AI for Breakfast

Chris Witham • February 6, 2024

Post 21 – Ethical considerations in Ai development


Early this morning I used the mobile version of ChatGPT on my phone using the voice feature. It transcribed my prompt as follows:


Me: Hey, ChatGPT. Today we’ve got another blog post to do on my AI for Breakfast blog. I’m just wondering if I can ask you what kind of subject should we cover today? That would be good if you could come up with a few suggestions because I’m stumped. We’ve done a few in the past that you can probably reference. We need to come up with just an idea for today’s post.


Strangely this isn’t exactly what I said, I wouldn’t use the words “Hey, ChatGPT” for starters but let’s run with it anyway!


It gave me 5 suggestions, I decided to choose this one:


  • Ethical Considerations in AI Development: A thought-provoking discussion on the ethical dilemmas faced by AI developers and users, touching on privacy, bias, and the future of work.


I chose this one because one of the many e-mail newsletters about Ai that I’m subscribed to mentioned an announcement from Meta about digital ethics, so I went with the timely coincidence.


I thought it might be interesting to ask ChatGPT about this and see what it came up with.


So the following article is unedited, apart from some typographical considerations, straight from the pasted-in prompt above. Bearing in mind I used a custom GPT I’ve built specifically to help me write blog posts for ‘AI for Breakfast’ I think it’s pretty reasonable. You may disagree and that’s fine, I am after all experimenting here so take it or leave it.


In the rapidly evolving landscape of artificial intelligence (AI), the buzz of innovation and technological advancement often overshadows the silent hum of ethical dilemmas lurking beneath. As AI continues to permeate every facet of our daily lives, from the way we work to how we interact with technology, the conversation around its ethical implications has never been more pertinent. Today, I’d like to delve into the ethical considerations in AI development, shedding light on the intricate challenges faced by developers and users alike, including privacy concerns, inherent biases, and the shifting dynamics of the workplace.


Privacy: A delicate balance

The digitisation of our personal lives has led to an unprecedented amount of data being generated, collected, and processed. AI systems, with their voracious appetite for data, play a pivotal role in this ecosystem. However, the question of privacy looms large. How do we navigate the fine line between leveraging data for technological advancement and safeguarding our personal privacy? AI developers are tasked with creating systems that respect user consent and data protection laws, ensuring that personal information is used ethically and responsibly.


Bias: The hidden influencer

Bias in AI is a reflection of the biases inherent in society. These biases can seep into AI systems through the data they’re trained on, leading to outcomes that are prejudiced and discriminatory. The ethical challenge here is twofold: identifying these biases and implementing measures to mitigate their impact. It’s essential for developers to engage in transparent, inclusive practices that encompass diverse datasets and perspectives, striving to create AI that is fair and equitable for all.


The Future of Work: Navigating New Territories

AI’s impact on the labour market and the future of work is a hotly debated topic. While AI promises to streamline operations and enhance productivity, there’s growing concern over job displacement and the widening skills gap. The ethical imperative for AI developers and businesses is to foster an environment where technology complements human labour, rather than replacing it. This involves reimagining the workforce, investing in skills development, and ensuring that the benefits of AI are distributed equitably across society.


As we stand at the crossroads of AI’s potential and its ethical implications, it’s clear that navigating this landscape requires a collaborative effort. Developers, users, policymakers, and the wider community must come together to establish guidelines that ensure AI is developed and deployed in a manner that respects human rights, promotes fairness, and benefits society as a whole.


In conclusion, the ethical considerations in AI development are as complex as they are critical. By addressing privacy concerns, combating bias, and thoughtfully considering the future of work, we can steer the course of AI towards a future that is not only technologically advanced but also ethically sound.


In summary:

  • Privacy is paramount, with a need for AI systems to balance data utilisation and personal privacy.
  • Bias in AI must be acknowledged and addressed through diverse datasets and inclusive development practices.
  • The Future of Work necessitates a harmonious integration of AI, focusing on complementing rather than replacing human labour.
Lines of colorful computer code on a dark background.
By Chris Witham December 11, 2025
Where AI really helps your Business If you spend any time on LinkedIn or X, you’ll have seen bold claims about how AI can help you build software in a matter of days. There’s a lot of excitement, a lot of big promises, and a fair bit of confusion for business owners trying to work out what’s real. A new term doing the rounds is “Vibe Coding” —the idea of describing what you want to an AI assistant and having it generate the code for you. It’s becoming popular because it can move things forward quickly and help people explore ideas they wouldn’t have been able to create alone. And the truth is, it does have its place. The challenge isn’t the technique. It’s the expectation that AI will automatically deliver finished, reliable, production-ready tools without any real design or thinking behind them. AI accelerates the work you already do well Used properly, AI can: • Remove huge amounts of repetitive work • Speed up drafting and iteration • Generate working prototypes in hours • Help non-technical people explore ideas • Improve documentation, planning and communication This is where it shines. But it still needs clarity, structure, and well-designed processes around it. It’s like having a very fast assistant rather than a fully formed development team. Why many AI projects don’t deliver what people expect Independent research this year showed a clear pattern: • Many early AI initiatives failed to produce measurable business value • Companies abandoned AI ideas because they couldn’t scale or integrate them • The gap between an impressive demo and a reliable tool is larger than people thought This doesn’t mean AI is overhyped. It means teams jumped straight to execution without the groundwork. The technology isn’t the issue. It’s the approach. Small businesses don’t need Enterprise Platforms Most UK small businesses don’t need to build a full software product. What they actually need is: • Better workflows • Faster content generation • Clearer communication • Improved customer support • Tools that reflect the way they work • Consistency and repeatability AI is perfect for this. A custom GPT trained on your tone, your documents and your processes can become: • A writing assistant • A customer support helper • A knowledge base navigator • An internal guide for staff • A quality-control layer • A process automator No engineering team needed. No complex infrastructure. No stress. Where AI builds real value right now AI works best when it’s part of a thoughtful, guided approach: • Define the outcome you want • Build a lightweight prototype (AI helps here) • Add structure, rules and guardrails • Connect it to your real workflow • Test it with real users or staff • Iterate until it feels natural You can still move fast. You just avoid building something brittle that breaks the moment it’s needed. The key insight: AI doesn’t replace expertise, it amplifies it AI is at its strongest when someone knowledgeable decides: • What it should do • What it shouldn’t do • How it should behave • What tone it should use • How it fits into the business • What checks and constraints matter That’s where tools like custom GPTs genuinely shine. They’re not software products in the traditional sense. They’re flexible assistants shaped around your business. With the right design, they can save huge amounts of time and deliver consistent, practical value without any of the complexity of building a full system. A more useful way to think about AI in 2026 Instead of “AI will build everything for you”, a healthier mindset is: AI speeds up the work, but you set the direction. For small businesses, that’s more than enough to make a real difference.
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