Author: Graham Attwell

GPT 4 is quite useful for some things. I have been developing four Open Educational Resources around Labour Market Information, designed for careers professionals in different European countries. I was asked to include Issues for Reflection and a short multiple choice quiz on each of the OERs. I fed GPT4 the content of each OER and asked for 6 issues for reflection and 6 quiz questions. Fast as a flash they were done and are (in my view) very good. If I had to have done it without the AI it would have taken me at least half a day.

For other things GPT4 is less useful. And I have to say that its English, although grammatically good, is both stilted and plain. It also has the tendency to use somewhat odd English words, which I had always ascribed to it writing American English. But it seems not. In a Guardian newspaper newsletter, Alex Hern reports on work by AI influencer Jeremy Nguyen, at the Swinburne University of Technology in Melbourne, who has highlighted ChatGPT’s tendency to use the word “delve” in responses.

I have to say that I don't think I have ever used delve in anything I have written And talking to my Spanish English speaking friends none of them even new what the work means, Anyway Jeremy Hguyen says no individual use of the word can be definitive proof of AI involvement, but at scale it’s a different story. When half a percent of all articles on research site PubMed contain the word “delve” – 10 to 100 times more than did a few years ago – it’s hard to conclude anything other than an awful lot of medical researchers using the technology to, at best, augment their writing.

And according to a dataset of 50,000 ChatGPT responses, its not the only one. It seems the ten most overused words are: Explore, Captivate, Tapestry, Leverage, Embrace, Resonate, Dynamic, Testament Delve, and Elevate.

Now back to my hypothesis that its the fault of our American cousins. According to Alex Hearn an army of human testers are given access to the raw outputs from Large Language Models like ChatGPT, and instructed to try it out: asking questions, giving instructions and providing feedback. This feedback may be just approving of disapproving the outputs, but can be "more advanced, even amounting to writing a model response for the next step of training to learn from." And, here is the rub: "large AI companies outsource the work to parts of the global south, where anglophonic knowledge workers are cheap to hire."

Now back to the word "Delve."

There’s one part of the internet where “delve” is a much more common word: the African web. In Nigeria, “delve” is much more frequently used in business English than it is in England or the US. So the workers training their systems provided examples of input and output that used the same language, eventually ending up with an AI system that writes slightly like an African.

A recent report on analysis by the Institute for Public Policy Research (IPPR) said the UK was facing a “sliding doors” moment around its implementation of generative AI, and called on the UK government to ensure that a fair industrial strategy was in place, according to an IPPR Press release. The IPPR paper, The IPPR paper, Transformed by AI: How generative artificial intelligence could affect work in the UK - and how to manage it, by Carsten Jung and Bhargav Srinvasa Desikan. The report identified two key stages of generative AI adoption: the first wave, which is already under way, and a second wave in which companies will more deeply integrate AI tech into their processes - a stage at which it suggests as many as 59 per cent of tasks done by workers could be vulnerable to being replaced by AI automation if no intervention occurs.It said that back office, entry level and part-time jobs were at the highest risk of being disrupted during the first wave - including secretarial, customer service and administrative roles - with women and young people the most likely to be affected as they are more likely to be in those roles. Those on lower wages were also identified as being the most exposed to being replaced by AI.

The study’s worst case scenario for the second wave of AI would be around 7.9 million job losses and no gross domestic product gains (GDP). However, the report suggests that if government and industry are proactive in protecting workers as the use of AI increases, there could be substantial economic benefits.

Its best case scenario for the second wave said no jobs would be lost as they are augmented to work alongside AI, which it claimed could lead to an economic boost of 13 per cent to GDP, around £306 billion (US$386 billion) a year.

IPPR also says that employment of AI could also free up labour to fill gaps related to unaddressed social needs. For instance, workers could be re-allocated to social care and mental health services which are currently under-resourced. But they she the modelling shows that there is no single predetermined path for how AI implementation will play out in the labour market. It also urges intervention to ensure that the economic gains are widely spread, rather than accruing to only a few.

Although the research for this report was undertaken in the UK, It seems likely that the different scenarios, while varying in quantity and impact, will also apply in many other countries.

The IPPR press release can be accessed here and the full report can be downloaded from the IPPR website.