Taccle AI

Improving skills and competences of VET teachers and trainers in the age of Artificial Intelligence

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AI and the future of jobs: An update

Graham Attwell 74 Views 0 Comments , , , , , , ,
Elise Racine & The Bigger Picture / Better Images of AI / Web of Influence I / CC-BY 4.0

One feature of the ongoing debates around Generative AI is that almost everything seems to be contested. While the big tech companies are ever bullish about the prospects for their new applications, controversy continues about the wider societal impact of these tools, including on education and employment.

Despite the initial concerns of the impact of Generative AI on employment, it seemed that fears were overblown although this may now be changing. Even so replacement of staff by AI may depend not just on sectors and occupations but all on the organisation and size of companies. Of course the motivation of companies to invest in AI is to increase profits. And it may be that the scale of organisational and work flow change required to introduce more AI has led to smaller companies holding back, was indeed with the ongoing doubts about the reliability of Generative AI applications. However there are signs of increasing use of AI in the software industry, albeit for boosting the speed to developing code, leading to higher productivity, and with more aggressive companies like Meta’s CEO Zuckerberg saying AI will replace mid-level engineers at Facebook, Instagram, and WhatsApp by 2025. Zuckerberg recently said that Meta and other tech companies are working on developing AI systems that are able to do complex coding with minimum human interactions. There is little doubt that creative jobs in the media film and advertising industries are coming under pressure with the increasing adoption of AI. The World Economic Forum (WEF) recently released its Future of Jobs Report 2025, including the finding that 40 percent of companies plan workforce reductions due to AI automation. But the report also finds that AI could create 170 million new jobs globally while eliminating 92 million positions, resulting in a net increase of 78 million jobs by 2030. Of course the key word here is “could”.

There are two ned developments which are worrying for future jobs. The first is AI agents which are the latest products from the big tech industry. These are designed to split up work tasks and undertake the tasks semi autonomously. But for all the hype t remains to be seen how effective such agents might be. And the second is the increasingly use of AI for training robots. Robots have previously been difficult and expensive to train. AI may substantially reduce the cost of training leading to a new wave of automation in many industries.

But all this is speculations and finding reliable research remains a challenge. From an education and training perspective it seems to point to the importance of AI literacy *as an extension of digital literacy) and the need to ramp up continuing training for employees whose work is changing as a result of AI. Interestingly the WEF report found that 77 percent of surveyed firms will launch retraining programs to help current workers collaborate with AI systems between 2025 and 2030.

About the Image

'Web of Influence I' is part of the artist's series, 'The Bigger Picture': exploring themes of digital doubles, surveillance, omnipresence, ubiquity, and interconnectedness. Adobe FireFly was used in the production of this image, using consented original material as input for elements of the images. Elise draws on a wide range of her own artwork from the past 20 years as references for style and composition and uses Firefly to experiment with intensity, colour/tone, lighting, camera angle, effects, and layering.

News Project 

Digital Pedagogies Rewilded

Graham Attwell 466 Views 0 Comments , , , , , ,
Ed Dingli for Fine Acts

I've written a lot about AI and education over the last year. I've not written so much about AI and learning and I'm going to try to remedy this in the next year. I've been writing for the AI Pioneers project in which Pontydysgu is a partner. But of course AI pioneers is not the only project around AI funded under the European Erasmus+ project.

And I very mush like the HlP - Hacking Innovative Pedagogies: Digital Education Rewilded Erasmus+  project carried out by the University of Graz, Aalborg University and Dublin City University.

They quote Beskorsa et al. (2023) saying:

Hacking innovative pedagogy means using existing methods or tools, spicing them up with creativity and curiosity and then using them to find new, exciting, or out-of-the- box solutions. It fosters experimentation, exploration, collaboration, and the integration of technology to promote critical thinking, problem solving and other key 21st century skills.

The web site is beautifully designed and a lot of fun.

And on February 20 and 21 they are holding a symposium in Dublin. This is the description:

A symposium for thinking otherwise about critical AI and post-AI pedagogies of higher education as part of the Erasmus+ Hacking Innovative Pedagogies: Digital Learning Rewilded (opens in a new tab)project.

This symposium aims to bring educators, learners, and interested others together to see how we might co-design futures beyond the calculative and output-obsessed forms which GenAI could funnel us into if we are not careful. It seeks to explore ways of teaching and learning that are based on mutualism, that recognise teaching as distributed activity and that honour our deep imaginative capacities for good (Czerniewicz & Cronin, 2023). We need to craft critical, creative and ethical responses in community to help address the multitude of issues now posed to educational assessment, future jobs, the environment, biases and increases in cyber-crime and deepfakes.

Come and help us think together during this event so as to rewild our pedagogical thinking and futures dreaming (Beskorsa et al, 2023; Lyngdorf et al 2024). In the words of Dr. Ruha Benjamin, we invite you to “invoke stories and speculation as surrogates, playing and poetry as proxies, and myths, visions, and narratives all as riffs on the imagination” (Benjamin, 2024 p. ix).

The symposium is free to attend, in person or online.

