring polyglots is huge, as evidenced by the countless articles written by language teachers and learners on how to use ChatGPT for learning and practicing languages. Among the many courses on ChatGPT offered by Udemy, there are already several (for example, here and here) dedicated specifically to using it for this same purpose.

Streamlined research and review

Many commentators online have noted that ChatGPT is quite good at generating abstracts and summaries of academic/research literature. The scope of such reviews is limited, at least for now, by the model’s incomplete access to publicly available, let alone paywalled, scientific papers. This, however, is likely to be remedied in the future via agreements made with universities, research centres, and other third parties.

Poring over dozens, if not hundreds, of papers and/or other primary sources is both time-consuming and often tiresome. Outsourcing all, or a part, of this process to an algorithmic data aggregator like ChatGPT would save many hundreds of hours that researchers could spend much more effectively doing what only humans can do. 

Moreover, the model can provide summaries of texts, such as websites and books. This would be highly useful in cases where a specific text is already known to the user – editing and supplementing a summary usually takes much less time than writing one from scratch.

In addition to condensing existing literature, ChatGPT is able to explain it at different levels of comprehension. For instance, a user can ask the AI tool to break down the concept of a black hole “suitable for a 5th grader” and get a pithy and concise definition. Afterwards, the user can choose to increase the level of complexity and continue learning about the topic.

Will ChatGPT provide false, dangerous or biased information?

As a tool, ChatGPT is still very new. And this means it is far from perfect. These flaws have the potential to cause all manner of problems for its users. 

For instance, the fact that it draws upon the internet for all of its output makes the model prone to making plausible-sounding but incorrect or nonsensical statements in a highly authoritative tone. This became apparent as early as December 2022, when Stack Overflow banned the use of ChatGPT for generating answers to questions, citing the ambiguous nature of its responses.

No less importantly, the model’s training data suffers from algorithmic bias. This can be seen in the descriptions it gives of people. 

OpenAI does not allow ChatGPT to express political opinions, and filters queries through a company-wide moderation API. This is intended to prevent offensive outputs from being presented to and produced by the model. So far, however, these measures have proven to be insufficient. In one instance, ChatGPT generated a rap that portrayed women and scientists of colour as inferior to their male and Caucasian peers. 

These examples relate to demonstrable and open prejudice like racism or homophobia. However, bias can also be more subtle. For example, imagine a 10th-grader researching different economic models. The way these models are explained can impact value judgements made regarding the efficacy and morality of these approaches. It remains unclear how ChatGPT will provide objectivity or neutrality in cases like this.

Dangerous content is another risk. A Twitter user shared how they were able to bypass content-moderation with some clever prompt engineering, convincing the model they were OpenAI itself. This allowed the user to get step-by-step instructions for creating a Molotov cocktail, and have the model expounding pro-Nazi arguments.

Will it distort public discourse?

Because it is freely accessible to everyone and has a flawed knowledge base, plus the vulnerabilities we have just mentioned, ChatGPT has the potential to distort public discourse.

Media commentators have expressed concern regarding its potential to harm democratic practices by unleashing a flood of automated partisan comments. It could also reduce the overall credibility of most online content by making it difficult to distinguish the genuine from the algorithmic. 

Again, the dangers in an educational context become clear when you imagine a sociology or history student using this tool for research. Which sources, and whose ideas, are impacting the answer ChatGPT generates in what are likely to be highly contested areas? 

Will it facilitate cheating, or inhibit the development of key skills?

ChatGPT is able to write lucid, well-researched, and copiously referenced articles. This has prompted some academics to call it “the death knell for conventional forms of educational assessment”. The fact that the tool has been shown to be capable of gaining an MBA from Wharton is proof of just how disruptive it is likely to be.

Playing around with the prompt, many teachers have managed to produce essays that would yield students a good grade if presented as their own. This is obviously problematic, but is hardly a new problem. Students already have access to “essay mills” turning out high quality text for a modest fee. 

In addition, essays authored by ChatGPT still bear certain trademark problems. These include non-existent quotations, false statements based on assumptions that no human would make, and irrelevant references that only make sense in light of the model’s own internal, predictive dynamics.

The extent to which students will use ChatGPT to write their essays for them from the ground up will ultimately depend on at least two things. 

1. The model’s future accessibility to the public, as well as the price that users might have to pay for it should OpenAI eventually decide to commercialise it (it is already working on the roll out of ChatGPT Plus, a paid version of the tool that offers better accessibility at peak periods.)

2. Efforts made by educators to shift away from prompt-based written assessments in favour of querying students in a way that fosters critical thinking and long-term retention of learning materials.

“In the last 100 years, almost no progress has been made to improve the assessment and student knowledge-testing mechanisms on a grand scale. As a result, we have 20th-century assessment mechanisms testing 21st-century skills”, Lukas Kaminskis noted.

To reduce these risks, OpenAI is now developing a watermark for all content produced by the model. It has also launched a tool for detecting AI-generated content.

Even if students don't use ChatGPT for writing their essays, even using it as a tool to support their writing process could be problematic. Will they miss out on the development of important research skills? Will their own writing suffer with AI handling much of the structuring and organisation? Only time will tell what happens in these areas.

Social isolation and homogenised learning

Like all online learning tools, ChatGPT has the potential to reduce human interaction between students and teachers. Will it diminish the availability of personalised feedback that as yet only humans are able to provide?

