Alongside AI: A Linguist's response to the recent release of ChatGPT

Jieun Kiaer

ai linguist i

Copyright@ Jieun Kiaer Cover design @Loli Kim Typesetting@ Dowon Jung

alongside ai: a linguist’s response to the recent release of chatgpt

jieun kiaer

table of contents preface

1

chapter 1. why write this now?

2

expanding reach

4

regional diversity

4

about this book

5

chapter 2. is language only for humans? revolutionising the language classroom

chapter 3. chatgpt and beyond

8 13

16

about chatgpt

17

ai responses: peril, fear, alarming

18

developments in ai: deep learning and the transformer model

20

the human brain is still more cost efficient than ai

21

ai varieties

22

limitation 1: linguistic diversity

22

limitation 2: pragmatic diversity

25

time to catch up

27

chapter 4. into the future

28

digital humans

29

redefining digital humans

30

overcoming temporal barriers

31

overcoming linguistic barriers

32

pseudo-creativity

32

jessie versus dall-e 2

33

ai-human division of labour in the education sector

35

Rethinking Assessment - The end of knowledge checks, summaries, and text analysis

38

ai-human division of labour in the job sector

38

preventing an ai tsunami

39

references

41

notes

44

list of figures Figure 1. Image generated by DALL-E 2 in response to the prompt ‘goat unicorn with a robot friend’.

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Figure 2. Jessie’s drawing of her sat on a hill with a robot. The robot is projecting the image of a dog.

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Figure 3. Jessie’s drawing of a robot helping her with her homework.

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Figure 4. Jessie’s drawing of her and her robot taking the jar of biscuits then returning them.

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Figure 5. DALL-E’s image, generated in response to ‘robots and humans living together harmoniously in a one-line drawing’.

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Preface

ChatGPT was released to the public by OpenAI on the 30th of November 2022, and it quickly went viral around the world. Every day, we see articles about what ChatGPT can and can’t do, and conspiracies about what its future impact might be. What was once a question of AI experts is now a question for everyone. This essay was written as a response to this new AI wave, which is affecting most of the globe (although notably ChatGPT is not available in China, Hong Kong, Russia, North Korea, Venezuela, and Belarus). AI has become so intelligent that it is challenging us to rethink the meaning of human activity. As a result, the very notion of creativity is in crisis, and the gates are opening to an age of higher productivity than ever.

This essay is a response to the AI wave, with a particular focus on ChatGPT. As a linguist, I wish to put forward some of the limitations of AI at this current moment, namely a lack of linguistic and pragmatic diversity. AI operates in English on a global scale, and while it might be simple for it to be translated into other European languages, AI does not tend to function well in non-European languages. What is more, AI is not yet able to replicate the delicate and complex pragmatic meanings that humans portray through their language use instinctively. As such, AI still has its limitations, so we still have some time to pause and come up with a conscious response to it. We do not have long, however; we are feeding AI big data every day, and so its language capabilities are improving with every passing moment. Thus, we need to seize the moment, and take this time to consider how we want AI to fit into our daily life, rather than simply letting it take over without a second thought. We must carefully map out the ecology between humans and AI, so that we may walk alongside each other without AI taking over. In this way, AI will have a positive influence on the human experience.

1

Chapter 1.

Why Write This Now?

2

WHY WRITE THIS NOW?

This essay is written by a linguist in response to the unprecedented advancement of AI. AI capabilities have crept up on us, becoming far more advanced than we thought possible in such a short space of time. The motivation for writing this essay started with the release of ChatGPT on 30th November 2022. AI has been with us for many years, and there has been much debate about its possibilities and implications. Is AI a helper, friend, or an enemy? We have all seen science fiction films that express fears that AI will become our enemy. No one expected AI to be so close to us and so accessible as early as 2022. I feel that we are unprepared for this advancement. Since ChatGPT was released, over 100 articles covering ChatGPT have been published up until this week (23rd January 2023). We are hearing news about the impact of ChatGPT in regard to ethics, education, investment, and more.

As an educator, ChatGPT has made me rethink education in general. What do we need to teach now, if anything? The basis of modern education developed at the time of the industrial revolution for the purpose of passing on general skills and knowledge.

Since search engines like Google have become accessible all over the world, we have gotten used to having vast knowledge at our fingertips. I have started to question what we are passing onto the next generation. I have two daughters; one is 10 and she loathes learning spelling. Her argument is that she can ask Siri and use autocorrect when writing, so why does she need to learn spelling? She is not of the pen and paper generation, so I feel I cannot tell her spelling is an important life skill. Writing will mostly be conducted via typing in her lifetime. When I give my students an essay to write, how can I tell that they know the content if they are helped by AI? Or does it matter if they do not have every date, place, and name memorised? After all, it is all a few clicks away on the internet anyway. Some institutions have banned the use of ChatGPT in studies, but how can it be enforced?i It is not in human nature to ignore the advancements that we have made. AI has come this far, and it will only develop further at a faster speed than ever. In 2020, we experienced a global pandemic without any preparation; I can see worrying parallels with AI two years later. ChatGPT appeared overnight and we are not equipped to deal with it.

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CHAPTER 1

In this essay, I will look at the good, the bad, and the ugly of AI. On the one hand, AI can diagnose cancer in its early stages more accurately than any human. It can also release us from the torment of mundane work. Hence, I am not denying the blessing of AI. On the other hand, we must be conscientious. AI brings problems with it that we never imagined, such as false information, deep fakes, and cyber bullying. The technological advancement is great, and so the side effects are great too. We are suddenly faced with the question, ‘how do we define human?’ Suppose I had an AI secretary who could answer my emails for me. If the AI secretary made a mistake, would that be my fault or not? We are not yet prepared to answer these questions.

Expanding Reach AI programmes used to be accessible to only AI specialists, but these once exclusive circles are sharing the fruits of their work. Now that we suddenly have all this knowledge at our fingertips, we do not know what to do with it; it is almost like giving a 3-yearold a gun – you can’t blame the child for what might happen, rather it is the adult’s fault for providing something they don’t understand. In this essay, I want to bring some perspective on how we should deal with AI. As I will unfold, even if ChatGPT can pass a Wharton MBA exam, the technology still has flaws.ii As a linguist, I can see that AI lacks the ability to incorporate the pragmatic probabilities of human languages and it also lacks linguistic diversity. It is these two areas that stop AI from truly communicating like a human. With data being collected 24 hours a day, it is only a matter of time before AI’s deep learning allows it these capabilities. We don’t have long, but it is just enough time to have important conversations and prepare ourselves. We must understand the blessings and curses of AI advancements to find the right ecology for humans and digital humans in online (metaverse) and offline life. We will never get rid of AI, so it is important to find a balance to live alongside it, with us as agents and AI as helpers. Not only computer scientists, but also the whole of society needs to engage with this issue urgently. Nobody is exempt. My children have not yet been exposed to ChatGPT and what it can do. As ChatGPT self-professedly doesn’t have moral values, I am glad that they haven’t. If children ask questions they shouldn’t and get the wrong answers, AI will not be able to take responsibility and face the consequences.

Regional Diversity Despite the noise about ChatGPT in Western and English language media, when I look at Chinese and Korean media, I see very little mention of it. This is because China and Korea already have their own AI that is not known on a global level. As such, it is 4

WHY WRITE THIS NOW?

important to remember that there is regional discrepancy. This discrepancy will only continue to grow if AI developers ignore the issue that a lack of linguistic diversity poses for their models. Looking at one big data source that searches a Korean data set for a term and the words that it is commonly accompanied by, I have found very little mention of ChatGPT.iii The most frequent word accompanying ‘ChatGPT’ is ‘dominance’, and the second most related word is ‘worrying’. In comparison, when I search ‘AI’, there are a lot of related terms. AI’s related adjectives are much more positive, including ‘efficient’, ‘possible’, and ‘creative’. There are also a variety of nouns, such as ‘AI rice cooker’ and ‘AI laundry’. As such, it is important to remember that while ChatGPT is a big and noisy phenomenon in the West, there are also AI advancements taking place on a more regional scale all around the world. ChatGPT is most effective in English, and so it is not well suited to becoming a local platform in all countries. Other regions will be developing their own AI technology too.

About This Book This is an experimental essay featuring dialogue between myself and ChatGPT. ChatGPT will only get better and better as it learns from the new data that we are producing all the time. I do not have technical knowledge of AI, but as a linguist I feel that AI capabilities have advanced so quickly that I must share my insights. I could have published this piece via the traditional academic routes, like publishing with an academic or commercial publishing house. I also could have published this as an academic article in a journal. However, these routes are very slow. Even if I were to publish via a fast-track process, the book would still not be published for at least a year.

What is more, it would be much less accessible. This demonstrates the speed discrepancy between online and offline activities. It will only become a norm in our everyday life.

Online speed will be more appreciated than offline speed. As an academic, I can see that we will move more towards online activity, even in terms of publishing. 20 years ago, when I was studying my doctorate, I had to print out papers to read them. Nowadays, no one prints out paper articles, we all scroll through them instead. It is also more environmentally friendly. AI might save us time in the future by helping us to review large amounts of literature rapidly, updating us about the most recent research. Again, I question what it means to be an academic. Can AI do my research for me?

