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Most students are interested and find it helpful, but some aren’t sure what’s okay and what’s not when using it.

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We can ask them through quick surveys, reflections in Canvas modules, or simple online tools like Padlet :)

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Some are stressed or just don’t have enough time. Others might not feel confident, or they think using AI is easier and no one will really care.

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I’m not totally sure, but as a general rule, we should model good use, set clear guidelines, and talk with students about using AI fairly and honestly..

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We should think about privacy, fairness, and making sure students still learn and think for themselves, not just copy AI.

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Instead of just giving students the answers, we can teach them to think critically, like checking if an AI translation sounds natural or if a sentence actually makes sense. This helps them use AI as a language tool, not just a shortcut. But for Beginners and Continuers, this can be tricky. AI produces responses that are too advanced or not level-appropriate. So we need to guide them carefully..., which shouldn't be easy AT ALL.

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We can use AI to create practice tasks that match each student’s language level, give instant feedback on grammar or vocabulary (like the quizzes in our Canvas), and suggest personalised reading or writing activities. It can also help students hear natural pronunciation or rewrite sentences in a clearer way.

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I wish... I’ll make it clearer when and how students should use AI, and I’ll set tasks that need their own ideas or real thinking — not something AI can do for them.

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We need to protect things like student voice, creativity, teamwork, and learning through problem-solving, not just relying on AI.

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Resources and information for the AI Assessment Scale (AIAS)

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One of my major grievances of large language models is the uncited reuse/repurposing of existing artworks and literature, it is basically theft in my opinion. I do not want to use any tool that does this for sourcing or creating images, exceptions being things like Adobe Firefly, which only uses Adobe's own images to derive its work. Any recommended or mandated tools should be vetted for such concerns first.

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Students are often aware of the growing importance of AI and digital literacy in the job market, leading to a positive attitude towards learning about AI and how to use it effectively.

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Students are often aware of the growing importance of AI and digital literacy in the job market, leading to a positive attitude towards learning about AI and how to use it effectively.

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we already survey students in Canvas and on lesson days to get real feedback on their attitudes towards their learning and use of AI and other tools

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we already survey students in Canvas and on lesson days to get real feedback on their attitudes towards their learning and use of AI and other tools

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Students are using AI to complete their coursework for several reasons.
First, many students feel pressured by heavy workloads and tight deadlines, so they turn to AI tools to save time and reduce stress.
Second, AI can help them generate ideas, improve grammar, and structure their writing more clearly, which makes completing tasks easier.
Finally, some students may not fully understand the topic or lack confidence in their own skills, so they rely on AI to fill those gaps and produce higher‑quality work.

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They get an instant answer without having to do the hard work.

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Students can upload their Best Answers doc with their sample speaking Q&As to receive feedback on how their responses could be improved. Marking criteria can also be uploaded to make feedback more accurate. They can also ask follow up questions creating a mock exam.

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Margarita: More competitive students feel that ChatGPT makes the work "too easy", perhaps in the same way as the Betty Crocker example.

Ke Fan: Students are using AI but don't know how to use it well. Students find it helpful but there is a lot for them to learn. They need a clear purpose. It could make students lazy if used incorrectly.

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When students are using transation tools for the purpose of creating texts we don't feel it's helpful. However, if we teach them how to enahnce the texts they write it's effective.

AI can be used to guide and improve, not to create.

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Time saving, fear of failure, it's quicker.

They feel they will learn better. A way to ease stress overload/

One example: instead of reading a book, students can create / access summaries.

Students can also use AI apps as a teaching tool.

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Students might want ideas to begin their task. They might also want to check if they are on the right track when completing their coursework.

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Since AI does not always require you to think, we need to be careful that we do not rely too much on it. We still need to use professional judgement and critical thinking.

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Discussions and surveys on Canvas and lesson days

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Discussions and surveys on Canvas and lesson days

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Students are experimenting with AI, but they often don't have a clear idea how to access the full potential of AI apps to help them improve their skills.

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Different experiences for the struggling and confident

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Different experiences for the struggling and confident

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Students who are struggling will see it as a way to get through work more quickly.

Some students feel that if their teachers use AI, what is the point of having a teacher.

Instant feedback on assessment practice is a big appeaL.

