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At Edinburgh, we have a home grown interface to some of the learning models that we're encouraging staff and students to use - ELM - (Edinburgh (access to) Language Models) | Computing | Information Services

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ELM - (Edinburgh (access to) Language Models) | Computing | Information Services

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ELM is the University of Edinburgh’s AI innovation platform, a central gateway providing safer access to Generative Artificial Intelligence (GAI) via access to Large Language Models (LLMs). To find our more about AI at the University see our dedicated AI pages.

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We are advised to use CoPilot and also have Grammarly -Queen Margaret University

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We are advised to use CoPilot and also have Grammarly -Queen Margaret University

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Looking at both AI and GenAI, at Abertay, there's also Padlet's GenAI and Read and Write's AI voices which I don't think have been mentioned yet.

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At St Andrews, Copilot has been made available, but I don't believe we have a curated list of other "approved" AI softwares, as some of the others have indicated.

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So many issues, some raised by Dan McQuillan here

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Questions for Anthropic (or any other LLM-pusher)

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People falling for the 'awe' of supposed AI capabilities and not understanding how much of it is hype - all the while pushing it forward in their institutions

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What We Talk about When We Talk about AI in Education

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What do folks mean when they talk about AI in education? Most of the time – and I’m certainly at fault here too – no definition or description of AI is even offered. You’re supposed to just known what AI means, what it does – or at the least, you’re supposed

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We have had a very limited pilot of CoPilot, and limited projects that have been able to use Open AI APIs either via OpenAI or MS Azure version. Also run some very constrained local LLMs as demonstrators.

But no "wide" availability really, primarily linked to the costs

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Risk of break down in trust between students and staff. Especially when it comes to assessment. Whether or not suspicions are justified ... it's the impact on trust in the educational relationship that's the risk.

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These will all have exclusions/T&C and age limits for staff, students and apprentices to agree to - We are a MS Office place so main one is MS Copilot in Bing, AI Tutor Pro, Claude.AI by Anthropic, Elicit, LeonardoAI, OpenAI ChatGPT, Perplexity, Phind, Satlas, SciSpace, Semantic Scholar.

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Keep hearing chat about how generative AI can adequately undertake literature reviews, synthesise and summarise - lack of engagement with research evidence about how they can't (and functionally will never be able to)

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KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive Reasoning

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Each year, tens of millions of essays are written and graded in college-level English courses. Students are asked to analyze literary and cultural texts through a process known as close reading, in which they gather textual details to formulate evidence-based arguments. Despite being viewed as a basis for critical thinking and widely adopted as a required element of university coursework, close reading has never been evaluated on large language models (LLMs), and multi-discipline benchmarks like MMLU do not include literature as a subject. To fill this gap, we present KRISTEVA, the first close reading benchmark for evaluating interpretive reasoning, consisting of 1331 multiple-choice questions adapted from classroom data. With KRISTEVA, we propose three progressively more difficult sets of tasks to approximate different elements of the close reading process, which we use to test how well LLMs may seem to understand and reason about literary works: 1) extracting stylistic features, 2) retrieving relevant contextual information from parametric knowledge, and 3) multi-hop reasoning between style and external contexts. Our baseline results find that, while state-of-the-art LLMs possess some college-level close reading competency (accuracy 49.7% - 69.7%), their performances still trail those of experienced human evaluators on 10 out of our 11 tasks.

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maybe not the intended question but from 25/26 we will be using the AI Assessment Scale for all taught programmes

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Free versus premium and the gulf between them.

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I concur with the issues raised by colleagues - big concerns re: ethics, sustainability, the accuracy (or lack thereof) of outputs, potential for reinforcing mis/disinformation. But at the same time, there is a need to teach students to use it appropriately.

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We recently had an AI Framework which establishes basic Co-Pilot in Office 365 as the tool that can be used (the exact boundaries are yet to be established), and any public AI tools are can only have publicly available information added to them. We are currently conducting a data protection review of the AI Design Assistant in Blackboard Ultra and we will look to use this when we fully adopt Blackboard Ultra.

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Copilot (not the full license), Adobe CC/Firefly, Otter.ai, Grammarly

Some of our programmes use specific tools: Midjourney; Runway

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Increasing amount of research around how people using AI quickly become intellectually lazy, less motivated or able to think critically etc

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The panic around detection and the potential for student data being added to external tools with no data protection review.