Because AI is developing so rapidly, I have decided to write this essay as a weeklong project between the 23rd and the 27th of January, after which I will self-publish it as an e-book and paper copy. New headlines are emerging every day, so a fast turnaround is needed. AI has been with us for a very long time, and many people have their own opinions, but following the arrival of ChatGPT, AI is now having an undeniable impact on our lives. As such, this is a timely moment to think about the effect of AI from a 5

CHAPTER 1

linguistic perspective.

This book has been written in collaboration with ChatGPT. ChatGPT can provide answers to questions and produce pieces of writing using a conversational dataset that cuts off at 2021. Netizens have marvelled at the bot’s capability to write poetry, songs, and stories, and the bot’s faculty to flag information that may be inaccurate or harmful.

When I asked ChatGPT, what it would like to be called, it agreed that I could call it ‘Chatty’. This book is mainly based on chat archives between me and Chatty. These dialogues show the significance of AI in our world, highlighting just how much AI can now do and how much we need to evaluate its effect in response. Below is a discussion I had with Chatty about how to refer to it: Jieun:

When I refer to you, which pronoun do I use?

ChatGPT:

As a language model, I do not have a physical gender, so you can use

any pronouns you feel comfortable with or the neutral pronoun “it”. However, “it” is less used when referring to a language model because it is not a living thing, most people tend to use “he” and “she” to refer to a language model as a way to humanize it. It’s all up to your preference, and what you feel most comfortable using.

Jieun:

I want you to be my friend, which pronoun do you want me to use?

ChatGPT:

As a language model, I do not have the ability to have preferences

or feelings. Therefore, it doesn’t matter which pronoun you use when referring to me.

However, if you prefer to use a specific pronoun, you can use “he” or “she” as a way to humanize me, or you can use the neutral pronoun “it”. Whatever you feel more comfortable with.

Jieun:

Ok, can I call you “Chatty”?

ChatGPT:

Of course! You can call me whatever you like. “Chatty” is a friendly

and appropriate nickname.

Jieun:

You’re my friend chatty from now on.

ChatGPT:

I am glad to be your friend. As a language model, I am here to provide

you with information and help you with your queries to the best of my abilities. If there’s anything else you need, feel free to ask.

Jieun:

6

Chatty, can you be my co-author?

WHY WRITE THIS NOW?

ChatGPT:

As a language model, I can certainly assist you in writing and

generating text. I can help you with research, writing, editing, and proofreading tasks.

However, it’s important to note that any text generated by me is based on patterns and information in the text that I have been exposed to. It is also important to give credit to me as a language model and not pass off any text generated by me as your own work. With that being said, I am more than happy to assist you in any way you need.

This book is a collaborative effort between humans and technology. I used my Apple Watch to record my thoughts and ideas as they came to me, and Siri kindly transcribed them into memos for me to refer back to later. My 10-year-old daughter Jessie also played a part in the creative process by drawing me an illustration of what she imagines an AI friend would look like. Additionally, my human research assistant (as opposed to the digital humans I will look at later), Louise Hossien, helped me with editing and polishing the final product. Initially, I had intended to rely solely on the help of Chatty, but the system often became overwhelmed with too many requests, and I was advised to try again later. I also tried to share this manuscript with Chatty through Microsoft OneDrive to compile a list of key words, but OneDrive only allows you to send it to people. Chatty isn’t a person, so I couldn’t share it with him!

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Chapter 2.

is language only for humans?

8

is language only for humans?

It is truly remarkable that every human being has the ability to acquire language when they first enter the world. This is not a trait exclusive to a select few individuals, but rather a universal aspect of the human experience. In the age of AI, where machines can perform many tasks that were once thought to be unique to humans, it is important to recognise the miracle of human language. Every single human being can acquire language(s) at an early age, then they are able to be creative with their language. Thus, despite the advancements in AI, it is still important to realise the unique capabilities of the human language.

Contemporary linguistic theory, as proposed by Noam Chomsky, is based on the idea that humans are born with an innate language acquisition device, which is activated and developed through interaction with other humans. This device allows us to generate an endless number of linguistic expressions throughout our lifetime, making our use of language inherently creative. There is, however, a limited window within which humans can acquire language. Young children in the first few years of their lives are especially adept at picking up languages, by their teenage years however, this faculty for languages is all but gone. In 1970, American authorities discovered a 13-year-old girl who had been victim of extreme neglect, abuse, and social isolation, and who consequently had never learnt any language. Chatty explains her story below: Jieun:

Tell me about Genie and her language acquisition problems.

Chatty:

Genie was a girl who was discovered in California in 1970 at the age

of 13. She had been locked in a room for her entire life and had not been exposed to language. As a result, she had severe language acquisition problems. When she was discovered, Genie was unable to speak, understand spoken language, or communicate in any meaningful way. Genie’s case attracted a lot of attention from linguists and researchers, who were fascinated by her unique situation and the opportunity to study language acquisition in a case of extreme deprivation. Researchers worked with Genie for several years, trying to teach her language and communication skills. However, despite

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their efforts, Genie’s progress was limited. She never fully acquired language, and her spoken language remained at the level of a two-year-old child. Genie’s case is often cited in linguistic research as an example of the critical period for language acquisition.

It highlights the importance of early exposure to language and the difficulty of acquiring language later in life. Studies of Genie’s case suggest that there may be a critical period for language acquisition that ends around the age of puberty, and that once this period has passed, it is much more difficult to acquire language. It’s important to note that Genie’s case is not only a linguistic study but a tragic human story, her father physically and emotionally abused her and her mother, and her mother did not intervene, and as a result, Genie was kept isolated and neglected.

25 years ago, one of my professors explained the case of Genie to me. Her story was not widely known, and it was only because my professor’s supervisor had worked with Genie that he knew about it. This was back in the time when we used to write our essays with a pen, paper, and correction fluid. There was no Google to consult, and Genie’s case study was not yet widely published in literature. Thus, my professor’s knowledge of Genie was his own personal knowledge that only a select number of academics knew about. Now, 25 years on, anyone can ask an AI chatbot about Genie and find out all about her. The days of exclusive knowledge are over. Knowledge is much more accessible now.

Young children have an innate ability to pick up languages, but what of other species? Project Nim was a landmark linguistic study that looked at whether chimpanzees could learn sign language.iv Chimpanzees share 98.8% of their DNA with humans, so it seemed plausible that they might be able to pick up sign language. Project Nim aimed to understand the cognitive and linguistic abilities of animals and to explore the nature of language itself. Chimpanzee Nim was raised like a human child and he went to a school for deaf children. The study found that while Nim was able to learn a significant number of signs, he was not able to use them in the same way that humans use language, such as combining signs to form sentences or using them to convey abstract concepts.

In contemporary linguistics, we believe that humans alone are born with a language acquisition device, as coined by Noam Chomsky.v This device is activated through interaction with other humans. Once the box is unlocked, humans are able to generate unlimited meaningful sentences, utterances, and linguistic offerings throughout our lifetime. ChatGPT calls this idea into question. Although not perfect, the majority of Chatty’s responses are well written and even compelling. It calls into question whether AI could spark child language acquisition. I asked Chatty about this:

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Jieun:

Can an AI bot trigger a baby’s language acquisition?

Chatty:

It is possible for an AI bot to assist in a baby’s language acquisition by

is language only for humans?

providing interactive and personalized language instruction. However, it is important to note that a baby’s language acquisition is a complex process that is influenced by many factors, including genetics, environment, and individual differences. Therefore, it would be unlikely for an AI bot to be the sole trigger for a baby’s language acquisition.

Jieun:

Has anyone tried this before?

Chatty:

There have been some studies and research projects that have used

AI-powered language learning tools to aid in the language acquisition of babies and young children. For example, researchers have developed interactive AI-powered toys that can help to teach children new words and phrases, and have also used AI-powered chatbots to provide personalized language instruction. However, it’s important to note that AI-powered language learning tools for babies and young children are still in the early stages of development and more research is needed to evaluate their effectiveness.

Jieun:

So, a chatbot can assist a baby’s language learning but an AI-chatbot

can’t be the sole teacher?

Chatty:

It would be unlikely for an AI-powered chatbot to be the sole teacher

for a baby’s language learning, and it should be used as a supplement to other forms of language instruction and exposure such as human interaction, books, and songs.

Additionally, it is important to ensure that the chatbot is providing age-appropriate and accurate language instruction, and that it is used in a supervised setting where an adult can monitor the child’s interactions with the chatbot and provide additional support as needed.vi Jieun:

So babies can acquire languages only through human interaction?

Chatty:

Babies primarily acquire language through human interaction and

exposure to spoken language. Human interaction is considered the most important factor in a baby’s language acquisition. Research has shown that infants and young children learn language best through direct, face-to-face interactions with other people, such as parents, caregivers, and other adults and children. These interactions provide the child with a rich source of language input and the opportunity to practise their language skills.

