There seem to be two common themes for people working in tech.
The first is that they’re deeply passionate about technology – the potential future capabilities as well as how it’s revolutionized business and life in the past half century. The second is that there’s an awareness that at some point in their career, they’ll be let go. i.e. Thank you, but you are no longer needed.
It’s a harsh reality that leaves many disillusioned about the industry. They’ve built amazing things, been part of amazing teams. Many still somehow manage to stay positive. Yet the reality remains, the tech industry is volatile, mass layoffs are common, and in the US especially, they happen with brutal efficiency.
Some people wonder what all the tech building is for, especially if human value is seen as temporary. The most recent trend is to get people to train AI so that it can do their jobs more efficiently. There’s the promise that AI is not there to replace, it’s there to augment efforts.
In the sales pitch, the emphasis is placed on the value of tech. The investments are courted on the basis of tech advancements. The promotions? They’re all about the love of tech and the benefits it delivers.
Is this what’s powering the deep loyalty to tech, despite the recurring pattern of layoffs or negative treatment of people working in the industry, or is it something else?
For those working in tech, the passion for development and advancement doesn’t seem to wane. Perhaps this is due to the outpouring of support from industry colleagues. Maybe it’s the endorsement of skills that helps to usher in the next opportunity. Regardless, tech building continues.
Is this due to a curiosity to see what’s possible? Remember when it was said that AI is good for crunching data, but would never have the ability to create music, art or content? Well, that myth has truly been busted – excluding the debate, of course, as to the quality of outputs or the ethics on how the training material was obtained.
The reality is that it was said that it couldn’t be done, and now it has been done. What’s next? And is a shift in focus in delivering actual value for humans needed? Time saved, effort saved – those have been big promises as GenAI was rolled out, but quality matters too.
If tech is there to augment and support human efforts, accuracy is vital. No time is saved if outputs are inaccurate or need to be significantly improved upon. Perhaps the value in tech needs to be focused on humans and what they need, both as developers and users.
In development there’s a real need to reduce bias and improve accuracy. Humans understand context, nuance and outliers – concepts that are foreign to LLMs but that are factors influencing both flaws in AI. For those passionate about building great tech, could this be the area where to add the most value right now?