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People who want to resist the use of AI (because it's not inevitable) don't feel like they can because of pressures from higher-ups

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Students new to using AI, thinking it a fountain of knowledge and not lecturers/tutor etc.. - taking what it says for granted, not fact checking, understanding the biases exist and the differences between these in the many different AI tools that are out there.

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Largely self-taught

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Not initally, but I think many of us are learning as we go and asking better questions about it.

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Could certainly do with more development in this area - but finding the time is challenging! We're introducing workshops for staff for the first time this coming academic year.

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I want to see higher education that has standards - supporting students to be critical members of society, upholding ethical standards, choosing not to use tools owned by some deeply problematic characters and that are burning the planet

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New AI features appearing in existing platforms. We want to have some control about whether these get turned on or not based on whether they seem useful and/or have the relevant contractual changes made. We've developed a process to manage this: Scoping AI in EdTech at Edinburgh (SADIE) | Learning Technology | Information Services

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Scoping AI in EdTech at Edinburgh (SADIE) | Learning Technology | Information Services

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The Scoping AI Developments in EdTech at Edinburgh (SADIE) project was set up to standardise an approach for service teams to test and evaluate the utility and suitability of the AI tools and features being made available in the centrally supported EdTech services. The approach developed looked at the risks of adopting a particular feature and calls upon the expertise of learning technologists within the Schools, as well as that of the service managers in Information Services, in evaluating them.

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Hard to keep up and I have not started my Adobe Express training yet so maybe that will improve my work in ways I don't know yet.

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I know plenty about it and how to use it and choose not to use it because it's not good enough and is deeply unethical

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Access to tools

Uneven approaches to assessment module to module (even within same programme)

Uneven approaches to academic integrity between faculties

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I started my AI journey beginning of 2023, I am in AI tools every day, I am on socials that follow AI folks, experts ( so called), and I still feel overwhelmed by it all. Call me sinical, I suspect that is a deliberate ploy by people/companies as its a money maker, by those folks 'selling' you support, how to create AI Agents etc, to companies getting you to take the upgrade with the latest AI [insert whizzy LLM}..

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An argument for providing AI and training at university I keep seeing is that workplaces will be expecting it and using it - evidence suggests this isn't the case, it's not being effectively used in various industries, and it's frustrating that this is used as supposed justification

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After years of depicting Klarna as an AI-first company, the fintech's CEO reversed himself, telling Bloomberg the company was once again recruiting humans after the AI approach led to "lower quality." An IBM survey reveals this is a common occurrence for AI use in business, where just 1 in 4 projects delivers the return it promised and even fewer are scaled up.

After months of boasting that AI has let it drop its employee count by over a thousand, Swedish fintech Klarna now says it's gone too far and is hiring people again.

Founder and CEO Sebastian Siemiatkowski told Bloomberg the company is in the midst of a recruitment drive to ensure customers always have a human to talk to.

"[I]t's so critical that you are clear to your customer that there will be always a human if you want," he said.

The apparent turnaround comes after years in which Klarna touted its all-in-on-AI strategy. A year ago, Klarna said that its chatbot, powered by OpenAI, does the work of 700 human agents and does it much faster. In December, the company revealed that it had hired no human workers for the previous year, with the CEO boasting that "people internally at Klarna are just rallying to deploy as much efficiency AI as they can."

"I am of the opinion that AI can already do all of the jobs that we, as humans, do," the CEO told Bloomberg in February.

It now seems that, while chatbots are cheaper, they're just not as good as humans for some jobs, according to Siemiatkowski.

"As cost unfortunately seems to have been a too predominant evaluation factor when organizing this, what you end up having is lower quality," he told Bloomberg this week. "Really investing in the quality of the human support is the way of the future for us."

A Klarna spokesperson told Fortune the company was maintaining its policy of not replacing employees who leave, outside of hiring freelance customer-service agents for the company's outsourcing division, noting, "we're very much still AI-first."

But when it comes to tempering AI expectations, Klarna is far from alone. Just one in four AI projects delivers on the return on investment it promised, according to a recent IBM survey of 2,000 CEOs.

An even smaller portion, 16%, are scaled across the enterprise, the survey said.

Despite this dismal success rate, companies are going all-in on AI, driven largely by the belief that everyone else is doing it. Nearly two-thirds of CEOs (64%) say "the risk of falling behind drives them to invest in some technologies before they have a clear understanding of the value they bring to the organization," according to the study.

