Learning via AI
In 1990 I was working at the DWP (Department for Work and Pensions). I had just taken the role of Computer Support Officer where I administered user access to the mainframe and provided first line support to staff using the terminals. That summer the office moved to a PC based network and the project was undertaken by the newly formed Siemens Nixdorf company. To cut a long story short I befriended one of the contract engineers and over the next 9 months he became an unofficial mentor to me. Technically he was only supposed to train me in the most basic of fashions but he liked the fact that I was always asking questions and effectively ended up schooling me in PC and server architecture, network administration and the associated protocols. For me this was the best way to learn. It was not a case of coming to grips with theory in a classroom environment. It was learning by doing and having direct and exclusive access to a source of knowledge and experience.
Throughout my career in IT which ran until 2016, I always enjoyed the fact that there were always professional colleagues available who were happy to share knowledge. We would all call each other if something came up that required additional information. There would be a few engineers who were cagey but they were soon sidelined from our shared, informal ad hoc pooling of knowledge. One of the aspects that I liked so much about my career was the opportunity to continuously learn and challenge my assumptions. A lot of the time in IT, you would work alone so your successes were yours. However, having access to a network of like-minded friends and colleagues was an invaluable resource. One that I now miss. Not only because it was a great means to learn something new or solve a problem but because there was a social component to this network. We would often meet up for drinks after work and swap stories and news.
I have embarked on several technical projects recently and it’s extremely frustrating when I grind to a halt due to gaps in my knowledge. Having been out of my line of work for over a decade, I no longer have access to people “who know”. So I have started using AI as an alternative. As my questions have become increasingly complex, I’ve started subscribing to Google Gemini so that I don’t run into any kind of cap or restrictions. The results have proven broadly positive although there has been issues along the way. Overall, I haven’t changed my position on AI. It is a tool and like all tools can be used efficiently and effectively or it can be misused. I don’t use it for writing and only generate images for my own amusement. As far as providing technical support it is very useful, especially with simple coding issues or troubleshooting software. However, it does have its own foibles, or at least Google Gemini does, which have to be worked around.
Simply put Google Gemini is a pedant. If you ask a broad question you can and often will get a broad answer. Hence you have to be very specific and detailed in your questioning. It takes a while to find the right level of information you need to provide and the learning curve can be frustrating. I asked multiple questions about setting up the live streaming software OBS. I wanted the stream to be in 2K resolution and there were all sorts of configuration settings, many of which were linked to which make and model of graphics card you have. Google Gemini would often reference setting by names that were not present in the version I had installed, so all my subsequent questions had to reference the software version number to ensure relevance. As Google Gemini’s “knowledge” is drawn from the websites that it parses, there is often a bias towards whatever has been written about the most. Hence its answers although correct, may not be the most recent.
Hence AI’s need to be addressed in a very specific manner. Often you feel that your not only asking questions but you’re also like a sheep dog; trying to steer the entire undertaking in the right direction. Google Gemini now has the capacity to retain your previous questions to try and get a better overall understanding of what you’re working towards. Obviously this is a privacy issue and comes down to personal choice but I have allowed it for the present as none of my questions are about me personally. They are simply technical enquiries relating to minor tasks I’m undertaking. I do not use AI to do such things as write letters, compose emails as I am more than capable of doing such things for myself. Hence for the present, Google Gemini is not accessing vast swathes of personal information about me. Unless asking lots of questions about specific video games and their respective mechanics provides any insight.
The one thing that AI cannot provide is the social aspect that comes with shared problem solving with a network of professional colleagues. Often exchanging information with colleagues is done after work over drinks or a meal. The social component often leads to wider friendships. That aspect is not present when you’re learning via an AI. Mind you, the latter can be a lot cheaper, as you don’t have to buy it a pint either or make small talk with it. Joking aside, both methods of sharing knowledge and learning have their respective merits. My recent experience using Google Gemini has been a very interesting experience. The quality of answers the AI gives increase in the quality once you start subscribing and accessing a more advanced version. However, while writing this post and reflecting upon the network of colleagues that I use to have, has made me realise how much I miss both their expertise and company.