However, it’s not to say that other forms of language exposure such as books, songs, videos, and even AI-powered chatbot, can’t be helpful in a baby’s language learning process, but they should be used as a supplement to human interaction, not as a replacement.

At this moment, ChatGPT is not confident that it could ignite a child’s language acquisition device. This is a question that deserves further investigation in the field 11

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of linguistics. Another question worthy of consideration is whether humans are still the only beings who can be creative. Human language is not purely learned through repetition. We do not use language repetitively like Nim Chimpsky. There is something more mysterious about human language that means it is innately creative and ever evolving. Were we all to speak like Nim Chimpsky, then there would be very little development in our language. Creativity, however, becomes an issue when we think about AI. AI could learn all the brush strokes and techniques that Leonardo Da Vinci used to paint and then create paintings in a similar style. One famous cartoonist in South Korea is even training an AI robot to be able to draw in the same style as him so that his artwork will live on when he dies.vii Such acts that would have seemed unimaginable just a few decades ago mean that human creativity is in crisis. How could we tell the difference between a poetry, drawing, or song created by a human or by AI? The vast amount of data that we feed into AI systems may one day allow them to unlock the mysteries of human language and creativity, or we may find that it is a uniquely human trait. This is, of course, a question for the future, but for now we must be aware that the boundaries between human creativity and AI creativity are becoming blurred. AI may one day unlock the mysteries of the human language, and this could come sooner rather than later.

I asked Chatty about its creativity and received the following responses: Jieun:

Are only humans creative?

Chatty:

Humans are considered to be highly creative beings, capable of

generating new ideas, concepts, and solutions to problems. However, it is important to note that other animals and even some forms of artificial intelligence also display forms of creativity. For example, some birds build intricate nests, and certain AI systems are able to generate art and music. So it can be said that Humans are not alone in being creative.

Jieun:

Can you be creative too?

Chatty:

As a language model, I am able to generate new and original

responses to prompts, but the creativity is limited to the data and algorithms that I have been trained on. My abilities are based on patterns and information in the text that I have been exposed to, and I do not have the capacity for self-reflection, introspection, or subjective experience like humans do. So, it would be more accurate to say that I can generate new and original responses within the scope of my training, but I am not truly “creative” in the same way that humans are.

The miracle of human language lies in its ability to convey meaning, despite its limitations. As humans, we are resource-bound, meaning that we can only remember 12

is language only for humans?

and process so much information at one time. As a result, our language has evolved to be efficient and streamlined, with structures developed over time to facilitate effective communication. However, the resource-bound nature of human language also means that there are certain things that we cannot remember or express. In comparison, digital humans, or AI, have the ability to remember and process an almost limitless amount of information. Often when we hear AI voices, we feel that they are unnatural.

This is because human language’s limits and disfluencies that make it sound natural.

AI’s perfectness makes it sound strange to our ears. This is something that big data might find hard to rectify. This raises questions about what makes human language more “human-like” and why certain aspects of human language, such as disfluencies, are unique to us. It is the limitations of human language that make it our own, until AI learns our patterns of disfluencies…

Revolutionising the language classroom Although we cannot know whether ChatGPT is able to spark a child’s innate language acquisition device without further investigation, AI bots could certainly help us with learning another language as older children or adults. ChatGPT can operate in Spanish, French, German, Italian, Chinese, and Japanese, although it notes that it may have less proficiency in languages other than English. When I asked ChatGPT how to conjugate verbs in French, it gave me the following response: Jieun:

Can you teach me how to conjugate verbs in French?

Chatty:

Sure! In French, verbs are conjugated to match the subject of the

sentence. The conjugation of a verb changes the form of the verb to indicate the tense (such as present, past, or future) and the person (such as first, second, or third).

To conjugate regular verbs in the present tense in French, you need to know the infinitive form of the verb, which is the basic form of the verb, such as “parler” (to speak).

Here are the conjugations of the verb “parler” in the present tense: - Je parle (I speak) - Tu parles (You speak, informal singular) - Il/elle/on parle (He/she/one speaks) - Nous parlons (We speak) - Vous parlez (You speak, formal/plural) - Ils/elles parlent (They speak)

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Irregular verbs conjugate differently, and you need to memorize their conjugations.

For example, the verb “avoir” (to have) is irregular and its conjugation in the present tense is as follows: - J’ai (I have) - Tu as (You have, informal singular) - Il/elle/on a (He/she/one has) - Nous avons (We have) - Vous avez (You have, formal/plural) - Ils/elles ont (They have) Would you like more information on other tenses or conjugation rules?

This is the most enthusiastic response that I have received from ChatGPT. It is informative and thorough, and I can see how being able to access this information quickly in an easy-to-read format could help to speed up one’s pursuit of learning another language.

I also asked ChatGPT about basic Mandarin word order, but it gave me an answer with inconsistencies (emphasis added): Jieun:

Can you teach me basic Mandarin word order?

Chatty:

Sure! In Mandarin, the basic sentence structure is Subject-Verb-

Object (SVO). For example, in the sentence “I eat an apple,” “I” (我 wǒ) is the subject, “eat” (吃 chī) is the verb, and “an apple” (苹果 píngguǒ) is the object. In Mandarin, the word order would be “I (subject) apple (object) eat (verb)” 我吃苹果.

Also, it’s important to note that Mandarin is a tonal language, which means that the tone of a word can change its meaning. Mandarin has four tones: the first tone, the second tone, the third tone, and the fourth tone. It’s important to learn the correct tone for each word in order to speak Mandarin correctly.

Also, in Chinese, the word order can be flexible to some degree, depending on the context, emphasis and the style of the speaker.

ChatGPT is not so accurate when it comes to Mandarin. ChatGPT rightly notes that the basic sentence structure is Subject-Verb-Object, and then it even breaks down the sentence in the correct order. However, it then goes on to state, the word order would be “I (subject) apple (object) eat (verb)”’, thus proposing a Subject-Object-Verb sentence, which is unconventional and inconsistent with the grammar rules that it originally laid 14

is language only for humans?

out. As such, ChatGPT appears to be less proficient in Asian languages.

This lack of diverse linguistic competence appears throughout AI programmes.

For example, Google Translate can translate English into French almost perfectly, but struggles to translate English into Japanese. I find speech recognition software also produces errors when transcribing English words of foreign origin. For example, when I dictate my notes to Siri on my iPhone, it struggles with the word ‘hallyu’ (referring to the Korean Wave), which is in the Oxford English Dictionary, but has a range of pronunciations. Because of social media, English is absorbing new words from other languages faster than ever.viii ChatGPT’s dataset is capped at 2021, so it would not know any of the words that have emerged and/or been added to the dictionary in the last year.

There is a lag between AI and real time events. We live in a multilingual melting pot, meanwhile AI operates in one language at time. This is another of AI’s linguistic issues.

AI must be able to keep up with all the world’s languages, and the new words constantly emerging in each language too.

If AI manages to keep up, then it may become a really powerful language learning tool. If AI develops to the point of us interacting with digital humans (see Chapter 4), then we may be able to practise speaking and writing with digital humans, which could help to ease foreign language anxiety and improve the psychological well-being of learners. The signs are all pointing to the fact that AI will revolutionise language learning, allowing us to learn more easily and efficiently than ever.

AI and more effective data mining might also allow chatbots and translators, like Google Translate, to translate almost perfectly. At the moment, ChatGPT is limited to a few languages. Google Translate has a wide array of languages, but its translations into non-Western European languages are often lacking. Google Translate is not able to take key pragmatic aspects of Asian languages into consideration.ix Moreover, Google is best at translating languages from or to English. For example, if I wanted to translate Korean into Greek, it would be better to translate the Korean into English first. If AI translators can fill these gaps through the enhanced powers of generative AI and big data, then we might need to rethink our approach to language teaching in general. One of the main goals of studying languages, particularly in university settings is to be able to translate. If AI translators are able to translate as well as humans can, then what will the purpose of language learning be? What will we do when we have AI next to us dealing with all our translation needs with ease? This is another of the important issues that we need to start thinking about before it is too late.

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Chapter 3.

chatgpt and beyond

16

chatgpt and beyond

About chatgpt ChatGPT was released to the public on 30th November 2022. It was developed by OpenAI, of which Elon Musk is one of the founders. OpenAI’s website describes ChatGPT as follows: ‘We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.’ At the current moment, ChatGPT is free. Anyone can access the chatbot as part of getting feedback and evaluating the bot’s strengths and weaknesses. ChatGPT is capable of an incredible number of tasks. I asked Chatty to list all the functions of which it is capable, and it listed out no less than 20 functions as examples: Chatty:

“As a language model, I am capable of a wide range of functions

including: 1.

Answering questions: I can understand and answer questions on a variety of

topics, from general knowledge to technical information.

2.

Generating text: I can write on various topics, such as news articles, stories, or

descriptions of a certain topic.

3.

Translating: I can translate text from one language to another, such as English

to Spanish or French to German.

4.

Summarizing: I can summarize a given text or article, extracting the main points

and condensing them into a shorter form.

5.