The tech-first-ask-questions-later approach has resulted in some memorable flubs. Air Canada once employed a chatbot that made up a refund policy when chatting with a customer; it was forced to give back $880 to the client despite trying to argue it wasn't responsible for the bot's actions. McDonald's tried an AI-driven system for its drive-thrus for three years before ending the effort. During those years, the system made mistakes like trying to add bacon to an ice cream order and giving one customer an order of 260 Chicken McNuggets.

In Klarna's case, evaluations by outside engineers suggest the bot wasn't bad, just limited.

Gergely Orosz, a tech writer and podcaster, tested the bot last year and found it "underwhelming. It recites exact docs and passes me on to human support fast," he wrote on X, while praising the bot's lack of hallucinations.

"It acts basically as a filter to get to customer support," he said.

Today, that customer support channel is hiring again: CEO Siemiatkowski said Klarna has two new agents acting as freelance customer support. It's also piloting an "Uber type of setup" that lets the workers choose their own schedules and work from anywhere in Sweden, where Klarna is based, at pay starting at 400 Swedish krona ($41.17). Some of these agents, Siemiatkowski said, could even be customers.

"We also know there are tons of Klarna users that are very passionate about our company and would enjoy working for us," he told Bloomberg.
Update, May 9, 2025: This story has been updated with a comment from Klarna on AI strategy.
Introducing the 2025 Fortune 500, the definitive ranking of the biggest companies in America. Explore this year's list.

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As Klarna flips from AI-first to hiring people again, a new landmark survey reveals most AI projects fail to deliver

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Just 1 in 4 AI investments bring in the ROI they promise-but CEOs just can't resist the technology.

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The way that higher education is dancing to the tune of these incredibly powerful, rich and frankly immoral companies. The discourse is totally normalising hugely harmful technologies, and we as a sector are amplifying that by saying it's the future of the workplace and we should be preparing students. It's completely uncritical and antithetical to the common good of higher education.

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Need real time with academic colleagues to explore opportunities for assessment re-design

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Values-led, skills-led, flexible for UG & PGT...

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Academic Integrity, Cognitive offloading, Employability vs AI replacing employment opportunities, Ethics (sustainability & training GenAI Assistants), lack of transparency/black box.

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Academic Integrity, Cognitive offloading, Employability vs AI replacing employment opportunities, Ethics (sustainability & training GenAI Assistants), lack of transparency/black box.

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It's hard to benchmark what those skills are, so unsure how to know if I have the necessary skills. It's quite a challenge.

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I don't have the specialist knowledge to truly upskill my academic staff on how they might really use genAI in a meaningful way in the curriculum, and I don't have time personally or resource in my team to acquire this knowledge and stay current with it in this fast moving environment. So I am frustrated.

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Really concerned that arguments about how great AI is for disabled people (e.g. ADHD, dyslexia, physical disabilities) is just disability-washing a harmful tool that's actually potentially very bad for disabled people

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I wrote this Q&A to help me prepare for a TV interview about AI and disability. I tried to include concrete examples and I steered clear of theory (not my usual approach!). The questions were what I imagined might come up, the answers are my attempt to challenge those assumptions. The answers are disjointed because they're a collection of talking points for a conversation. They boil down quite a lot of background research, and if I get the time I'll add links to the sources. I'm posting them here in case they're helpful for anyone else who wants to challenge the disability-washing of AI. I'd be interested in any feedback and comments, or other examples I could add to the list, so feel free to drop me a line at resistingai@gmail.com.

I would like to thank Rick Burgess of the Greater Manchester Coalition of Disabled People, Louise Hickman and Alexa Hagerty from the The Minderoo Centre for Technology and Democracy, and the artist and game creator Joseph Wilk for trying to clue me up about the technopolitics of disability. Any misunderstandings or clangers are mine alone.

Q. Doesn't AI have amazing potential to help disabled people in all sorts of ways?

Q. Wouldn't it be amazing to have glasses that give you a live audio description of the surroundings?

If you'd seen all the videos I've seen of Tesla's on autopilot crashing into things, you'd think twice about trusting AI glasses.

It doesn't 'see', it's guessing based on what it's been trained on, so anything unusual can throw it.

It's very Black Mirror; the tech companies will control what you get to 'see' (remember Google maps & ads).

Some workers labelling training images for computer vision were told not to include homeless people.

Those glasses would be a privacy-invasion nightmare for everyone else. And who owns all that data?

Q. Isn't it liberating to have an app rather than, for example, waiting to book a sign-language interpreter?

Q. But what about transcribing and captions; isn't this AI loads better than the old tools?

Maybe. The real problem is the fantasy that it's good enough for serious uses.

The Health Secretary, Wes Streeting, is trying to force GPs to use it for consultations.