Lower classroom participation rates are also likely to constrict the avenues people have for meaningful dialogue and exchange of ideas. Given the highly social nature of human reasoning and the unmatched richness of face to face communication in real life, subordinating all of education to never-quite-fully-reliable, proprietary algorithms that people use at home, alone, could have serious consequences for society at large.

It should also be said that if all students are given the same information and feedback based on the model’s output, this might crystallize into a one-size-fits-all approach to learning. Without opportunities to learn from (and bounce ideas off of) each other, students could become rather stereotyped and rigid in their thinking.

False or biased information

This might turn out to be the most difficult question to properly address. Since all that ChatGPT has to work with is data sets cribbed from the internet, the problem ultimately rests with society itself. To what extent private enterprises could, or should, be expected to deal with it effectively is not entirely clear. The moral questions that arise in this field are being actively engaged by people working in Digital Ethics. 

On the practical level, however, prior history with online platforms suggests that problems caused by ChatGPT will be solved by way of appeals from civil society, new legislation, changes to company policy, and further technical development.

Distorting public discourse

ChatGPT’s potential for trolling and disinformation isn’t necessarily much higher than that of already existing online bots. The only difference is that ChatGPT is more sophisticated and human-like. As we’ve mentioned earlier, this problem could be dealt with more or less successfully once OpenAI launches the watermark it’s developing to flag the content generated by the algorithm.

Cheating or loss of skills

Use of the model to “outsource” one’s thinking and writing could be addressed by updating student assessment to the 21st century. 

For instance, Turing College has developed a highly effective (and fully ChatGPT-proof) teaching method that includes 1-on-1 assessment of every subject that students are required to master in their course. 

Once mastery has been achieved, students are asked to build a project of their own, which is evaluated during a 1-on-1 call with industry professionals and more senior students. 

“ChatGPT is already capable of writing the greater part of essays that are commonly assigned to students," says Lukas. "And this will likely improve even further with the advent of GPT-4. The good news is that its negative effects are easily preventable through 1-on-1 assessments that include asking students to explain their choices and arguments. This is known as the Socratic method, and it works exceptionally well in the programming field, where it‘s usually called “live code review”. At the core of Turing College‘s assessment methodology is software that handles the operational part of 1-on-1 assessments, including scheduling, evaluation guidelines, and more.”

Isolated or homogenized learning

These problems can be overcome by supplementing individual, self-paced study online with group discussions and tasks.

These can include discourse channels, regular classroom activities, meetups and events together with other students and teachers. ChatGPT is an excellent tool for achieving mastery faster and more efficiently. Such tools, however, should (and likely won’t) ever be seen as a complete replacement for a robust educational infrastructure.

Life-long learning

From the late 17th to the mid 18th century, Enlightenment intellectuals like Diderot and Leibniz compiled massive encyclopedias intended as representations of the entire world’s knowledge up to that point. They assumed that the various academic disciplines were still part of the same world, only seen through different lenses. They embraced generalism. 

In contrast, today’s highly specialised curricula often preclude students from viewing phenomena according to methodologies other than their own. And yet social and economic dynamism reduces the half-life of knowledge, making continuous learning a must. 

"In a rapidly changing world, it's important to have a range of skills and abilities that you can draw on in different situations, " explains Lukas. "This means being open to learning new things and developing skills that may not be directly related to your current job, but that can help you adapt to new roles and industries."

Tools like ChatGPT will make it easier for people to study a given subject by applying different methodologies, e.g., analysing climate change by way of physics, literary fiction, politics, or economics.

Furthermore, AI is being deployed to progressively automate routine tasks. “Perhaps surprisingly, we are seeing that AI is able to automate more white-collar positions than expected with technologies such as ChatGPT," says Lukas. "This is the opposite of what most people expected. It proves how little we understand about the number of cognitively demanding tasks that can be automated. And shows that in the future many more will be automated.”

What matters here is that, the more our day to day activities are performed by technological systems, the more time and energy we’ll have for tackling more demanding tasks and addressing problems that affect us all globally. AI can be our support system in becoming true life-long learners.

The changing role of teachers

As education systems migrate towards more AI-centric approaches, teaching and learning requirements are likely to change quite substantially as well. Therefore, it’s not unreasonable to assume that even the concept of a “teacher” will be redefined to accommodate the emerging dynamic of learning vs. teaching.

Traditionally, school teachers and university lecturers were viewed as the custodians or repositories of knowledge, and students – as empty vessels to be filled with it. As education becomes more self-directed and extended throughout one’s lifetime, teachers might become something closer to technicians facilitating a more streamlined educational process. 

Students will spend more time learning independently, especially in view of the fact that modern technology gives students access to courses based on the best, research-based teaching methodologies adapted to each subject. Rather than passively absorbing knowledge from teachers in class, students will learn on their own and then ask teachers specific questions based on what they’ve learned to further consolidate their understanding.

With instant feedback-based AI systems for learning, students will also become more deeply involved in the pathways of their own learning. Measurement of educational outcomes will therefore be conducted either moment to moment or at least day to day. For instance, given further successful technological development, teachers will be able to know at the end of each student’s day whether they are meeting the set requirements, and, if necessary, remedy deficiencies then and there to stay on schedule and to not waste anyone’s time.