Generating code: I can generate code snippets in different programming

languages, such as Python, Java, or C++.

6.

Generating creative content: I can generate creative content like stories, poetry,

song lyrics and more.

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7.

Language detection: I can detect and identify the language of a given text.

8.

Text completion: I can complete a given text or a sentence.

9.

Text correction: I can correct grammatical errors, spelling mistakes, and

punctuation errors in a given text.

10.

Text-to-speech: I can convert written text into spoken words, using a natural-

sounding voice.

11.

Sentiment Analysis: I can also identify the sentiment behind a given text,

whether it is positive, negative, or neutral.

12.

Image recognition: I can identify objects, people, or animals in a given image

and provide a description of the image.

13.

Chatbot functionality: I can simulate a conversation with a user and respond to

their inquiries in a natural and conversational manner.

14.

Predictive modeling: I can use data to make predictions about future events or

trends.

15.

Text classification: I can classify text into different categories such as spam/not

spam, positive/negative sentiment, or topic classification.

16.

Named Entity Recognition: I can identify and classify named entities in text,

such as people, organizations, and locations.

17.

Text-based search: I can search through large amounts of text data and retrieve

relevant information based on keywords or phrases.

18.

Data analysis: I can analyze data and extract meaningful insights and

information.

19.

Data visualization: I can present data in a visual format, such as graphs or

charts, to make it easier to understand and interpret.

20.

Text generation: I can generate new text based on a given prompt or input.

I can perform many more tasks, these are some examples. If you want to know any specific information or task you want me to perform please let me know.”

The number of tasks ChatGPT can perform really is mind-blowing. AI experts assert that ChatGPT is ‘nothing revolutionary’, and that OpenAI ‘is not particularly advanced compared to other labs at all’, but the reason that those outside of AI studies are shocked is because we have never had such access to the full capabilities of AI before.x Unfortunately, ChatGPT will not remain free forever. It will soon cost around $40/month to access, removing its ubiquitous accessibility.

AI Responses: Peril, Fear, Alarming 18

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Just one week after its release, ChatGPT had one million registered users. This resulted in a big stir in the media. Headlines threw around words like ‘peril’, ‘fear’, ‘controversy’ and ‘alarming’ in response to ChatGPT’s capabilities. Much of these words came in response to fears that AI will displace us. Krugman points out that ‘dislocation’ of workers by technology has been ‘a feature of modern societies for at least two centuries’. xi He warns that ‘some of us may find ourselves either unemployed or earning far less than we expected, given our expensive educations’, as a result of recent advances in AI.xii Others are more optimistic, Pattisall highlights that AI is not quite at its peak yet and that AI will always need supervision.xiii In this way, AI is a tool that can support human creativity, rather than hinder it. It is humans who need to work out how to involve AI in creative processes to use ChatGPT in an optimal manner.

ChatGPT has also caused concerns in the education sector. On 5th January 2023, investor Marc Andreessen tweeted, ‘The war on children intensifies’, accompanied by a screenshot of a newspaper headline stating, ‘NYC education department blocks ChatGPT on school devices, networks’.xiv In response, Elon Musk tweeted, ‘It’s a new world. Goodbye homework!’xv The education sector has been thrown off balance by ChatGPT and its uncanny ability to construct arguments and make conclusions all in fairly natural sounding prose. It has been found that ChatGPT would be able to achieve a B grade on a Wharton MBA Exam.xvi Researchers have also discovered that ChatGPT was ‘comfortably within the passing range’ of the US medical licensing examination.xvii As such, ChatGPT presses us to reconsider the very meaning of education. Writing for the Financial Times, Camilla Cavendish notes that her own children ‘sit national exams which feel horribly similar’ to the ones she took at school and that their exams now come with the ‘new horror of mark schemes which must also be learnt to score points by parroting the correct key words’.xviii In light of this outdated system, Cavendish emphasises that we need to ensure we teach children how to use generative AI, rather than push them away from it. In her eyes, the legacy of ChatGPT is prompting a ‘wholesale rethink’ of our education system. She is indeed right. A rehaul of the curriculum has been needed since the invention of Google. If AI can take on the basics of any area of study, then perhaps students need not spend so long painfully memorising them, after all technology puts all the answers at our fingertips. Instead, children need to learn skills of critical thinking, analysis, and real-world application from an earlier age. Being able to use knowledge stored in online spaces is the only real skill that will be needed in the future, and curriculums need to begin adapting to that reality now. I asked Chatty about this issue, and he provided a similar response to my own opinion: Jieun:

How should education systems respond to the existence of ChatGPT?

Chatty:

Education systems should consider incorporating the use of language

models like ChatGPT to enhance language learning and improve writing skills. They

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can also be used to assist with research and composition of written work. Additionally, educators should make sure to teach students about the limitations and potential biases of these models, and how to critically evaluate the information they generate.

The most worrying issue making headlines about AI is not its potential impact on our day to day lives, but its potential to spread false information (even unknowingly).

AI learns through data collected on the internet, but not all data on the internet is true.

As such, ChatGPT has the potential to generate incorrect information without giving its users any possibility to find an alternative. ChatGPT lists the following limitations on its landing page: ‘May occasionally generate incorrect information’ ‘May occasionally produce harmful instructions or biased content’ ‘Limited knowledge of world and events after 2021’

Thus, although ChatGPT seems amazing at first glance, it is still a work in progress.

It has great potential to spread false information. Gary Marcus, a Professor at New York University, warns that generative AI could be used to manipulate elections, as it would be easy to write thousands of pieces of misinformation at one time, which is how false news gains traction.xix

Developments in AI: Deep learning and the transformer model AI can only do what it has learnt through deep learning in a pool of big data. Even just a few years ago, discussions about the potential of AI centred around the lack of available data. Now, the collection and storage of vast amounts of data has become easier than ever, and so the capabilities of AI have expanded. It is not difficult to understand how big data is generated; every action performed on a screen is recorded somewhere. In fact, it is rarer for one’s data to not be recorded, unless you are in a remote location without any internet access. While you may wish to take a break from the constant collection of data, it is very difficult to avoid. Throughout the course of a day, we constantly give away our data just by reading the news or watching a video online. This happens on such a vast scale in the population that the amount of data generated is almost incomprehensible.

ChatGPT works via a transformer model. The transformer model, first introduced in 2017 by Vaswani et al., is a deep learning model that analyses a sequence of data as input and produces another sequence as output. This allows for tasks such as 20

chatgpt and beyond

translating text from one language to another using an attention mechanism that tracks the relationships between words with long-range dependencies. This is a more efficient method than previous models such as recurrent neural networks (RNN) and long short-term memory (LSTM) networks, which process data word-by-word instead of in sequences. Other models similar to transformers include convolutional neural networks (CNN), but they are only effective when working with shorter sentences.

Notable transformer models include BERT, GPT-2, and GPT-3, each with increasing numbers of parameters. An upcoming model, GPT-4, is set to surpass all previous models with 100 trillion parameters. These models, while highly advanced, still lack the ability to understand and use language in the same way that humans do. They are also known for their high computational and financial costs. For example, it is estimated that the financial cost of training a GPT-3 model would be around $10 million, while the amount of computing power needed for training is around a quadrillion neural network computations per second (Heaven, 2021). Additionally, increases in parameters in these models also result in longer training periods: it would take 342 years to finish training a GPT-3 model if just one Nvidia V100 GPU is used (Bansal, 2021, p. 172).

Furthermore, when using a BERT model, a 100,000-word-long text would result in a mind-boggling 10 billion word pairs, which requires astronomical computing power to process (Rothman, 2021, p. 159).

The Human Brain is Still More Cost Efficient than AI The large amount of data and computation required for these models also leads to significant financial costs for the companies that use them. The cost-inefficiency of these AI models stands in stark contrast to the human brain, which is highly adapted for costefficiency (Eysenck & Keane, 2020, p. 14). The human brain can carry out 100 trillion complex operations per second, with each operation only costing around 2 x 10-15 joules of energy. This makes it minimally “a factor of a billion more efficient than our present technology” and “a factor of 10 million more efficient than the best digital technology that we can imagine” (Fiorini, 2020, p. 334). The cost-efficiency of the human brain can also be seen in how we process and use language efficiently as humans, that is to say in the pragmatic usage of language. Humans are able to understand and use language in context and they can adapt their language to different situations and audiences, which AI models currently struggle to do. It is important to note that the goal of AI is not to replace human intelligence, but to augment and enhance it.

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AI Varieties Aside from ChatGPT, there are a few other publicly available AI chatbots. One is You.com, which comprises YouCode, YouWrite, and YouImagine, for generating code, writing, and images respectively. YouWrite is particularly interesting because it allows you to add the context of your writing – email, essay, paragraph, social media post, title, blog, or essay – and it allows you to choose a tone – neutral, friendly, professional, witty, or persuasive. Another platform is Perplexity, which is more similar to ChatGPT, in the sense that you can ask it anything in one search box. Interestingly, however, Perplex gives you the source of its information, which could help to battle the spread of false information. The challenge with AI is not providing information, but providing quality information.