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Where do we draw the line of 'authenticity' when we are creating content?

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Something different that I will do this term, is guide my students to how they can use AI tools to enhance their learning i.e. using Notebook LM for study notes, summarising texts i.e. in Extension, how to use it safely i.e. keeping anoynomous not sharing any personal data. That way they also have some autonomy in their learning and can learn to study and feel prepared for their exams. Further, I plan to use AI differently when providing feedback for my students such as recording feedback, and using AI to enhance connections with students through guidance, using AI for exam preparation and individualised learning to assist with their learning needs.

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Excitement about new technology and capacity to be able to cheat. Gives them confidence, especially with the weaker students. and will just submit to get the task done. It doesn't change the mind set.

Whereas the better students they use it they use it to brainstorm and for their drafts their responses are more refined

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Collect feedback during speaking lessons, include a question on AI use in the lesson day surveys.

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Our group wants to individualise speaking lessons for each individual student using Educhat. We also want to help students prepare for speaking exam prep using the best answers doc (similar to Q4)

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Find out from the students how they are using AI so we can guide them. Perhaps a survey to see things from their end.

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Our group wants to individualise speaking lessons for each individual student using Educhat. We also want to help students prepare for speaking exam prep using the best answers doc (similar to Q4)

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Margarita: As language teachers we have been dealing with AI for longer as students have used AI translation tools before generative AI was introuced.

Ke Fan: School use of AI (not encouraged by DET for students) vs universities encouraging it. Problems in universities with AI generating work.

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Oral feedback, surveys. Lesson days.

2nd part of q : find qs via discussion forums to improve our use of AI

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Other tools: Subtitling tools; Speaking/conversation practice eg Mizou; Geniallly for MindMaps;

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Generating ideas for assessments. Differentiating speaking lessons for students.

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We can use AI for personalised learning by letting it adjust the work to each student’s level, giving quick feedback on their answers or writing, and suggesting what they should focus on next. AI can also act like a tutor, explaining things in different ways to help students understand better. These strategies make learning more suited to each student’s needs.

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Students need to check for mistakes when they generate anything via AI as it can be inaccurate.

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There are different reasons:

academic overload (as a 'shortcut')

if there is a lack of modeling / rubric for tasks showing them how to compose a text

to look up words / expressions

to check for accuracy

out of worry that their current skills are not good enough to achieve good marks

to get feedback on & enhance their work

to research, get information & ideas

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Facilitates differentiation for students with particular learning difficulties

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Facilitates differentiation for students with particular learning difficulties

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Prompts like "effective teaching strategies for students who struggle with particular learning difficulties.

Students with reading difficulties could content content read aloud to them (for example).

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Ke Fan: We don't need to abandon old tools, but keep other ways of teaching and add AI on. We welcome and encourage students to use AI but maintain other modes of teaching.

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Creating differentiated learning materials for students.

Personalised lessons for students.

AI can be used create audio material for students to listen to rather than read large chunks of material.

Scaffolding work for students who are struggling to engage with course content

Creating more accessible materials via visual materials - AI can be used to create the lead in via the visual material.

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Summary of grammar topic for students' speaking documents

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Summary of grammar topic for students' speaking documents

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AI could great a personalised grammar summary for students' speaking documents. This could be an upcoming new grammar point or a concept they are struggling with.

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Many students are using it secretly, but not effectively. A lot of AI use so far is not disclosed to us as they do not have productive uses of it.

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Using our professional knowledge and judgement, we need to consider the issues around the intellectual property, plagiarism and appropriateness of the content generated by AI tools.

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Time poor, saves time, overwhelmed, it checks their grammar, spelling errors.

For the higher students it's to refine their work.

To know which each option is best we can give students a few options

Research project- helps to process many sources quickly

Don't have to do too much thinking

Structured responses are there

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We need to have discussions with our students about the pros and cons of the use of AI and stress that information generated by AI should only be used as a supplement.

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I think students are using AI to do their coursework because it's fast, easy, and quite helpful when they are attempting some challenging tasks. Some students don't feel confident in their skills, while others just want to finish quickly. If the work feels boring or too hard, they're even more likely to turn to AI for help.

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fear, laziness, to reduce cognitive load, it is an easy fix, judgement. There is a big gap between the demands of stage 5 and 6. The most important thing is to engage in conversation and find out why?