Research in hospitals shows the AI tools invent things that no-one said.

Other researchers found errors in 8 out of 10 transcriptions.

NHS England is advising doctors to get a lawyer to protect themselves against malpractice from using these tools.

Universities in the USA are firing transcribers and replacing them with crappy AI, so it increases the disadvantage of visually impaired students.

Q. Wouldn't it be great to have a tool that can summarise things for people who can't see, or have trouble with long text?

Q. Even if tools are glitchy, aren't they an improvement for disabled people?

Q. Isn't it a good thing for disabled people to find uses for the latest tech, like AI?

This isn't assistive tech, it's 'screw you' tech.

The tech bros don't care about disabled people or anyone else who's vulnerable.

Otherwise they wouldn't release tools that anyone could see would be used for porn and disinformation, and which make people dependent on them.

They did for their own selfish reasons, for money and power.

Sam Altman, the boss of OpenAI, said "young people don't really make life decisions without asking ChatGPT".

Students aren't just using it to cheat on tests, they're asking what they should do about their relationship problems.

People are already turning to chatbots for support, like the poor lad in the USA who killed himself because the bot encouraged him.

The risk of thinking this is going to help disabled people is disability-washing some very bad stuff.

Q. Why do you say the way that AI is made harms people?

It's like sweatshop labour, but with added psychological trauma.

The tools absorb everything they're trained on, so someone needs to weed out the violence and sexual abuse.

This is done by poorly paid workers, often in poorer countries, who are traumatised by it.

It turns out that there's quite a bit of child labour as well.

Q. Why do you say AI is based on stealing?

Q. If AI is as bad as you say it is, how come governments and investors are putting so much into it?

Telling lies about what AI can do saves our leaders from fixing the basics for everyone, but especially for disabled people.

The government clearly isn't going to do things like tax the rich or the tech companies.

So it needs a way to divert people's attention from how everything is breaking down.

The tech bros have convinced the politicians that AI means growth.

But if we want to fix education & healthcare we need more teachers & nurses and more decent buildings.

AI is more and more becoming a military tech. It's not really helping us much, but it's a boom time for AI weapons.

Q. You say AI is bad for the environment, but aren't there problems with any kind of digital tech?

Yes, but AI is very bad news and it's growing fast.

Musk's XAI datacentre in Memphis has 34 methane generators emitting pollution into the surrounding black neighbourhoods.

When it comes to power cuts or water shortages in the future, it's going to be us versus the data centres.

They're planning datacentres in Oxfordshire but there's already plans for water rationing due to future shortages. Thanks Thames Water!

The GLA had to suspend some affordable housing developments in West London because data centres had already booked all the available electricity grid.

Q. Why do you call AI 'tech solutionism'; surely solutions are good?

Q. Even if it's got problems now, surely AI will have advanced beyond that in a couple of years?

AI is running into a wall; the new models are still crap, and it's never going to have common sense.

One of the so-called godfathers of AI, Geoffrey Hinton, said back in 2016 that we don't need to train any more radiologists because AI could do better cancer scanning,

It turned out to be rubbish. AI scanning has very mixed results at best, so thank god people didn't stop training as radiologists.

The same argument is being used now for nurses, teachers and all the other kinds of care workers we were clapping during Covid.

AI fantasies are going to make things worse for disabled people and everyone else.

Q. Surely AI will save money and make services more efficient for disabled people?

Q. Won't AI make the benefits system more effective?

The same government pushing for AI everywhere is the one that talks about a war on benefits and is going to cut PIP, personal independence payments.

The Department of Work and Pensions is already using untrustworthy AI to classify people's medical conditions for Employment Support Allowance.

Much worse is on the way with the so-called Fraud Error and Recovery Bill where AI will be scanning the bank accounts of everyone who's claiming any kind of benefit.

Introducing AI to the benefits system is going to be like the Post Office Horizon IT scandal on steroids.

Q. Won't AI give disabled people more freedom?

They want disabled people to have ChatGPT instead of having human rights.

We don't need tech that tries to 'fix' people, we need to fix society so it supports people to have autonomy.

At the end of the day, everyone depends on other people, even the tech bros, and any of us can become disabled through age, Long Covid or whatever.

Disabled people are used to hacking tech to make it work for them, but AI is the least hackable.

Q. You're very negative about AI, what would you do instead?

A lot of the money spent on AI should just be used for the basics.

What people mainly want is decent, accessible transport, housing, healthcare and education, not sci-fi toys.

