Day: 14 September 2024

In this interview, we dive into the exciting world of artificial intelligence with computer expert Svend Albertsen, the founder of Albertsen Informatique and President of the Professional Chamber of Experts of Monaco.

Here, Svend breaks down the complexities of AI, from the basics to the cutting-edge developments shaping its future, while also tackling some of the ethical issues that come with this fast-evolving technology.

Whether you’re just starting out with AI or want to expand your knowledge, this conversation will shed light on how AI is impacting industries like finance and healthcare, what it means for everyone’s daily life and what the future holds for this game-changing field.

(This is a summarised version of the podcast interview with Svend Albertsen. To listen to the podcast, press play below.) 

Monaco Life: How would you describe AI to someone who’s just starting to learn about it?

Svend Albertsen: That’s a good question! To put it simply, artificial intelligence has one goal: to reproduce the way a human behaves—thinking, talking, understanding and reasoning. A famous figure, Alan Turing, developed a test in the 1950s known as the Turing Test. His idea was that if a human could not distinguish between talking to another human and a computer, then the computer was considered to possess artificial intelligence. Essentially, if you can’t tell the difference between a human with knowledge and a computer with knowledge, that’s AI.

What is the core difference between AI and traditional computer programs?

Traditional computer programs operate with predefined rules. The programmer sets instructions like, “If you do this, then do that.” There’s no learning involved in these systems. However, with AI, the computer is provided with vast amounts of data—whether it’s text, images or even video—and through a complex system, it learns. This concept of learning is different because while the computer isn’t truly understanding, it’s able to reproduce answers based on the data it has been trained on.

Could you explain a bit more about how AI learns and improves over time?

It’s a complicated topic, but I’ll simplify it. AI learns from massive amounts of data, which can include text, pictures, drawings, audio or videos. There are generally three major steps in learning. The first is unsupervised learning, where the AI is given a lot of data, but no labels. For example, we might give it images of tomatoes and carrots, but we don’t tell it which is which. The second step is supervised learning, where we label the images and teach the system to differentiate between them. Finally, there’s reinforcement learning, where the system receives feedback—positive or negative—based on its responses. It’s much more complex than that, but this is the general idea.

There are different types of AI. Could you break down the main ones and how they differ?

AI is often categorised into three main types. The first is Artificial Narrow Intelligence (ANI), which is the AI we have today. It’s specialised to perform specific tasks. For example, an AI in a self-driving car can only drive the car—it can’t select music or recommend products like other AIs might.

The second type is Artificial General Intelligence (AGI). We’re not there yet, but AGI would be on par with human intelligence. It could answer questions on various topics, reason and analyse just like a human. Some believe AGI might be achievable within a few years, while others think it’ll take longer.

The third type is Artificial Super Intelligence (ASI), which is an intelligence far beyond human capabilities. This concept is still speculative, and opinions vary on when or if we’ll ever reach ASI. It’s the stuff of science fiction, but some believe it could happen within decades, while others think it may never be realised.

We spoke a few months ago, and things have already changed dramatically. What recent developments in AI have caught your attention, and how are they shaping the future of this technology?

AI is evolving rapidly. In my 40 years in the tech industry, I’ve never seen anything move so fast. The most significant recent developments are in generative AI, like ChatGPT, Gemini and Claude. These systems are becoming almost human-like in how they interact. For example, a recent Turing Test with ChatGPT showed that we are there, and in some cases, it even performed better than real humans.

Generative AI is changing the way we approach creativity. It can write poems, create images, generate videos and even answer questions in a conversational manner. The new versions of these AIs, like GPT-4, can now engage in real-time conversations, detect emotions based on voice, and soon, they’ll even be able to interact with cameras, analysing images or videos in real time.

That’s incredible. Could you explain what generative AI is and how it’s impacting creative industries?

Generative AI is truly fascinating. It’s an AI that can create—whether it’s text, music, art or videos. Many people were amazed when ChatGPT was first released, expecting it to be limited to technical tasks. But instead, it showed immense creativity, composing songs, writing poems and summarising or editing text.

We also have AI tools for generating images, like DALL-E and others like MidJourney and Stable Diffusion, which are excellent at creating visuals. OpenAI has announced a video creation tool called Sora, which can generate short videos based on text prompts. The tool allows you to refine and adjust your video just by talking to the AI.

This makes content creation easier, faster and more accessible to everyone, which is revolutionary.

AI is impacting many industries, but what about non-creative sectors like finance or manufacturing?

AI is already benefiting nearly every industry. In finance, for instance, AI is used for fraud detection and automated trading. Many banks rely on AI to detect unusual patterns in transactions, like flagging your credit card if you make a purchase in an unfamiliar country.

In manufacturing, AI plays a significant role in robotics and automation. Predictive maintenance is also crucial, where AI systems can predict when machinery might need servicing, preventing costly breakdowns. Big companies like Amazon use AI to optimise their supply chains, ensuring efficiency in everything they do.