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fear, laziness, to reduce cognitive load, it is an easy fix, judgement. There is a big gap between the demands of stage 5 and 6. The most important thing is to engage in conversation and find out why?

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Even with more AI in teaching and learning, our role as educators can stay the same in many ways. We still need to plan lessons, explain ideas clearly, and build relationships with students. AI can be a helpful tool, but it cannot replace the care, judgment, and experience that teachers bring. Instead of changing our role, we can keep doing what we do best while using AI only when it truly supports our teaching.

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How much course content can we upload to something like EduChat to differentiate course material?

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AI is not neutral. The data reflects the biases of the material it is fed and the algorithms; a white, Western, masculine, view of the world. There is the danger that it will perpetuate these inequalities.

It is also less effective in languages other than English, which in turn may contribute to the narrowing of diversity in culture and language:

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AI chatbots are less fluent in languages other than English, threatening to amplify existing bias in global commerce and innovation.

Computer scientist Pascale Fung can imagine a rosy future in which polyglot AI helpers like ChatGPT bridge language barriers. In that world, Indonesian store owners fluent only in local dialects might reach new shoppers by listing their products online in English. "It can open opportunities," Fung says-then pauses. She's spotted the bias in her vision of a more interconnected future: The AI-aided shopping would be one-sided, because few Americans would bother to use AI translation to help research products advertised in Indonesian. "Americans are not incentivized to learn another language," she says.

Not every American fits that description- about one in five speak another language at home-but the dominance of English in global commerce is real. Fung, director of the Center for AI Research at the Hong Kong University of Science and Technology, who herself speaks seven languages, sees this bias in her own field. "If you don't publish papers in English, you're not relevant," she says. "Non-English speakers tend to be punished professionally."

Fung would like to see AI change that, not further reinforce the primacy of English. She's part of a global community of AI researchers testing the language skills of ChatGPT and its rival chatbots and sounding the alarm about evidence that they are significantly less capable in languages other than English.

Although researchers have identified some potential fixes, the mostly English-spewing chatbots spread. "One of my biggest concerns is we're going to exacerbate the bias for English and English speakers," says Thien Huu Nguyen, a University of Oregon computer scientist who's also been on the case against skewed chatbots. "People are going to follow the norm and not think about their own identities or culture. It kills diversity. It kills innovation."

At least 15 research papers posted this year on the preprint server arXiv.org, including studies co-authored by Nguyen and Fung, have probed the multilingualism of large language models, the breed of AI software powering experiences such as ChatGPT. The methodologies vary, but their findings fall in line: The AI systems are good at translating other languages into English, but they struggle with rewriting English into other languages-especially those, like Korean, with non-Latin scripts.

Despite much recent talk of AI becoming superhuman, ChatGPT-like systems also struggle to
fluently mix languages in the same utterance-say English and Tamil-as billions of people in the world casually do each day. Nguyen's study reports that tests on ChatGPT in March showed it performed substantially worse at answering factual questions or summarizing complex text in non-English languages and was more likely to fabricate information. "This is an English sentence, so there is no way to translate it to Vietnamese," the bot responded inaccurately to one query.

Despite the technology's limitations, workers around the world are turning to chatbots for help crafting business ideas, drafting corporate emails, and perfecting software code. If the tools continue to work the best in English, they could increase the pressure to learn the language on people hoping to earn a spot in the global economy. That could further a spiral of imposition and influence of English that began with the British Empire.

Not only AI scholars are worried. At a US congressional hearing this month, Senator Alex Padilla of California asked Sam Altman, CEO of ChatGPT's creator, OpenAI, which is based in the state, what his company is doing to close the language gap. About 44 percent of Californians speak a language other than English. Altman said he hoped to partner with governments and other organizations to acquire data sets that would bolster ChatGPT's's language skills and broaden its benefits to "as wide of a group as possible."

Padilla, who also speaks Spanish, is skeptical about the systems delivering equitable linguistic outcomes without big shifts in strategies by their developers. "These new technologies hold great promise for access to information, education, and enhanced communication, and we must ensure that language doesn't become a barrier to these benefits," he says.