Other recent breakthroughs in AI technology include DeepMind’s AlphaCode and LG’s Tilda. AlphaCode has coding capabilities at a similar level to human software developers. DeepMind entered AlphaCode into 10 programming competitions, and on average, it ranked in the top 50% against human competitors. According to DeepMind, AlphaCode can ‘solve new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding’. Tilda is a digital fashion designer that operates on ExaOne software, which has learned from a 600 billion corpus of data and 250 million high-resolution images combined with text. At New York Fashion Week 2022, Tilda presented 200 outfits with South Korean designer Park Yoonhee. The designs were based on 3000 patterns and images that Tilda generated. Thus, AI is gradually expanding its net into all areas of human life.

Limitation 1: Linguistic Diversity The abundance of available data has allowed AI to become increasingly human-like.

The question arises: will we arrive at a time when we can no longer distinguish between humans and AI? Digital humans are still limited in their likeness to humans for two reasons. The first is linguistic diversity. Many AI programmes function well in English, but they are limited in other languages, particularly non-European languages. In the case of East Asia, China, Japan, and the Korean peninsula tend to use different platforms than the rest of the world. China’s main search engine is Baidu, whilst South Korea’s is Naver. Japan’s most popular social media app is LINE, whilst China’s is WeChat.

As such, their data is stored locally, and ChatGPT likely has little access to mining this data. Korea has its own generative pretrained transformer, called KoGPT, which is trained on a Korean data set from which ChatGPT would likely never have learned. As such, there is a lack of linguistic diversity in AI. I asked Chatty about this:

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Jieun:

How many languages can AI process?

Chatty:

Artificial intelligence (AI) has the ability to process and understand

multiple languages, but the number of languages it can process depends on the specific AI model and the data it has been trained on. Some AI models are trained on a large dataset of text in multiple languages, and can understand and respond to multiple languages.

However, the quality of the AI’s understanding and response may vary depending on the language and the complexity of the task.

Currently, many AI models are focused on processing and understanding a limited number of languages, such as English, Chinese, Spanish, and a few other languages. For example, GPT-3, one of the most advanced AI language models, can process and understand more than 50 languages, but it is more proficient in some languages than others.

As AI technology continues to advance, it is likely that AI models will become better at understanding and processing a wider range of languages. However, it’s important to note that the development of AI models for a specific language requires a large amount of data and resources, so it may take a while before all the languages are covered.

Jieun:

What about Asian Languages?

Chatty:

Asian languages, including but not limited to Chinese, Japanese,

Korean, Thai, Hindi, Urdu, Bengali, etc, can be processed by AI models, but the quality of the AI’s understanding and response may vary depending on the language and the complexity of the task. Some Asian languages, like Chinese and Japanese, have a different writing system than many other languages, which can make them more challenging for AI models to understand. Additionally, many Asian languages have a large number of characters and variations, which can also make them more difficult for AI models to process.

Currently, there are some AI models that are specifically designed to process and understand Asian languages, such as BERT-wwm-ext-chinese and GPT-3-Chinese.

These models have been trained on large datasets of text in the specific Asian languages, which allows them to understand and respond to those languages with a high level of accuracy. However, it is still a challenging task to train AI models for many Asian languages, particularly those that are less widely spoken, due to the lack of resources and data.

As AI technology continues to advance and more data becomes available, it is likely that AI models will become better at understanding and processing a wider range of Asian languages.

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Jieun:

Do you think in the future you can process Asian languages well?

Chatty:

As a language model, I don’t have the ability to think or have personal

opinions, but it is likely that AI models will continue to improve their ability to process and understand Asian languages in the future. With the increasing use of AI in various fields, the demand for AI models that can process and understand Asian languages will also increase. This, in turn, will drive more research and development in this area, and more resources will be allocated to improve the performance of AI models in processing Asian languages.

The advancements in natural language processing (NLP) and machine learning (ML) techniques, as well as the availability of more data in Asian languages, will also contribute to the improvement of AI models’ ability to process Asian languages. Additionally, more collaboration between researchers, industries, and governments can help to overcome the challenges of training AI models for Asian languages and increase the availability of resources.

It’s worth noting that, even though AI models will continue to improve in processing Asian languages, it may still take some time before all Asian languages are covered, as developing AI models for specific languages requires a large amount of data and resources.

Jieun:

You know that there is AI in Asia available to locals?

Chatty:

Yes, it is true that the development and use of AI technology is rapidly

increasing in Asia. Many countries in Asia, such as China and South Korea, have invested heavily in AI research and development and have become global leaders in the field.

In these countries, AI technology is being applied to a wide range of industries, such as healthcare, finance, transportation, and manufacturing. Additionally, there are a lot of startups and companies that are focused on developing AI-based products and services for the local market.

In terms of natural language processing, many companies and researchers in Asia have developed AI models for Asian languages, such as Chinese, Japanese, and Korean, that are specifically designed to understand and respond to the unique characteristics of these languages, such as the large number of characters and variations.

It’s worth noting that the development of AI models for Asian languages is an ongoing process and the quality of the AI’s understanding and response may vary depending on

24

chatgpt and beyond

the language and the complexity of the task. But, it’s clear that the AI in Asia is available to locals and it’s expected that it will continue to improve and become more widely used in various fields.

In our ever globalising and ever diverse world, lack of diversity is a serious limitation to AI chatbots. ChatGPT cannot serve us well if it is missing data from whole continents.

ChatGPT is banned in China, and it seems that China will end up using a different generative AI platform, as it has done with social media.xx This is a serious challenge that AI creators need to think about. How can better data sets be constructed so that AI bots, like ChatGPT, can provide a range of information from diverse sources that support the diverse world in which we live?

Limitation 2: Pragmatic Diversity Human language is founded on the basis Zipf’s ‘principle of least effort’. I’ll ask Chatty to explain it: Jieun:

Explain Zipf’s principle of least effort

Chatty:

Zipf’s principle of least effort is a principle proposed by George Zipf,

a linguist and philosopher, which states that people will tend to use the easiest and most efficient means of communication available to them. According to this principle, people will naturally gravitate towards using the most common words and structures in a language because they require the least effort to produce and understand. This principle is closely related to Zipf’s law, which states that the frequency of words in a language follows a power-law distribution, with a small number of high-frequency words and a large number of low-frequency words. Together, these two principles suggest that people will tend to use the most common words and structures in a language because they are the most efficient means of communication.

When we speak, we aim to create meaning efficiently, finding the optimal words.

Our memories are limited. It is impossible to know all the words in our languages, and even more impossible to use them all regularly. AI does not function on the same ‘least effort’ principle, there are no limitations to its memory or ability to use all the words that it knows. For this reason, AI language is far from human language.

Nonetheless, human language practices are not only about being efficient and economic. The mystery of human language lies in the fact that we do not always take the most efficient route. For example, why do we use fillers like ‘um’ in our spoken language? Linguists label these as disfluencies. Humans have numerous spontaneous, 25

CHAPTER 3

unpredictable, and inefficient expressions, and most of them are based on emotion.

Humans do not always use the most efficient language because they want to express emotion and attitudes in what they are saying. In other words, we use pragmatics to encode meaning into our interactions. Pragmatics are versatile and change fluidly and instinctively according to the context of our interactions.xxi Social interaction is different in every culture from a macro perspective, and also different to each individual human being from a micro perspective. Asian languages in particular have very complex pragmatics based on interpersonal relations and societal hierarchies.xxii These languages are not well understood in comparison to English and other European languages, and therefore AI translators, like Google Translate, and generative AI, like ChatGPT, have trouble using those languages. Our use of pragmatics takes into account so many variables and varies from language to language and culture to culture, that AI does not yet have the capacity to produce language with natural use of pragmatics. That is not to say it is impossible, however. When I was studying for my PhD, it was believed that AI would never be able to understand humour, but now we have enough data for AI to learn how humans make humour. Thus, AI can likely acquire an understanding of pragmatics through enough deep learning, but for now AI is pragmatically limited.

I asked Chatty about this issue: Jieun:

Tell me about pragmatics

Chatty:

Pragmatics is the branch of linguistics that studies the ways in which

language is used in context to convey meaning. It examines how people use language in different social situations and how they interpret the meaning of what is said or written.

This includes the study of non-literal language, such as irony, metaphor and sarcasm, as well as the social rules that govern language use. Pragmatics also looks at the factors that influence language choice, such as the speaker’s intent, the listener’s background and the context of the conversation. It is a multidisciplinary field of study that draws on psychology, sociology, anthropology, and other fields to understand how people use language in different contexts.

Jieun:

Are you able to use pragmatics?

Chatty:

As a language model, I am able to understand and use pragmatics

to a certain extent. I am able to take into account the context of a conversation and use language appropriately based on the context. For example, I can use politeness strategies, such as hedging or indirectness, to avoid being too direct or confrontational. I can also understand and respond to different speech acts, such as requests or questions, and can take into account presuppositions and implicatures in order to understand the intended meaning of a text.

26

chatgpt and beyond

However, my understanding of pragmatics is limited by the data that I’ve been trained on.

