I was disheartened to see that the number of adult learners in England declined by 47% between 2010-11 and 2022-23. This decline is most pronounced in the most deprived areas of the country, exacerbating the existing skills divide. At the same time, business schools recognise the need for AI upskilling and are responding by developing new offerings to meet the evolving needs of executives and organisations and whilst there is a shortage of experts to teach the courses, it seems clear that those who can afford it will be able to get the skills they need. Sadly, the majority risk being left behind unless a concerted effort is made to increase adult training.

There are also questions about job satisfaction as AI completes more of the mundane work tasks to boost efficiency, the rise of AI also raises questions about the role of human judgment, creativity, and interpersonal relationships. Organisations that thoughtfully navigate these issues and find ways to leverage AI while empowering their employees will undoubtedly thrive in the AI era.

And employees with skills will likely do very well - 97% of IT jobs that pay over £100,000 now require AI skills as a core requirement and in general workers with AI skills are well-positioned to command an average skill premium of 21% compared to their peers without such expertise. 66% of executives at the vice president level or above state that they would not hire an applicant for a senior position who lacked knowledge of using basic generative AI tools. However, the ability to build applications using AI opens up even more opportunities, positioning job seekers as highly sought-after candidates in various industries.

Khan Academy announced that it is collaborating with Microsoft on AI in education and just to put the pressure on, OpenAI co-founder Greg Brockman and Khan Academy founder Sal Khan suggested that the window of opportunity for starting AI initiatives in education is closing rapidly. I find that hard to believe. I can understand why they would want us to believe that time is tight, but the truth is that we are only at the start of what will inevitably be a considerable a long journey for AI in education. It is also the case that building AI tutors that are truly helpful and natural to use is extremely hard and without advancing our understanding of a learner's context and evidence of delivering consistently helpful results, we should maintain some healthy scepticism.

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Meanwhile, Google published an intriguing paper, "Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach." The paper reports research that underscores the potential for sector-specific data to refine and optimise AI models for particular applications, such as education. The authors call for collaborative development of shared pedagogical benchmarks in the AI and education sector to drive evidence-based progress. They also acknowledge the technical limitations of their LearnLM-Tutor. For example, it is text-only, lacks full understanding of context, cannot leverage non-verbal cues, and may hallucinate information. Sociotechnical limitations include less personalisation and rapport-building compared to human tutors. They stress that more research is needed on effective human-AI collaboration in education. A finding that will be recognised by all those of us who have been working as part of the AI and education community for the past few decades.

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The relentless march of technological progress continues, from OpenAI's GPT-4o launch and Google's enhanced Gemini 1.5 Pro and Gemini Live voice chat app, to the development of smaller language models by Microsoft, Google, Meta, and Apple to address concerns over the costs and resource demands of large language models (LLMs). Chinese AI companies offer "AI-in-a-box" products for businesses to maintain data and operations in-house, while Apple's OpenELM family of open-source, smaller LLMs prioritizes user privacy by running on Apple devices. Amidst this progress, big tech's disingenuity persists, from OpenAI's 'Sky' voice controversy to Meta's simultaneous release of the open-source Llama 3 LLM and expressions of their own scepticism regarding the safety and human-like intelligence of large LLMs. Microsoft's "Windows Recall" also raises questions, granting their AI co-pilot a "photographic memory" of user activity without clear justification.

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As Abba famously sang, "Money, money, money." The unabated flow of substantial investments in AI continues, exemplified by Saudi Arabia's $100 billion commitment to become a global AI hub and diversify its economy. With investors demanding swift returns, the pressure to innovate may overshadow considerations of safety and ethics. Regrettably, this climate could exacerbate the existing lack of transparency from AI companies at a time when public trust and collaboration between companies and regulators are paramount for the responsible development and deployment of AI technologies. Whilst on the subject of money, Nvidia, the leading AI chip manufacturer, reported a staggering 262% revenue increase in the past quarter, underscoring the immense financial potential in this field.

As we all try to safely navigate this complex and rapidly evolving landscape, let’s remain committed to the thoughtful and ethical advancement of AI in education. Collaboratively, I continue to believe we can work towards a future where the benefits of AI are harnessed for the greater good, while vigilantly safeguarding against potential pitfalls.

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