OpenAI hasn't hid the fact its systems are biased. The company's report card on GPT-4, its most advanced language model, which is available to paying users of ChatGPT, states that the majority of the underlying data came from English and that the company's efforts to fine-tune and study the performance of the model primarily focused on English "with a US-centric point of view." Or as a staff member wrote last December on the company's support forum, after a user asked if OpenAI would add Spanish support to ChatGPT, "Any good Spanish results are a bonus." OpenAI declined to comment for this story.

Jessica Forde, a computer science doctoral student at Brown University has criticized OpenAI for not thoroughly evaluating GPT-4's capabilities in other languages before releasing it. She's among the researchers who would like companies to publicly explain their training data and track their progress on multilingual support. "English has been so cemented because people have been saying (and studying), can this perform like a lawyer in English or a doctor in English? Can this produce a comedy in English? But they aren't asking the same about other languages," she says.

Large language models work with words using statistical patterns learned from billions of words of text grabbed from the internet, books, and other resources. More of those available materials are in English and Chinese than in other languages, due to US economic dominance and China's huge population.

Because text data sets also have some other languages mixed in, the models do pick up capability in other languages. Their knowledge just isn't necessarily comprehensive. As researchers at the Center for Democracy and Technology in Washington, DC, explained in a paper this month, because of the dominance of English, "a multilingual model might associate the word dove in all languages with peace even though the Basque word for dove (' uso ') can be an insult."

Aleyda Solis encountered that weakness when she tried Microsoft's Bing chat, a search tool that relies on GPT-4. The Bing bot provided her the appropriate colloquial term for sneakers in several English-speaking countries ("trainers" in the UK, "joggers" in parts of Australia) but failed to provide regionally appropriate terms when asked in Spanish for the local footwear lingo across Latin America ("Zapatillas deportivas" for Spain, "championes" for Uruguay).

In a separate dialog, when queried in English, Bing chat correctly identified Thailand as the rumored location for the next setting of the TV show White Lotus, but provided "somewhere in Asia" when the query was translated to Spanish, says Solis, who runs a consultancy called Orainti that helps websites increase visits from search engines.

Executives at Microsoft, OpenAI, and Google working on chatbots have said users can counteract poor responses by adding more detailed instructions to their queries. Without explicit guidance, chatbots' bias to fall back on English speech and English-speaking perspectives can be strong. Just ask Veruska Anconitano, another search engine optimization expert, who splits her time between Italy and Ireland. She found asking Bing chat questions in Italian drew answers in English unless she specified "Answer me in Italian." In different chat, Anconitano says, Bing assumed she wanted the Japanese prompt 元気ですか ("How are you?") rendered into English rather than continuing the conversation in Japanese.

Recent research papers have validated the anecdotal findings of people running into the limits of Bing chat and its brethren. Zheng-Xin Yong, a doctoral student at Brown University also studying multilingual language models, says he and his collaborators found in one study that generating better answers for Chinese questions required asking them in English, rather than Chinese.

When Fung at Hong Kong and her collaborators tried asking ChatGPT to translate 30 sentences, it correctly rendered 28 from Indonesian into English, but only 19 in the other direction, suggesting that monoglot Americans who turn to the bot to make deals with Indonesian merchants would struggle. The same limited, one-way fluency was found to repeat across at least five other languages.

Large language models' language problems make them difficult to trust for anyone venturing past English, and maybe Chinese. When I sought to translate ancient Sanskrit hymns through ChatGPT as part of an experiment in using AI to accelerate wedding planning, the results seemed plausible enough to add into a ceremony script. But I had no idea whether I could rely on them or would be laughed off the stage by elders.

Researchers who spoke to WIRED do see some signs of improvement. When Google created its PaLM 2 language model, released this month, it made an effort to increase the non-English training data for over 100 languages. The model recognizes idioms in German and Swahili, jokes in Japanese, and cleans up grammar in Indonesian, Google says, and it recognizes regional variations better than prior models.

But in consumer services, Google is keeping PaLM 2 caged. Its chatbot Bard is powered by PaLM 2 but only works in US English, Japanese, and Korean. A writing assistant for Gmail that uses PaLM 2 only supports English. It takes time to officially support a language by conducting testing and applying filters to ensure the system isn't generating toxic content. Google did not make an all-out investment to launch many languages from the beginning, though it's working to rapidly add more.