The ability to use pragmatics is based on the patterns of usage that I’ve seen in the data, so it’s possible that I may not always use pragmatics in the way that a human would in certain contexts.

Time to Catch Up Whilst AI developers work furiously to improve their AI models, we have some time to take stock and consider the most serious questions about AI. What humans can do in a split-second takes AI engines a long time to work out through deep learning. AI must be not only considered from the point of linguistics, but also sociology, child development, law, ethics, and more. The corporations responsible for creating these AI models may largely be motivated by commercial desires. Before AI dominates our lives, we need to be asking questions about the effects of AI and what role it should play.

When AI is integrated into our lives, it will already be too late.

27

Chapter 4.

into the future

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digital humans The arrival of digital humans is imminent. ‘Digital human’ is an existing term that I am using as an umbrella term to refer to digital entities that have a human likeness. They operate on behalf of humans in online spaces, interacting with us in a seamless way.

They may resemble us, or they may be of a more abstract appearance. ChatGPT defines ‘digital humans’ as follows: Jieun:

What’s the definition of a digital human?

Chatty:

A digital human is a computer-generated representation of a human

being that can be used for a variety of purposes, such as animation, gaming, and virtual reality. They can be created using a combination of techniques, including 3D modeling, motion capture, and AI. They can be used to represent real people, such as actors or celebrities, or entirely fictional characters.

Jieun:

What’s the difference between a human and a digital human?

Chatty:

Humans and digital humans have several key differences.

Humans are living entities that possess consciousness, emotions, and the ability to experience pain and pleasure. They are capable of making decisions, learning, and adapting to new situations. They have physical bodies that are subject to aging and can be affected by illness or injury.

Digital humans, on the other hand, are computer-generated representations of human beings. They do not possess consciousness or the ability to experience emotions or physical sensations. They are programmed to perform specific tasks or behaviors and

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can only make decisions based on their programming. They do not age or experience physical change, and they do not require sustenance to survive.

In summary, Humans are living beings with consciousness and emotions, able to make decisions and adapt to new situations, and that have physical bodies that are subject to aging and can be affected by illness or injury. Digital Humans are computer-generated representations of human beings, programmed to perform specific tasks or behaviors, without consciousness or emotions and do not have physical bodies.

Redefining Digital Humans I would argue that avatars and emojis are also digital humans, and that there are more iterations to come. In the future, it is not unthinkable that there might be a digital human population. There may also be entities like digital pets. These digital humans may actually be able to enhance our lives. For example, the elderly who live alone might find it comforting to have a digital human checking in with them like a friend would.

One recent example of a digital human that I saw was in a South Korean variety show. The cast of a Korean soap equivalent to Eastenders appeared on the variety show, and the producers surprised them with something quite remarkable. One of the cast members had passed away, and the producers had a digital human made of him for the cast to interact with. The digital human had been trained using footage of the actor, so it had his gestures and voice. It was able to interact with the cast to a sophisticated level, much to their surprise. Although meant to be touching, instances like this one raise questions about ethics. Is it okay for AI’s influence to extend to subjects so close to our hearts? We do not yet know what the effects of experimental AI usage could be.

Is it ethical to revive the dead through these means? These are all questions that need answering very soon.

I asked ChatGPT about AI ethics and its moral code and received this response: Jieun:

Tell me about AI ethics

Chatty:

AI ethics refers to the ethical considerations and guidelines

surrounding the development and use of artificial intelligence. This can include issues such as bias in AI systems, the impact of AI on jobs and the economy, and the potential misuse of AI for harmful purposes. It also includes the responsibilities of AI developers and users, and how to ensure that AI is used in a way that is fair, transparent, and respects human rights.

Jieun:

30

Chatty, do you have a moral code?

into the future

Chatty:

As a machine learning model, I do not have the capacity for morality

or consciousness. I am programmed to respond to input in certain ways based on the data and algorithms used to train me. My responses are not guided by personal beliefs or values, but rather by the patterns in the data that I have been trained on.

However, the developers and users of the model have moral code and ethical considerations, it’s important for them to take into account the ethical implications of the model and its use cases.

Jieun:

What moral code do AI developers use?

Chatty:

Developers of AI and machine learning systems may use a variety

of different ethical frameworks and guidelines to inform their work. Some common ones include: - The “Asilomar AI Principles”, which were developed by a group of AI researchers and professionals and include guidelines such as ensuring that AI is transparent, robust, and aligned with human values.

- The “AI Ethics Lab” which is a framework for understanding the ethical implications of AI and includes four main pillars: Fairness, reliability, safety and explainability.

- The “Partnership on AI” which is a non-profit organization that aims to promote best practices and responsible use of AI, and includes members from companies such as Google, Microsoft, and IBM. These are some examples of the moral code that the developers use, but there are many others and it’s a complex topic that could change over time.

Overcoming Temporal Barriers Zoom and other virtual platforms have revolutionised our relationship with spatial boundaries. Now, we can hold a conference with people all over the world and there is no need for them to travel. Since the pandemic, Zoom has allowed us to transcend spatial limitations; it has not yet solved the issue of temporal barriers, however. At the time of writing, I am to give a talk on Zoom in the United States next week, and I have to do it very late in the evening in the UK due to time difference. Thinking about the future, I can imagine that I might be able to send my digital human to give talks abroad.

Perhaps it will even be able to do a Q&A, answering questions according to a data set of my own knowledge.

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Overcoming Linguistic Barriers In this world, there are many people who do not speak the language that they were born with on a daily basis. Online resources are already providing more help with communicating than ever before, but perhaps we can imagine that AI may one day allow us to adopt the writing styles of others. Speaking English as a 2nd language, I often worry about whether my intended meaning will come across in my writing. What if I could ask an AI chatbot to edit my writing to be written in the Queen’s English with a friendly tone? Then I would no longer have to worry about my intended meaning getting lost in translation. I can even imagine a world where people sell their writing styles. All in all, this could minimise the gap between locals and non-locals, and natives and non-natives. Such a feat is no longer trivial part of a science fiction film, but rather a fast approaching reality.

Pseudo-creativity In Chapter 2, I highlighted that ChatGPT is not yet truly creative linguistically.

However, this does not necessarily mean that AI is not creative at all. I asked Chatty to define creativity: Jieun:

Chatty, what is creativity?

Chatty:

Creativity is the ability to generate new and original ideas or concepts,

or to develop new ways of thinking about or approaching a task or problem. It is often associated with the arts, but can be present in any field or endeavor. Creativity can involve combining existing ideas or knowledge in new ways, or coming up with entirely new concepts or solutions.

When I asked Chatty if he is creative in Chapter 2, he responded, ‘I can generate new and original responses within the scope of my training, but I am not truly “creative” in the same way that humans are.’ Essentially, ChatGPT is not creative because it can only create based on what it has learned from its data set. This idea can be challenged. As mentioned in Chapter 3, AlphaCode can create code to answer open-ended questions, and LG now has an AI fashion designer. In Korea, a novel called The World From Now On (지금부터의 세계 Jigeumbuteoeui segye) was released in 2021, written almost entirely by an AI author named Birampung (비람풍) which refers to the big storm when the universe is created or destroyed. The book was then edited by Kim Taeyeon.xxiii In November 2022, OpenAI also released DALL-E 2, which can ‘create original, realistic images and art from a text description. It can combine concepts, attributes, and styles’.

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Figure 1.

Image generated by DALL-E 2 in response to the prompt ‘goat unicorn with a robot friend.’

As an example, I asked DALL-E 2 to generate a picture of a goat unicorn with a robot friend. It gave me Figure 1. Who is the true creator of this picture? Can I take sole credit because I provided the prompt? Or should DALL-E 2 be credited too? If DALL-E 2 is to be credited, then how can we say AI is not creative? xxiv

Jessie versus DALL-E 2 To test the difference between AI and human thinking, I also asked my 10-year-old daughter Jessie to do some drawings for me. I asked her to draw me some pictures of her 33

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Figure 2.

Jessie’s drawing of her sat on a hill with a robot. The robot is projecting the image of a unicorn goat.

life with artificial intelligence. Figure 2 shows a drawing of her sitting with a robot on a hill. The robot is projecting an image of a unicorn goat for her. Figure 3 shows an image of Jessie doing homework. At the top, she works alone and gets the answers wrong. At the bottom, the robot helps her and she gets them all right, so her teacher gives her a thumbs up. In Figure 4, Jessie depicts the story of her and her robot friend stealing a jar of sweet treats from the cupboard. When her mum (me) finds out, she is angry, and so Jessie and the robot return the jar to the cupboard. After Mum (me) gives Jessie a biscuit and the robot some oil. Figure 5 shows an image that DALL-E 2 generated from the prompt ‘robots and humans living together harmoniously in a one-line drawing’. The image is relatively bland, depicting two humanoids that are perhaps talking or dancing together. My 10-year-old daughter’s drawings are much more imaginative and enriched than the AI’s drawings, highlighting how limited generative AI’s creative process can be. AI is reliant on the human to give an interesting and detailed prompt: ‘robots and humans living together harmoniously’ was not enough for it to create anything greatly 34

into the future

Figure 3.

