At Oslo Business Forum, Mikko shared insights on AI's latest developments and possible future. He helped leaders understand how AI is reshaping leadership by empowering improved decision-making and innovation—and previewed the ethical considerations that come with integrating AI into their organizations.
The AI Revolution: Redefining Leadership
Decades of research have demonstrated that every time there's a major revolution, we overestimate its speed but underestimate its size. Mikko has spent his career thinking about AI, even before its recent surge. He first encountered the idea in a 1983 Finnish magazine that published an eight-page special feature on intelligent machines. Looking back, it's uncanny how accurate its predictions were.
As the CRO of a leading cyber security corporation, Mikko Hypponen monitors how cybercriminals work. Cyber security companies have been a step ahead thanks to automation and AI, while criminals have been building their attacks manually.
In most languages, the word "computer" comes from Latin and it means to calculate. In Norway, the word means "data machine." And in Finland, Mikko's home, the word means "knowledge machine."
"I have been working with computers all my life, and computers have known nothing," said Mikko. "They have been doing exactly what they have been programmed to do. That clearly is changing now."
Today, we have answers to everything right in our pockets. Our smartphones deliver all the information we demand, and at a speed that was unimaginable even 25 years ago. Mikko observed the revolution in three stages:
Stage 1: Feeding Data
Data used to be physical, in the form of paper. In the first revolution, information became data that could be fed to computers.
Stage 2: Storing Data
We then developed the capability to store data like a massive library of all humankind's knowledge. Today, this is known as the cloud, which gives us access to incredible amounts of information that we have fed to computers.
Stage 3: Computing Power
The smartphones we all use today are faster than the fastest supercomputers produced 20 years ago. Today, pioneering AI companies have hundreds of thousands of these CPUs in data centers.
"We are building something that is pretty exciting and also a little bit scary.
The end result of these revolutionary stages? "We are building something that is pretty exciting and also a little bit scary," said Mikko.
We've seen how good generative AI is. There are endless examples across the internet and in our everyday lives. "You can generate any content you can imagine," said Mikko. "This is a bit problematic."
The rise of generative AI poses significant ethical challenges. Leaders must grapple with these issues as they consider how to integrate AI into their organizations.
Challenge #1: Giving credit where credit is due
We used to think that intelligence and creativity only come from humans. That's changing. We can see it happening already happening in music, where tools like Udio can compose, arrange, and produce a song in under 30 seconds. There is even an entirely AI-generated song charting in the German Top 40 hits today.
One of the biggest questions this poses is, where should the royalties go? To the person who typed the prompt? To the company that built the system? To the AI itself or the songs used to teach the system? "We have very real, unsolved questions about the ethics of generative AI," said Mikko.
Challenge #2: Balancing human expertise with AI assistance
AI has also begun to blur the line between the knowledge we acquire and the knowledge we "borrow." Mikko presented the example of visiting a doctor for symptoms of a stomachache.
"I would prefer to go to a doctor who uses AI to assist him," he said. "We train doctors extensively, but clearly, they can't read everything." A doctor using AI to facilitate a diagnosis can access an expert system that has read every book and journal in every language, including the latest research published yesterday.
"I want a real expert, but I want the expert to use the latest and greatest technology," Mikko said. "This is how you should be thinking about your company." Ask yourself: what are we doing, and how can we make it better?
Challenge #3: Distinguishing fiction and reality
Another challenge that has emerged is the proliferation of AI deepfakes. In the 1990s, Photoshop changed the way we looked at photos. We felt we could no longer trust anything as an authentic, untouched image. Today, deepfakes—in the form of images and voices—have emerged in attacks on organizations and individuals.
Challenge #4: Running out of data
We're rapidly approaching the point where we have already fed AI all our available data. If we continue to feed AI that data that's online today, we will be feeding it data generated by earlier systems. You can recycle data, but Mikko said, "There is a limit to how far you can take it."
Challenge #5: Determining if systems should be open or closed
Mikko admits that he is an advocate for open-source research. But open source presents a major risk to safety and security. The guardrails will be torn down if you can simply download the source code and remove the restrictions. "There might be limits to open source, and the limits might be in generative AI," Mikko said.
Adapt or Fall Behind
Mikko left leaders at Oslo Business Forum with this critical consideration: "Nothing changes the world as much and as quickly as technology revolutions." He beckoned us all not to overestimate the speed or underestimate the size of the revolution we're facing. It may take longer than we anticipate, but it's sure to be bigger than we can predict.
Key Points
Questions to Consider
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