As well as calling out the failings of language models, researchers are creating new data sets of non-English text to try to accelerate the development of truly multilingual models. Fung's group is curating Indonesian-language data for training models, while Yong's multi-university team is doing the same for Southeast Asian languages. They're following the path of groups targeting African languages and Latin American dialects.

"We want to think about our relationship with Big Tech as collaborative rather than adversarial," says Skyler Wang, a sociologist of technology and AI at UC Berkeley who is collaborating with Yong. "There are a lot of resources that can be shared."

But collecting more data is unlikely to be enough, because the reams of English text are so large-and still growing. Though it carries the risk of eliminating cultural nuances, some researchers believe companies will have to generate synthetic data-for example, by using intermediary languages such as Mandarin or English to bridge translations between languages with limited training materials. "If we start from scratch, we will never have enough data in other languages," says Nguyen at the University of Oregon. "If you want to ask about a scientific issue, you do it in English. Same thing in finance."

Nguyen would also like to see AI developers be more attentive to what data sets they feed into their models and how it affects each step in the building process, not just the ultimate responses. So far, what languages have ended up in models has been a "random process," Nguyen says. More rigorous controls to reach certain thresholds of content for each language-as Google tried to do with PaLM-could boost the quality of non-English output.

Fung has given up on using ChatGPT and other tools born out of large language models for any purpose beyond research. Their speech too often comes off as boring to her. Due to the underlying technology's design, the chatbots' utterances are "the average of what's on the internet," she says-a calculation that works best in English, and leaves responses in other tongues lacking spice.

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ChatGPT Is Cutting Non-English Languages Out of the AI Revolution

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AI chatbots are less fluent in languages other than English, threatening to amplify existing bias in global commerce and innovation.

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Our group says most are using it to generate work because it's easy and they use it for the work that doesn't interest them/they are not engaged in the coursework. Many students do not understand how the use of AI to complete work will affect their learning. Students cannot self-check their learning if they have just uploaded a generated text, so they need to use it effectively/ through Notebook AI for study.

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We shall encourage students to use AI as a useful tool responsibly; students should understand what they have written, we can ask them to read the texts, to paraphrase or clarify their work. As teachers, we act as moderators, facilitators; we guide and make sure that learning has taken place, not just copying. The students should own their work and understand what they have submitted.

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Show students techniques to:

extend vocabulary (e.g. lists of topic specific vocabulary, cognates)

get actionable feedback on their written work (structure, variety of expressions, clarity of ideas)

compare levels of grammar

create study plans

help with email communication with teachers

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For extension students:

Some students struggle to come up with ideas for their speaking and writing tasks. We recommend that they use AI to generate ideas in English first, and then try to construct their speech or writing in Japanese.

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Margarita: Generative AI reduces creativity.

AI creates environmental damage - resources needed to run the data centres are enormous. Some students are reluctant for this reason.

The challenge of teaching students what reality is as opposed to what they see online, which is often arifically generated, such as images of others.

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Focus on the use of AI as a tool, emphasise critical thinking skills, analyse patterns in the language, think about register (formal/informal) and the purpose, audience and context of the text they are writing.  Compare AI feedback and experienced teacher feedback on writing. 

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Focus on the use of AI as a tool, emphasise critical thinking skills, analyse patterns in the language, think about register (formal/informal) and the purpose, audience and context of the text they are writing.  Compare AI feedback and experienced teacher feedback on writing. 

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A student in the beginners Italian course who express concern on her own oversuse of AI. Teacher and student engaged in conversation with students and broke down the non negotianbles and how AI can be a TOOL for learning.

Student is now aware of the impact and ethical use of AI and they have improved in due to the effective use of differente tools keeping the human component and the learning process as the liveline.

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Ke Fan:L As teachers we should always be updating our practice. The students are different every year, as they have different experiences and ways of thinking. How can we engage these students? How can we prepare them for the future when we are not sure what that future will be? People will change careers.

We can train them as critical thinkers, flexible, able to know how to learn.

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We discussed comparisons between teaching "literacy" and teaching "AI", in the context of discussing whether or not it is our role to explicitly teach such things. Jocelyne had a great idea, something useful would be an "AI Literacy Chart", similar to the ACARA literacy and numeracy progressions, that describe ideal behaviours of how students should use AI for differrent things.