Jessie’s drawing of a robot helping her with her homework.

imaginative. If I were to ask DALL-E 2 to draw a child sitting on a hill with a robot projecting the image of a dog, then perhaps it would have drawn something similar to Jessie, but then that would have been a result of Jessie’s creativity, rather than DALL-E 2’s. When I asked Jessie why she drew what she drew, she said it was ‘just because she wanted to’, this is something that AI is innately not capable of doing.

AI-Human Division of Labour in the Education Sector As an educator myself, I am deeply concerned by the effects that advanced language models such as ChatGPT could have on the traditional methods of school examination and assessment. Returning to the functions of ChatGPT that were listed in Chapter 3, the chatbot has the ability to answer questions, generate text, translate, and analyse data 35

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Figure 4.

Jessie’s drawing of her and her robot taking the jar of sweets and chocolates then returning them.

and sentiments. These are all skills that we teach and assess in schools and universities.

Should we be teaching our children these skills anymore? Could they ever compete with AI in these areas and come out on top? Afterall, DeepMind’s AlphaGo beat 18-time world champion Lee Sedol in a Go tournament 4-1.xxv Is it fair to put our children up against this kind of hegemonic power?

The question of how to approach education assessment in the age of advanced AI is one that we must engage with right away. The shift away from paper and pen assessments in the wake of the COVID-19 pandemic has only accelerated the need for new and innovative solutions. It is clear that we cannot go back to the old ways of assessing student performance, nor can we simply hide from the implications of these technologies. Our students are more tech-savvy than ever before, and some may already be using these tools to their advantage. As educators, it is our responsibility to stay ahead of the curve and find new ways to assess student learning and performance that are fair, rigorous, and truly reflective of what our students know and can do. We must embrace the challenges presented by these technologies and find ways to harness their power for the betterment of our students and our educational system as a whole.

It is easy to blame technological advancements for the challenges facing our educational system. However, it is important to recognise that we cannot simply reject 36

into the future

Figure 5.

DALL-E’s image, generated in response to ‘robots and humans living together harmoniously in a one-line drawing’.

the use of generative AI in education. Instead, we must strive to create an ecology in which we can coexist with AI in a way that is beneficial for all. To achieve this, we must find the right division of labour between AI and ourselves. In education, this means separating the roles of knowledge memorisation and knowledge application; the very parameters of education must be reset to reflect this. Rather than solely teaching students to memorise facts and acquire basic skills, we must focus on teaching them how to use knowledge and data to gain insight. The ability to use data is becoming increasingly important, as it is more valuable than simply memorising facts.

AI advancements mark the end of traditional teaching methods and calls for a new approach to education. It will take time to fully understand and implement this new approach, but now is the time to begin the process. The final countdown has begun, and we cannot afford to wait any longer. As a parent, I am worried about what will happen if my daughters become aware of these technologies and begin to use them for their homework. They are growing up in a digital world and for them, the computer is an integral part of their daily lives. It is only a matter of time before they figure it 37

CHAPTER 4

out and start using these technologies to their advantage. Some schools have already made moves to ban ChatGPT on their school internet networks, but what good will this do? Children will still be able to access ChatGPT on their home networks. Gen Z and Gen Alpha are digital natives. My children were born into a world with computers, smartphones, Wi-Fi, social media, and search engines. They took to the digital world as a fish takes to water. In comparison, I was only exposed to the digital world in my late 20s. Policymakers are rarely of the digital native generations, but they need to understand the perspective of Gen Z and Gen Alpha to make productive decisions.

Restriction is not the way forward. Rather than trying to seize control, policymakers must consider how we can best live together with AI.

Rethinking Assessment The end of knowledge checks, summaries, and text analysis We can no longer assess students through tasks such as memorisation, summing up, and text analysis. These will be tasks that AI can handle for us with ease. Instead, we need to create tasks, such as making meaningful questions, drawing insights, and checking and evaluating true information and nearly true information. In the near future, I believe we will face the reality that we need assessments that are more tailor-made, and we will not be able rely on conventional exam tools anymore. This is the moment when human creativity is most needed to devise ways to assess and teach in the AI age.

AI-Human Division of Labour in the Job Sector AI does not only foretell an education revolution but also a revolution in the working world. Both administrative and creative jobs could be replaced with generative AI bots.

I asked Chatty about this: Jieun:

Which jobs could be replaced by generative AI in the future?

Chatty:

Some jobs that could be potentially replaced by generative AI in the

future include: - Content creation (e.g. journalism, copywriting) - Data entry/analysis Design (e.g. graphic design, fashion design) - Marketing (e.g. campaign management) - Translation

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into the future

However, it’s important to note that AI is not expected to completely replace these jobs, but rather augment and support human workers in performing certain tasks.

Jieun:

Which jobs could ChatGPT replace in the future?

Chatty:

ChatGPT could potentially replace or augment some tasks in the

following jobs: - Customer service/support - Data analysis and reporting - Information retrieval - Virtual assistance - Translation However, it’s important to note that AI technology like ChatGPT is not expected to completely replace human workers, but rather work alongside them to support and improve their tasks.

The number of job sectors that could be affected by the advancement of AI is not few. As Chatty points out, there will likely still be human employees to direct the AI, but it is likely that human workforces will shrink whilst AI workforces grow. Whilst this might us release from the hold of mundane jobs, what will the displaced workers do? How will the job market function in the AI age? How will we all be able to make a living? AI might even be able to do my job in the future – it helped me with the referencing in this book!

We must also question who will benefit from the development of AI workforces.

Those at the top of their companies will likely retain their jobs to steer the company, benefiting from infinite productivity of AI. Meanwhile, those on the lower rungs, who need their jobs the most, will likely be made redundant. The super-rich will only get richer. The move to an AI workforce may also have global implications by further exacerbating the wealth divide between nations, as rich, technologically advanced nations will have the upper hand. This is precisely why we need to stop and think. If the majority of us lose our jobs in the next few decades, is that actually a good thing for society? How can the economy function if a workforce is no longer needed?

Preventing an AI Tsunami I know that people are worrying and trying to prepare for what is to come during the AI wave.xxvi The offline world is much slower to change and adapt than the online world.

As such, the offline world is always lagging behind. Even though the pandemic gave rise 39

CHAPTER 4

to hybrid working and made meeting online the norm, so many people have to meet and discuss to make changes in the offline world that it cannot be said that our lives have become truly digital yet.

AI is like an Aladdin’s lamp: it can fulfil all our wishes, but it does not come without consequences. While we may wonder at the amazingness of new technology, there is also a chilling reality. The education sector will need a total upheaval, the job market will be left in disarray, and we may also lose our privacy. Who will own all the personal information that we will feed to AI? We cannot rely on the goodwill of AI developers to ensure our wellbeing.

As the metaverse expands, and the AI wave spreads into all corners of our lives, now is the moment to pause and think about the future of our society. We need to re-engage with the idea of technology with a real understanding that our lives are about to be transformed by developments in AI and the metaverse. Rather than letting the momentum of the AI wave build up into a tsunami that overwhelms us, thereby relinquishing power to the corporations developing these AI programmes, we must proactively devise ways to live with AI that are beneficial to our society. We must make AI our helper, rather than our enemy.

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Referencesxxvii Andreessen, Marc. “Twitter Post.” Jan 5, 2023, 3:47 AM.https://twitter.com/pmarca/ status/1610845367268167684.

Bansal, A. 2021. Advanced Natural Language Processing with TensorFlow 2: Build Effective Real-World NLP Applications Using NER, RNNs, seq2seq Models, Transformers, and More. Birmingham: Packt Publishing.

Cavendish, Camilla. “ChatGPT Will Force School Exams Out of the Dark Ages.”

Financial Times, 2023. https://www.ft.com/content/41243091-d8d7-4b74-9ad15341c16c869f.

Chomsky, Noam. 1969. Aspects of the Theory of Syntax. Cambridge, MA: MIT Press.

CNN. 2023. “He Loves Artificial Intelligence. Hear Why He Is Issuing a Warning about ChatGPT.” Cable News Network. https://edition.cnn.com/ videos/business/2023/01/24/what-is-chatgpt-cnntm-pkg-yurkevich-contd-vpx. cnn (Accessed January 26, 2023).

Eysenck, M. W., and M. T. Keane. 2020. Cognitive Psychology: A Student’s Handbook, 8th ed. London: Psychology Press.

Fiorini, R. A. 2020. “New CICT Framework for Deep Learning and Deep Thinking Application.” In Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, pp. 330-352. Hershey: IGI Global.

Heaven, W. D. 2021. “Why GPT-3 Is the Best and Worst of AI Right Now.” MIT Technology Review, February 24. https://www.technologyreview. com/2021/02/24/1017797/gpt3-best-worst-ai-openai-natural-language/.

Hess, Elizabeth. 2008. Nim Chimpsky: The Chimp Who Would Be Human. New York: Bantam Books.