Technology can help disabled people, but that tech development needs to be led by disabled people.

It takes disabled people themselves to understand how and where situations are actually disabling.

We need pan-impairment inclusion, not just some crappy apps built on toxic tech.

We should all, as a society, have a say in what kind of tech is released instead of being used as guinea pigs by big companies.

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I wrote this Q&A to help me prepare for a TV interview about AI and disability. I tried to include concrete examples and I steered clear of theory (not my usual approach!). The questions were what I imagined might come up, the answers are my attempt to challenge those assumptions. The answers are disjointed because they’re a collection of talking points for a conversation. They boil down quite a lot of background research, and if I get the time I’ll add links to the sources. I’m posting them here in case they’re helpful for anyone else who wants to challenge the disability-washing of AI. I’d be interested in any feedback and comments, or other examples I could add to the list, so feel free to drop me a line at resistingai@gmail.com.

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Keep seeing examples of students' work where they've been recommended to use Grammarly - it's giving really bad advice! I tried some of my own work on it and it couldn't make sense of complex sentences, couldn't agree verbs, suggested inappropriate synonyms etc

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But as an IT Developer who has "grown" an educational aspect, the training / develoment for Education sometimes "feels" more hyperbolic, than useful vs. the "technical" or pratical type training you see for developers to build AI tools.

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Supportive of intellectual property and ethical use of information

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Supportive of intellectual property and ethical use of information

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Not supportive of intellectual theft from generative AI tools, which are (all? mostly?) built on stolen content

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I am concerned about the hype in the press, that mention jobs going, and linking in that its generative AI - whilst I do not know anyone in these companies, I do not believe for a second its a free/basics AI versions, of tools ChatGPT, Claude etc that is taking all of these jobs, likely its automation using AI Agents ( at a high cost that these companies are choosing to buy) with more pro AI software, that has been programmes by a human - people using ChatGPT, CoPilot etc isn't going to cause 1000s of job to go.

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EYs points finger at the former head of EY UAE

The UK's Big Four accountancy firms are cutting hundreds of jobs and pulling back sharply on graduate recruitment, as artificial intelligence (AI) begins replacing the junior roles once filled by school and university graduates.

Deloitte, EY, KMPG and PwC - which cumulatively employ around 100,000 people across the UK - have all stripped back early-career hiring over the last two years, slashing intake by as much as 29 per cent, in some cases.

KPMG has made the steepest cuts, trimming its 2023 graduate intakes from 1,399 to just 942.

Deloitte reduced its own scheme by 18 per cent, while EY and PwC followed with 11 per cent and six per cent cuts respectively.

Cost-cutting AI expansion

The job cuts come as firms look to preserve seven-figure partner payouts amid a post-Covid consulting slump, and shrinking client budgets.

Generative AI tools like ChatGPT are increasingly being used to automate administrative tasks usually performed by entry-level employees - accelerating the shift.

"The Big Four are looking at AI very seriously to replicate junior work more cost-effectively", said James O'Dowd of executive search firm Patrick Morgan.

Alongside job reductions, all four firms have expanded their offshoring efforts, pushing more work to lower-cost hubs in India, Malaysia and the Philippines.

Indeed, data has shown that graduate job adverts in accountancy are also down 44 per cent year on year, outpacing the wider slump in overall graduate listings.

AI assurance - the new growth area

Even as they cut junior roles, Big Four firms are racing to profit from the AI boom.

Deloitte, PwC and EY are developing AI assurance services - auditing tools that verify the performance and safety of AI models - in response to escalating demand.

Deloitte's audit partner Richard Tedder called AI assurance "critical to adoption", while PwC is reportedly launching its own service "soon".

This comes amid broader ambitions to position the UK as a global AI hub, with government figures showing AI could add £200bn to the economy.

The same research found that SME adoption alone could offer a £78bn boost over the next decade.

But public trust remains a challenge, with KPMG research showing that just 42 per cent of Brits trust AI, and nearly three-quarters lack formal training in it.

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Big Four slash graduate jobs as AI takes on entry level work

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Th Big Four are cutting hundreds of jobs and pulling back sharply on graduate recruitment, as AI begins replacing the junior roles

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I think HE institutions should take the stance that generative AI isn't ethical for many reasons and as a result they don't support its use

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Creating the conditions for people to feel like they can say no to using it without being accused of being a luddite.

