Introduction To AI & The Future of Work

Welcome to AI & The Future of Work — a weekly newsletter at the intersection between AI technology and people at work. I'm Larry Maguire, work & business psychologist, lecturer in work and organisational psychology, and writer. Before psychology, I spent 20+ years in the electrical business, security systems, home automation and systems integration. Technology and gadgetry has always been a core interest. Human behaviour has been too, and now — not so much by design — I find myself occupying the ground where these two interests merge.

Call it the Socio-Technical space where the behaviour and social interaction of human beings meets artificial intelligence. The idea is that technical and social systems are interdependent. So improving one requires us to consider the other to ensure successful outcomes for people and organisations. And now, in this rapidly changing world of work, keeping people at the centre of our conversations and planning has become vital.

I've been helping professionals and educators put AI to work in real contexts since 2023 when my colleague Bernard Goldbach suggested a collaboration. We built what was one of the first Generative AI skills programmes in Ireland and have been delivering to business people and educators around the country since. In excess of five hundred people have taken the programme in its various forms to date, and we continue to iterate based on changes in generative AI capability.

Separating signal from noise in the AI conversation is harder than it should be. AI evangelists promise transformational gains — faster decisions, improved efficiencies, greater profits, broader access to expertise, entire categories of drudgery eliminated. In parallel, respected sceptics like Gary Marcus and Meredith Whittaker warn of job displacement, algorithmic bias, environmental cost, and a troubling concentration of power in the hands of a few Silicon Valley corporations.

If you're selling an idea — like AI will change the world for the better — I'm unlikely to take you at face value. After all, you have a vested interest in my buy-in. In that, I am a sceptic. Nonetheless, I have an optimistic outlook. I love the things that generative AI can do while being distinctly aware of its limitations and risks to privacy. So everything I write here will come from that sceptical yet optimistic position.

I'm not selling you a technology. I'm selling you a philosophical position and a framework for thinking about and interacting with Generative AI applications.

I'm not selling you a technology. I'm selling you a philosophical position and a framework for thinking about and interacting with Generative AI applications. This is no-code stuff, by the way — no computer science degree required.

Separating signal from noise in the AI conversation is harder than it should be — and everything I write here comes from a sceptical yet optimistic position.

Who's This Newsletter For?

There's a lot to digest, a lot of noise, and vested interests vying for your attention and your money. So I decided to put this newsletter together to share my own experience using and teaching AI. And not least because the topic captures my interest like nothing else.

This newsletter is for you if you want to better understand how artificial intelligence is impacting the world of work. If you want to develop your AI skillset, become more productive and creative, understand the pros and cons of AI, and make better business and career decisions — you're in the right place. If you don't code and have no time or desire to, you're also in the right place.

What You'll Learn

• How to brief AI tools accurately — stop getting vague outputs by learning to give clear instructions with context, sources, and constraints
• Where AI actually saves time — which tasks genuinely benefit from automation and which still need human judgement
• Spotting AI hype versus reality — cut through vendor promises and understand what generative AI can and cannot do in your work
• Privacy and security basics — what data you should never put into public AI tools and how to protect sensitive information
• Critical thinking with AI outputs — why you must verify, fact-check, and sense-check everything AI produces
• The socio-technical balance — how to implement AI without ignoring the human and organisational factors that determine success or failure
• Latest research findings — summaries of peer-reviewed studies on productivity, bias, job displacement, and organisational impact
• Ethical and governance considerations — understanding algorithmic bias, power concentration, environmental cost, and regulatory developments

Quick Win For This Week

Use the GCSE Prompt Framework to get better results from your GenAI application:

1. Define the Goal — State the outcome in one sentence. Example: "Draft a 400-word project update for stakeholders with risks, decisions, and next steps."
2. Give the Context — Two to three bullets with audience, constraints, and relevant facts.
3. Provide Sources — Paste or link to the authoritative materials the model must use. If none, say so and request assumptions be explicitly listed.
4. Set Expectations — Specify format, tone, length, and what to avoid. Add a simple scoring rubric: "Rate your draft against clarity, accuracy, and actionability from 1–5 and revise anything under 4."