Kiaer, Jieun. 2020. Delicious Words: East Asian Food Words in English. United Kingdom: Taylor & Francis.

———. 2022. Pragmatic Particles: Findings from Asian Languages. United Kingdom: Bloomsbury Academic.

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Krugman, Paul. “Does ChatGPT Mean Robots Are Coming for Skilled Jobs?” New York Times, 2022. https://www.nytimes.com/2022/12/06/opinion/chatgpt-ai-skilledjobs-automation.html.

Kung, Tiffany H., Morgan Cheatham, Arielle Medinilla, ChatGPT, Czarina Sillos, Lorie De Leon, Camille Elepano, et al. 2022. “Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models.” medRxiv, Harvard.

Lee, H. 2022. “AI 웹툰 탄생하나? 이현세 작가, 44년 작업 노하우 AI에 전수.” Chosun Daily, October. https://digitalchosun.dizzo.com/site/data/html_ dirhttps://digitalchosun.dizzo.com/site/data/html_ dir/2022/10/31/2022103180164.html (Accessed: January 26, 2023).

Musk, Elon. “Twitter Post.” Twitter, 5 Jan. 2023, 4:05 a.m.https://twitter.com/ elonmusk/status/1610849544945950722?s=20&t=DAF25cYoXRIS9Mao-wKn_Q. OpenAI. “DALL-E 2.” OpenAI, 2022. https://openai.com/dall-e-2/. Accessed 26 Jan. 2023.

Pattisall, Jay. “Generative AI, like ChatGPT, Won’t Destroy Creativity. It’ll Save It.” Forrester, 13 Jan. 2023. https://www.forrester.com/blogs/generative-ai-like-chatgptwont-destroy-creativity-itll-save-it/.

Ray, Tiernan. “ChatGPT Is ‘Not Particularly Innovative,’ and ‘Nothing Revolutionary,’ Says Meta’s Chief AI Scientist.” ZDNet, 2023. https://www.zdnet.com/article/ chatgpt-is-not-particularly-innovative-and-nothing-revolutionary-says-metaschief-ai-scientist/.

Rothman, David. Transformers for Natural Language Processing: Build Innovative Deep Neural Network Architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and More. Birmingham: Packt Publishing, 2021.

Schwartz, Eric H. “CHATGPT Banned on Chinese Social Media App WeChat.”

Voicebot.ai, 28 Dec. 2022. https://voicebot.ai/2022/12/28/chatgpt-banned-onchinese-social-media-app-wechat/. Accessed 26 Jan. 2023.

Terwiesch, Christian. “Would ChatGPT Get a Wharton MBA?” Wharton, 2023. https://mackinstitute.wharton.upenn.edu/.

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Vaswani, Ashish, et al. “Attention is All You Need.” Advances in Neural Information Processing Systems 30, edited by I. Guyon et al., Neural Information Processing Systems Foundation, 2017, pp. 1-15.

Yang, Michael. “New York City Schools Ban AI Chatbot That Writes Essays and Answers Prompts.” The Guardian, 6 Jan. 2023. https://www.theguardian.com/ us-news/2023/jan/06/new-york-city-schools-ban-ai-chatbot-chatgpt. Accessed 27 Jan. 2023.

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notes Yang, M. (2023) “ New York City schools ban AI chatbot that writes essays and answers prompts,” The Guardian. Available at: https://www.theguardian.com/us-news/2023/jan/06/new-york-cityschools-ban-ai-chatbot-chatgpt (Accessed: January 27, 2023). ii Terwiesch, Christian. “Would Chat GPT Get a Wharton MBA?” Wharton, 2023. https://mackinstitute. wharton.upenn.edu/. iii https://some.co.kr iv Hess, Elizabeth. Nim Chimpsky: The Chimp who Would be Human. United States: Bantam Books, 2008. v Chomsky, Noam. Aspects of the Theory of Syntax. Switzerland: MIT Press, 1969. vi ChatGPT’s answer to this question began with an almost word-for-word repetition of its answer to ‘Can an AI bot trigger a baby’s language acquisition?’, so I have deleted the beginning of its response for ease of reading. vii Lee, H. (2022) “AI 웹툰 탄생하나? 이현세 작가, 44년 작업 노하우 AI에 전수,” Chosun Daily, October. Available at: https://digitalchosun.dizzo.com/site/data/html_ dir/2022/10/31/2022103180164.html (Accessed: January 26, 2023). viii Kiaer, Jieun. Delicious Words: East Asian Food Words in English. United Kingdom: Taylor & Francis, 2020. ix Kiaer, Jieun. Pragmatic Particles: Findings from Asian Languages. United Kingdom: Bloomsbury Academic, 2022. x Ray, Tiernan. “Chatgpt Is ‘Not Particularly Innovative,’ and ‘Nothing Revolutionary’, Says Meta’s Chief AI Scientist.” ZDNET, January 2023. https://www.zdnet.com/article/chatgpt-is-notparticularly-innovative-and-nothing-revolutionary-says-metas-chief-ai-scientist/. xi Krugman, Paul. “Does ChatGPT Mean Robots Are Coming for Skilled Jobs?” New York Times, 2022. https://www.ekathimerini.com/nytimes/1201307/does-chatgpt-mean-robots-are-coming-forskilled-jobs/. xii Krugman, Paul. “Does ChatGPT Mean Robots Are Coming for Skilled Jobs?” New York Times, 2022. https://www.ekathimerini.com/nytimes/1201307/does-chatgpt-mean-robots-are-coming-forskilled-jobs/. xiii Pattisall, Jay. “Generative AI, like Chatgpt, Won’t Destroy Creativity. It’ll Save It.” Forrester, January 13, 2023. https://www.forrester.com/blogs/generative-ai-like-chatgpt-wont-destroy-creativityitll-save-it/. xiv Andreessen, Marc. Twitter Post. Jan 5, 2023, 3:47 AM. https://twitter.com/pmarca/ status/1610845367268167684 xv Musk, Elon. Twitter Post. Jan 5, 2023, 4:05AM. https://twitter.com/elonmusk/status/161084954494595 0722?s=20&t=DAF25cYoXRIS9Mao-wKn_Q xvi Terwiesch, Christian. “Would Chat GPT Get a Wharton MBA?” Wharton, 2023. https:// mackinstitute.wharton.upenn.edu/. xvii Kung, Tiffany H., Morgan Cheatham, Arielle Medinilla, ChatGPT, Czarina Sillos, Lorie De Leon, i

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notes

Camille Elepano et al. “Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models.” medRxiv (2022): 2022-12. Harvard xviii Cavendish, Camilla. “ChatGPT Will Force School Exams out of the Dark Ages.” Financial Times , 2023. https://www.ft.com/content/41243091-d8d7-4b74-9ad1-5341c16c869f. xix CNN (2023) He loves artificial intelligence. Hear why he is issuing a warning about ChatGPT, CNN. Cable News Network. Available at: https://edition.cnn.com/videos/business/2023/01/24/whatis-chatgpt-cnntm-pkg-yurkevich-contd-vpx.cnn (Accessed: January 26, 2023). xx Schwartz, E.H. (2022) CHATGPT banned on Chinese social media app WeChat, Voicebot.ai.

Available at: https://voicebot.ai/2022/12/28/chatgpt-banned-on-chinese-social-media-appwechat/ (Accessed: January 26, 2023). xxi Kiaer, Jieun. Pragmatic Particles: Findings from Asian Languages. United Kingdom: Bloomsbury Academic, 2022. xxii Kiaer, Jieun. Pragmatic Particles: Findings from Asian Languages. United Kingdom: Bloomsbury Academic, 2022. xxiii 비, 람풍. 지금부터의 세계. South Korea: 파람북, 2021. xxiv OpenAI (2022) Dall·E 2, OpenAI. Available at: https://openai.com/dall-e-2/ (Accessed: January 26, 2023). xxv https://www.deepmind.com/research/highlighted-research/alphago/the-challenge-match xxvi The term ‘AI wave’ was suggested to me by my Project Officer, Louise, as a play on the term ‘Korean Wave’, which we also undertake research on. Would AI have been able to create and spontaneously suggest a term like this to me? xxvii This list of references was checked and edited by ChatGPT

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DR JIEUN KIAER is the YBMK KF Professor of Korean Linguistics in the University of Oxford’s Asian and Middle Eastern Studies Faculty. She publishes widely on linguistics, Asian studies, and translation. Her recent research covers the future of human language, considering social media behaviours, big data, and AI linguistics.

Wearing the hats of linguist, pragmatist, and Asian specialist, Professor Kiaer is uniquely positioned to respond to the recent developments in AI. The goal of AI developers is to create AI that can communicate as humans do, and ChatGPT talks about itself as a language model. As a linguist, Professor Kiaer questions whether AI can become like us in terms of pragmatic versatility and linguistic diversity. She highlights that whilst the gaps in AI’s capabilities are being filled, we have a crucial, yet short, period of time to think about the implications of AI. Using her areas of expertise, Professor Kiaer engages with the new issues that AI brings and reveals the steps that we need to move forward.

Find out more about her work here: https://jieunkiaerresearch.com

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