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Provide students with tips. Show them / walk them through how to use the app/s effectively and ethically.

Using AI to support creative tasks can be very effective. Examples: Picture book - AI Images

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Coach students how to use AI effectively

Locate main ideas in a text

Sentence starters to co-create work

Ethically use of to create/generate new ideas

Learning how to create revision activities

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Different students use AI for different purposes. Stronger students use AI to extend their language skills and knowledge even further; while weaker students use AI to meet the requirements of the course, therefore to build their confidence. In either case, AI should be used meaningfully, responsibly and with a clear learning outcome.

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Remind students not to put personal information about themselves or others

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Many students are focussed on what they want to say, not demonstrating what they can say and so they want to produce a text expressing themselves the same way as their native language. We need to help them develop the skills to communicate their ideas using the building blocks that they have, through simplification and/or rephrasing, rather than being stuck on expressing themselves identically in their native language. There's also the unavoidable reality that humans, especially children, will naturally look for shortcuts, no quick answer to that but it should be acknowledged as the starting point.

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Chris, Lisa, Daniella, Marina and Marian

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Chris, Lisa, Daniella, Marina and Marian

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AI works both ways, if the teacher is using AI, we need to support our students when they use AI. Help students find the purpose in learning languages/ English as a second language (so students can see the value of studying languages beyond school).

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Formative assessment during speaking lessons (all four skills; especially text production, reading comprehension)

During lessons, check for comprehension of submitted texts that may have been produced by AI

Discuss sample answers produced by AI to understand limitations (e.g. when writing about a prescribed text in Extension)

Model for students how to use AI without compromising their learning

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We need to admit that students are using AI and educate them on how to do it, show them the satisfaction of learning by themselves and motivate them by the joy and satisfaction of learning.

It has been introduced so quickly and education systems are struggling to catch up. We need to create the right conditions for students to achieve. If tasks are too difficult, students will be more tempted to use AI tools.

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Speaking lessons - a chatbot can't replace the human element of listening to a student and providing human feedback.

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1. Activity: Collaborative Songwriting with AI

1. Introduce a Theme or Topic
Provide students with a topic related to the lesson (e.g., nature, friendship, future dreams) to inspire their creativity.

2. Group Lyric Writing
In small groups, students collaboratively write song lyrics in the target language, focusing on vocabulary, grammar, and expressive language relevant to the theme.

3. AI Music Generation
Use an AI music generator to compose a melody and accompaniment based on the students' lyrics. Play the generated songs for the class and discuss language use, creativity, and cultural elements.

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We can have class discussions, individual conversations (speaking lessons), class questionnaires, individual feedback sessions with a student - all of those allow us as teachers to collect student feedback.

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Both teachers and students need to be trained to filter the AI produce text. Wheather it is an email, reports, focus tasks, homework etc. A proofreading for HUMANITY stage is always necessary. This is part of the ethical use of ti!

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Try different AI tools such as Notebook LM and show students how to use these.

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I also add that we should protect processes that develop memory, recall and analysis. Things like memorising vocabulary might seem simplistic or superfluous, but they serve the same purpose as repetitive exercises in the gym, to strengthen the brain muscle!

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Protect and promote Creativity, Human Interaction and thinking independently.

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Question 7

Giving guidance to the students of how to use and not to use AI   - teach them to question AI creditability and critical thinking

We can use AI for preparing resources, lessons plan and assessments

Use as a tool for saving time but not be too reliant

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Question 8

Use for time saving

Use for generating ideas for exam writing

Get ideas about lesson day ideas

Be mindful and remind students and ourselves that AI is not completely free

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For quick check to see whether they're on right track, it saves up time.

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Colonial in Code: How Language Models Mirror Global Power Imbalances

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Bias in, bias out. Explore how colonial legacies live on in AI through biased data, gender norms and linguistic exclusion in large language models.

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Question 9

Promote the idea that students' work should be authentic

Promote the idea that process of learning including making mistakes is important.

Protect the idea that speaking lessons important

Teaching skills based approach ( scaffolding, breaking information into smaller steps according to the individual needs)

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Suggested reading for those interested in exploring the ethics of AI further.