What about healthcare? How is AI being used there to improve diagnosis and treatment?

Healthcare stands to benefit greatly from AI. We already see AI systems analysing medical images like X-rays or MRIs to detect diseases, heart conditions or neurological disorders with greater accuracy than ever before. Predictive analytics can also anticipate future health problems based on current data, which could help in preventing diseases before they manifest.

AI is also speeding up drug discovery by allowing researchers to simulate millions of potential treatments in a fraction of the time. In remote healthcare, AI could diagnose patients without them needing to visit a doctor in person. Google’s AMIE project showed that AI-assisted diagnoses can sometimes outperform human doctors, which is both fascinating and a bit scary.

Autonomous vehicles, robots, smart cities—AI is driving progress in all these areas. Can you tell us more about that?

It’s amazing, isn’t it? AI in autonomous vehicles has advanced object detection and decision-making processes, though accidents still happen, just like with human drivers. As AI technology improves, these accidents will decrease.

In robotics, we’re seeing humanoid robots that can walk and carry items, and in healthcare, robots may soon assist with tasks like taking blood samples. In smart cities, AI optimises traffic management, reducing congestion and improving energy efficiency. Public safety is another area where AI is used, with emergency services being automatically dispatched when accidents are detected.

AI is becoming a part of our everyday lives. What does this mean for the average consumer?

For consumers, AI is making life more personalised and convenient. We already see it in personalised product recommendations from companies like Amazon or in smart assistants like Siri and Alexa. AI is also behind smart products like thermostats that learn your habits, adjusting your home’s temperature based on your daily routine. 

It’s about making life easier, more comfortable and tailored to individual needs. However, there are still challenges, and things don’t always work perfectly yet, but we’re moving in the right direction.

As AI evolves, it raises ethical concerns, especially around privacy, bias and transparency. How do we address these issues?

Privacy is a big issue, particularly with data collection. Many companies make money by collecting and selling data. The phrase “If it’s free, you’re the product!” is quite relevant here. We need to be mindful of facial recognition technology, data security and potential identity theft.

Bias is another challenge. AI is only as good as the data it’s trained on, and if the data is biased, the AI’s decisions will be too. Transparency is key—companies should explain how their AI systems work and ensure fairness in their algorithms. And of course, regulation will play a critical role in making sure AI is used responsibly.

Deep fakes are becoming a major concern, especially after incidents like Donald Trump sharing the Taylor Swift deep fake. How can we combat that?

It’s a big challenge. We need to ensure that AI companies use diverse and representative data sets, implement bias detection tools and are transparent about how their systems produce results. The issue is that even the creators of AI don’t always fully understand how their systems work because they’re so complex. This is why we need interdisciplinary teams—ethicists, sociologists, legal experts—to balance out the impact of AI.

AI is becoming more integrated into critical infrastructure. How can we ensure that AI systems are secure and protected from misuse or hacking?

Security is crucial. We need robust cybersecurity measures like encryption, access controls and regular updates to ensure that AI systems aren’t hacked or misused. Companies need to employ security by design, meaning that security is considered at every stage of the AI’s development. Regulations will likely play a role here as well, ensuring that AI systems meet high-security standards.

People are worried about AI replacing jobs. How do you see AI affecting the workforce, and what can we do to prepare for these changes?

This is one of the most critical topics. AI will undoubtedly transform many jobs, particularly those involving routine tasks. We’ll likely see augmented jobs, where workers are assisted by AI to be more efficient, and we’ll need upskilling programs to help people adapt to these changes.

There will also be new job opportunities in managing AI systems, but this won’t make up for the jobs lost. It’s important that we focus on education and retraining to prepare workers for the future.

What do you think will be the next big breakthrough in AI?

That’s hard to predict! AI is already making strides in healthcare, and I think we’ll see even more advancements there. The education system will need to adapt as AI becomes more integrated.

Other exciting developments include brain-computer interfaces, like Elon Musk’s Neuralink, which could enhance human capabilities. Quantum computing is also on the horizon, which could revolutionise everything from cryptography to energy consumption. The possibilities are endless.

AI consumes a lot of energy. Where is all this power coming from, and how can AI address climate change?

AI does use a tremendous amount of energy. Some AI data centres are so large that they require the equivalent power of a nuclear plant to run. We’ll need to rely more on renewable energy sources like solar and wind to meet these demands.

That said, AI can also help optimise energy use through smart grids, sustainable agriculture and energy-efficient building management. It’s a double-edged sword, but with the right approach, AI can play a role in addressing climate change.

Finally, what advice would you give to policymakers and industry leaders about advancing AI responsibly?

First, it’s essential that AI systems are thoroughly checked to ensure they don’t produce harmful or manipulative outcomes. We also need to focus on mitigating job displacement by providing education and reskilling opportunities.

Policymakers must understand that AI isn’t just about replacing humans—it’s about determining how many humans will still be needed in various roles. And we need strict regulations, especially when it comes to military applications of AI, because while AI can be used for good, it also has the potential to be used for harm.

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