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Institutions concerned with sustainability, social justice etc. and how they can walk that walk while encouraging use of socially and environmentally damaging technology

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It depends on what these skills are. I'd say for everday use it may be straighforward, but what academic skills looks like for Gen AI

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Some forms of AI are demonstrably making improvements to healthcare (identifying cancer early etc) but this is fundamentally different to what's available in HE, when what we're really talking about is LLMs. LLMs aren't improving anything

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How we're going to fix the internet when generative AI has fed so much slop onto the wider web that it means we can't trust the content we encounter

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One of the primary skill required is a critical approach to using the tools; deciding if and when they even need to be used, and then how best to use them.

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love it for sorting out my brain dumps of nonsense and limited use of commas and full stops. Used it to map against standards, for training as a starting point to allow me to step back and see what I had done, compare and review. This quicken up the process by hours, freeing my time for other tasks. I never use it summarise and even personally looking for ideas for a recent trip, it made up pubs/ restaurants to visit, with some 20Km from the local point I asked it to map it to.

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I often encounter colleagues who think AI is working for them and I'm very concerned that they genuinely don't realise it confabulates, can't fact check, can't adequately synthesise information, has bias baked in - some with the Eliza effect in full force. It's hard to know how to challenge some of the misunderstandings about the nature of AI, particularly when there is a power differential

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The ability to evaluate evidence and sources is also key - users need to be able to critique the outputs of AI to decide if they seem plausible on the face of it.

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More 'global' level conversations about where we think this is going. It seems that the tech companies are changing our world in a way that the majority of people have no say in. 

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More 'global' level conversations about where we think this is going. It seems that the tech companies are changing our world in a way that the majority of people have no say in. 

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I guess "authentic" assessment now should be re-defined in light of AI and graduate skills expectations. This is changing heavily across the disciplines.

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Without people able to have honest conversations with students, asking if they wrote X assessments, and students not lying about AI doing the assessments, or even family members, essay mill etc.. Then I suspect, sadly it will either move to closed book exams or would be open book assessments for those that can. The above is from experience, where now I am seeing more students having family members doing their work and they (both students and family), I also suspect they are also the ones encouraging them to use AI tools in their assessments and think that is ok to do - a broader conversation in society is perhaps needed that its ok to fail, not get the outcome you want, including some responsible needs to be on the students - learning is hard, keeping to deadlines is hard along with work/family commitments. Its up to them to do the work with support from lecturers/PAts etc.

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Speaking back to society about GenAI, leading the debates, informing, educating widely - not just our students - about the ethical implications of these tools. Taking back ownership of our expertise and as a place where knowledge and learning is valued and protected.

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A portfolio of secure and open assessments. Authentic assessments and 'process' type assessments.

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A portfolio of secure and open assessments. Authentic assessments and 'process' type assessments.

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Assessments should focus on assessing the process not the output

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1) Having conversations with colleagues about whether to assess use of AI, particularly in a disciplinary context. And the importance of any such assessment linking to their learning outcomes. But we need to think about whether this is appropriate? (i.e. some disciplines it's important to be able to use AI, and some it's not or it's being included because it's the current hot topic)

2) And then ongoing conversations about authentic assessment (although this started well before GenAI became widespread). Thinking about what we are assessing and is it really authentic?

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Information and digital literacy training

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Information and digital literacy training

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Rolling out of something like this course, which can help students (and HE staff) understand the principles of AI

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Technologists and publicists gush about how Large Language Models (LLMs) will revolutionize the way we work, learn, play, communicate, create, and connect to another.

They are right that artificial intelligence (AI) will affect nearly every aspect of our daily lives.

And they are right that by providing a way for people to talk with machines in ordinary language, LLMs constitute a dramatic step forward in making computing accessible to everyone.

Yet for all the good that AI systems will do, they will also saturate our information environment with bullshit at a scale we've never before encountered.

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Modern-Day Oracles or Bullshit Machines: Introduction

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A free online humanities course about how to learn and work and thrive in an AI world.

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There's an increasing amount of research coming out about the impact of use of AI on people's ability to learn, meaningfully engage, apply critical thinking etc. This has implications for students but also in healthcare sector and other sectors.

One study showed that the diagnostic ability of radiologists plummets when they are working in concert with an inaccurate AI.

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Misinformation and its impact on academic research, student assessments, wider social impact

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Misinformation and its impact on academic research, student assessments, wider social impact

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A number of AI-generated and error-ridden books about mushroom identification have been found on Amazon. In a viral Reddit thread, one man claimed that one family ended up in the hospital with severe poisoning after buying and using one of these books. - apply that to an academic context without adequate screening, curation, evaluation etc. - scary