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What's in the box? That's the question almost everyone that Madhumita Murgia speaks to seems to be asking. If the "black box" of the algorithm is going to make critical decisions about our health, education or human rights, it would be nice to know exactly what it contains. So long as it remains a mystery, what can you do if you find your child added to a list of potential future criminals based on flawed, even racist, data, as happened to hundreds of families in the Netherlands in the late 2010s?

It's these Kafkaesque absurdities, and how they play out on a human level, that interest Murgia, the Financial Times's first artificial intelligence editor. Code, she reminds us several times in this troubling book, is not neutral.

This isn't a story about ChatGPT and the other large language models and their looming impact on everything from Hollywood to homework, though there is a bit of that. Instead, it's an account of how the everyday algorithms we have already learned to live beside are changing us: from the people paid (not much) to make sense of vast datasets, to the unintended consequences of the biases they contain. It's also the story of how the AI systems built using that data benefit many of us (you, ordering McDonald's on UberEats) at the expense of some - usually individuals and communities that are already marginalised (the young immigrant worker picking up your Big Mac for a small fee).

Many subcontracted AI labourers are pulled out of poverty by this work but the wealth created by it isn't shared equitably

The scope of Murgia's reporting here, reflective of her day job, is vast. She takes us from the sometimes comically basic way AI systems are trained (workers in a Kenyan office block labelling road signs to teach driverless cars to recognise them) to how its flaws play out in the finished product (the delivery drivers paid less because their app doesn't account for delays caused by roadworks or having to cycle uphill).

Murgia also argues that we are seeing the emergence of a new data colonialism. Yes, many subcontracted AI labourers are pulled out of poverty by this work, but the wealth created by it is not shared equitably. Then there's the sheer monotony of it, the inability to deviate from instructions and regional disparities in pay and job security, not to mention the PTSD that results from being forced to look at the worst images on the internet so the rest of us don't have to. And, crucially, because the AI supply chain is broken down into chunks, many of these workers are told nothing about the purpose of the task they have been given - or even who they're working for.

One Kenyan lawyer Murgia meets sees algorithm training as another version of the Bangladeshi clothing industry that supplies western fast-fashion brands. Or even the designer goods sector: "The factory worker just thinks, all I'm making is a shoe. They don't know their shoe is being sold for $3,000."

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There is a little optimism. Murgia - a former Wired writer - is alive to the potential of AI to improve health outcomes. And we meet people such as Hiba, whose family, refugees from Falluja, in Iraq, used their work as data labourers to fund a new life in Bulgaria. There are also cheering stories of how frustration at being exploited has led to gig economy workers quietly organising - even in China - to regain some of the autonomy they have sacrificed at "the altar of the algorithm".

But the bass note here is pessimistic. We are way past the techno-boosterism of the early 00s, and, for every government official wondering how AI can help them streamline health and welfare services, there are thousands of people asking whether it will allow them to continue making a living. Worse than that, as in the Chinese government's facial recognition systems and pre-emptive detention lists in Xinjiang, it's the story of a dystopia we are already living in.

Code Dependent: Living in the Shadow of AI by Madhumita Murgia is published by Picador (£20). To support the Guardian and the Observer buy a copy at guardianbookshop.com. Delivery charges may apply.

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Code Dependent by Madhumita Murgia review - understanding the human impacts of AI

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Daunting tales of how everyday algorithms are changing us

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This term I will try to encourage my chronic AI users to explain why they use it and what they hope to achieve in its use. I'm hoping they can see the benefits and how they can use it for good rather than the lazy quick fix we can work together to channel the incredible resource AI can be. I hope to get them to articulate the benefits and how they will use AI to their advantage.

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To get their written work done as accurately and as quickly as possible - tick, done.

Unfortunately they do not enter the appropriate criteria to produce texts that may in the end be helpful. If we can teach them to enter parameters of context, audience, purpose, topic vocabulary etc, this will get them thinking more and be working together with the AI tool they choose.

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Students possibly use it when they are time poor. They may also lack confidence in their abilities. The concern is when they rely heavily on this without using critical thinking and not applying the required skills to learn something new or in depth. 

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Students possibly use it when they are time poor. They may also lack confidence in their abilities. The concern is when they rely heavily on this without using critical thinking and not applying the required skills to learn something new or in depth. 