News 

AI – Productivity, Jobs and Skills

Graham Attwell 190 Views , , , , , ,
Hanna Barakat + AIxDESIGN & Archival Images of AI / Better Images of AI / Textiles and Tech 1 / CC-BY 4.0

Much of the big excitement about Generative AI was driven by the idea that it would boost productivity (and thus profit). Conversely one of the fears was that it would lead to job losses although there was little or no consensus about how severe such job losses might be and indeed some commentators speculated that new jobs created by AI would balance out the losses.

Early research and reports into the impact of AI were conflicted, with increasing levels of hype perhaps overwhelming more sober research findings. And even now there is only a limited consensus of the impact of Generative AI on employment. Lets look first at productivity. Early research has tended to emphasize that less experienced staff have gained most from using AI,with only limited gain from more senior employees, although of course there are big differences between sectors and occupations. A recent report – Reclaim your Day – the impact of AI PCs on Productivity - about a study by Intel, which tried to see if AI can save time and boost productivity, found that “current AI PC owners spend longer on tasks than their counterparts using traditional PCs.” According to the study, the users of these AIs spent a long time trying to identify “how best to communicate with AI tools to get the desired answers or response,” which is why they took longer. However, there is also a stark lack of data in the report on how much time was spent monitoring and correcting these AIs’ outputs. Despite this the study was optimistic, stating that people need to be better educated on using these AI tools.

Women in Technology has published a study by Sarah Writtenhouse entitled The Great Tech Job Migration is Upon Us - What you need to know about how jobs are adapting to the new tech climate (Paywalled), looking at how jobs in the software industry are changing. The software industry is interesting as thgi sis one of the sectors for which the big Gen AI companies have claimed big productivity savings. Software jobs were already in decline but Writtenhouse says that Software Development jobs postings on LinkedIn fell almost 25% in October this year, shrinking from 22,000 to just under 17,000. But not all is as it seems Writtenhouse says:

“These jobs are just evolving into the next generation of software development work by adding new skills to new job titles.

AI, ML, and Cloud Computing Engineers — Just new names for “Software Developer”

In terms of skills she says “Python, Java, and C++ are still core skills, but an added upskill to ML frameworks, cloud AI toolsets, and LLM models create new AI-centric development jobs… oops, I mean AI-centric engineering jobs.”

It seems AI Engineer postings rose sharply in October, increasing 55% from 10,000 to almost 16,000 from September with a doubling in openings for Cloud Computing Engineers and ML Engineers. Similarly there was an increase in demand for Data Analysts, Data Engineers, and Data Scientists.

I suspect that changes in skills demand and job titles may be more significant than overall employment in different sectors,. However this suggests that there is going to be higher levels of advanced skill training. It may well be that those working in the software industry are used to fast moving technology change but this may not be reflected in others sectors where professional training is needed to help employees keep up.

About the image

Textiles and Tech' intertwine the visual elements of circuits and textiles, merging the past and future, wires and strings. The collages draw inspiration from the history of 1960s Silicon Valley, where Navajo women were employed by Fairchild Semiconductor for their weaving expertise to assemble circuits that laid the groundwork for today’s microchips. By compiling archival images of hands, the series seeks to personify the anonymity of tech labor. The strings and wires running through the visuals encourage viewers to reflect: what is uncovered when we pull on these threads?

News 

Do we need specialised AI tools for education and instructional design?

Graham Attwell 163 Views , , , , , , , , , ,
Photo by Amélie Mourichon on Unsplash

In last weeks edition of her newsletter, Philippa Hardman reported on an interesting research project she has undertaken to explore the effectiveness of Large Language Models (LLMs) like ChatGPT, Claude, and Gemini in instructional design. It seems instructional designers are increasingly using LLMs to complete learning design tasks like writing objectives, selecting instructional strategies and creating lesson plans.

The question Hardman set out to explore was: “how well do these generic, all-purpose LLMs handle the nuanced and complex tasks of instructional design? They may be fast, but are AI tools like Claude, ChatGPT, and Gemini actually any good at learning design?” To find this out she set two research question. The first was sound the Theoretical Knowledge of Instructional Design by LLMs and the second to assess their practical application.She then analysed each model’s responses to assess theoretical accuracy, practical feasibility, and alignment between theory and practice.

In her newsletter Hardman gives a detailed account of the outcomes of testing the different models from each of the three LLM providers, But the The headline is that across all generic LLMs, AI is limited in both its theoretical understanding and its practical application of instructional design. The reasons she says is that they lack industry specific knowledge and nuance, they uncritically use outdated concepts and they display a superficial application of theory.

Hardman concludes that “While general-purpose AI models like Claude, ChatGPT, and Gemini offer a degree of assistance for instructional design, their limitations underscore the risks of relying on generic tools in a specialised field like instructional design.”

She goes on to point out that in industries like coding and medicine, similar risks have led to the emergence of fine-tuned AI copilots, such Cursor for coders and Hippocratic AI for medics and sees a need for “similar specialised AI tools tailored to the nuances of instructional design principles, practices and processes.”