Conference season is well and truly upon us now… Last week, I found myself down at the FourNet event at Mansion House in London, talking about all things data and security. It was quite the venue and an interesting day too.

Unique Insights on Social Engineering

The keynote speaker, Jenny Radcliffe from Human Factor Security, had some really interesting insights – social engineering and physical security in the context of data.

I must admit, listening to her speak seemed to induce a collective minor panic attack about social media and LinkedIn profiles across the room. It turns out that even the most well-intentioned acts can leave us exposed if we’re not careful, and we are all targets no matter where we reside in a company. A few photos here, a comment there, and before we know it, a detailed profile on all our lives, habits, and networks can be stitched together.

It was a sobering reminder of how readily we give away private information without a second thought… I mean we even have to be careful holding doors open for people… so no being polite either – can also be a risk used to gain access!

It was all a stark reminder of the human element in security. It’s not just about firewalls and encryption; it’s about understanding human behaviour and how easily we can become targets.

Some of the examples were eye-opening and a reminder for us all to be more vigilant about the information we share, both online and offline.

Trends in IT Investment

Bryan Glick from Computer Weekly also gave his yearly round-up of IT investment across the UK and Europe.

No surprises that IT investment continues. Although what was interesting was that, outside of known areas such as AI etc., there is also significant investment in HR systems it seems.

For all the talk of returning to the office, there is a significant focus ensuring good people management, and managing people remotely too… “Follow the money” is the adage that came to mind here… I am not so sure hybrid working will quickly go away now, despite the beating drums in the media.

A Glimpse into the Future

These events are always a melting pot of ideas, insights, and reflections on the current state of the industry, shedding light on the challenges and opportunities ahead.

As we delve deeper into the autumn, it’s fascinating to see these emerging trends and innovative solutions.

So, more insights expected this week, and at some point, I hope, it will calm down. In the meantime have a good week everyone.

Increasingly, the words ‘Artificial Intelligence’ (AI) are not limited to the realms of science fiction. They’re being used more frequently and interchangeably in the domains of technology, business, and even our everyday lives.

The Hype and Its Ramifications

The term “AI” is buzzing, selling newspapers, software, and technology. Before long, it might even be promoting breakfast cereal. The hype cycle is upon us. This term is thrown about as a catch-all phrase. The incessant chatter revolves around its potential applications, how it’s revolutionizing industries, and its potential to solve the world’s most complex problems. While some of these assertions are undoubtedly true, this approach can be overly simplistic and, at times, potentially wildly inaccurate. AI is a blanket term that encompasses a vast array of techniques, and I find the broad usage increasingly frustrating.

Understanding the Nuances of AI

At its core, AI relies on mathematics and mathematical techniques to determine outcomes. However, the purpose and nature of those outcomes matter significantly. By lumping them together, we risk undermining and conflating their capabilities. So, when we refer to AI, what exactly do we mean? Decision science? Predictive modeling? Machine learning or generative predictive text? Are we aiming to forecast future events or merely predict the next word or image/letter based on historical data? Understanding these outcomes is crucial.

Another intriguing aspect is our evolving relationship with computers. Historically, we’ve perceived computers as precise, engineering tools that operate error-free, in contrast to fallible humans. Although these new AI techniques run on computers, their outputs have become more probabilistic, imperfect, and, in a sense, more human. However, our language still clings to the old paradigm where “the computer is always right.” This perspective might need updating.

The AI Assistant

Personally, I view these new Generative Predictive Text models as helpful assistants—aiding, streamlining processes, and enhancing efficiency. Yet, they still require oversight to ensure the quality and accuracy of their outputs.

In the long run, perspectives will evolve. But for now, let’s ensure we’re not solely chasing the hype and begin to speak more precisely. After all, precision is where the real benefits and productivity lie.