The Ethics of Tomorrow: AI expert on the Metaverse and a tech-driven future

A former judge and barrister, Kay is a renowned AI speaker and was the world’s first Chief AI Ethics Officer, advising organisations such as the World Economic Forum, governments, and Fortune 500 companies on the responsible adoption of AI and emerging technologies.

In this exclusive interview with Champions Speakers, she explores the evolving role of the Metaverse, the transformative potential of generative AI, and the ethical responsibilities facing business leaders in a data-driven world.

Q: The initial hype around the Metaverse positioned it as the next major shift in digital engagement. From your perspective, how is its role in business evolving—and where do you see real-world value emerging in the years ahead?

Kay Firth-Butterfield: “It’s interesting because we’ve been through a bit of an exciting Metaverse concept, where everybody was very enthusiastic and wanted to get on board. But now we’re more in a Metaverse winter—or perhaps autumn—because it’s actually very difficult to create content for the Metaverse.

“Where we’re seeing great applications for business is in industrial uses. However, where we’re struggling is in achieving the vision of us all entering the Metaverse in a Ready Player One scenario, where we can shop, buy houses, inhabit the Metaverse, and enjoy full 3D interaction. That’s because it requires a lot of computer power and dedicated resources to create the background infrastructure needed to be truly immersive.

“So, I think if you asked me what will happen in five years, I’d say we’ll begin to see the Metaverse deliver the rewards we expect for business. Customers will have exceptional shopping experiences where, instead of just browsing online, they can enter a virtual store, ‘feel’ fabrics—although not physically—and make decisions in real time.

“We may also see remote working in the Metaverse, where you’re actually with colleagues. A recent study found that remote work makes it harder for young people to receive proper supervision. But you could imagine being able to truly supervise junior staff in the Metaverse. Young people also miss out on social interaction with colleagues when working remotely, so the Metaverse could help with that too. It frees us from physical limits and offers new virtual environments.

“But we need balance—many people likely don’t want to spend all their time in an immersive environment.”

Q: Looking ahead to the next decade, what emerging technologies or global tech trends do you believe will most significantly reshape society, industry, and the human experience?

Kay Firth-Butterfield: “That’s a great question—like getting out my crystal ball and giving it a rub. But undoubtedly, generative AI is a huge change we are seeing now. As it improves and becomes more refined, it will enable more AI applications, just by us asking it questions.

“Natural language processing is the AI term for conversations—it’s the computer understanding the language you type. Soon, only elite coders will need to code. The rest of us will just type or speak our questions, and the system will supply answers—or even code something on request. It’s very powerful, transformative technology.

“But it has downsides. First, it sometimes lies to us. Data will increasingly be dominated by machines and, with generative AI, every question generates new data 24/7. We’ll see less human-generated data and more computer-generated data. We need to ensure it doesn’t relay lies it created in past responses.

“So, in ten years, data creation and AI will look very different, and this raises questions about the human role. If AI excels at many tasks without needing rest, what is our place? There are cost savings, but also societal impacts related to potential mass unemployment.

“AI powers the Metaverse, so progress there depends on further AI developments. I also think synthetic biology will surge with the help of AI. There may be an interplay between quantum computing and AI, which will bring both advantages and disadvantages.

“We’ll also see more Internet of Things devices—but that presents challenges around security and data privacy.

“There’s huge potential, but also serious problems embedded within those benefits. Some people think general AI could become sentient, but I don’t see that as likely—at least not yet. It lacks causal reasoning. It’s still just a predictive model. We’d need to add something significant to reach human-level intelligence—but it’s certainly an exciting time we’re entering.”

Q: You’ve been at the forefront of AI governance and ethics for many years. In today’s data-driven economy, what do you see as the most pressing ethical risks related to AI and big data—and how should organisations respond?

Kay Firth-Butterfield: “This is where I’ve spent much of my career. I started my life in the AI world—after my legal career—thinking about the risks of AI to humanity, businesses, and governments. That’s how I became the world’s first Chief AI Ethics Officer. I had to come up with a title, and I think that today I might have gone with ‘Trustworthy Technology Officer’ or ‘Responsible AI Officer’.

“But back then, we weren’t really talking about ethics. So why are we discussing it so much now? Well, because people’s ethics differ, and those differences are often geographical.

“There is global agreement that we should be concerned about safety and robustness, but we also need to worry about bias in the system. Bias can occur when you input biased historical data into the machine. That data shapes the machine’s decisions.

“Another source of bias is the people writing the code. Many coders are young men under the age of 30, and only 22% of coders are women. Obviously, those are pre-generative AI figures, but it's unlikely to have changed significantly. More men use generative AI simply because of the types of jobs we do.

“So, these coders bring in their own values—and the values of young men may not reflect mine, or yours.”

Q: Generative AI is dominating headlines and transforming how people interact with information. For those new to the concept, how would you describe how it works—and what makes it such a pivotal development in the AI landscape?

Kay Firth-Butterfield: “It’s very exciting because it represents the next iteration of artificial intelligence. What generative AI allows you to do is ask questions of the world’s data—simply by typing them in.

“If we think back to science fiction, this is what we’ve always wanted: to ask a computer a question and have it respond, drawing on the full spectrum of global knowledge.

“How does it work? Well, it predicts what word is likely to come next. It does this by accessing enormous amounts of data—we call these large language models. Essentially, the machine reads—or at least accesses—all the data available on the open web.

“In some cases—and this is a highly contentious legal issue—it may also access IP-protected or copyrighted material. We’re likely to see a lot of court cases about this.

“When the system has ingested all that data, it predicts what word naturally follows the next. It can construct really complex responses just through this process.

“Anyone who has used it will know that it can return very eloquent and compelling responses—just through word prediction.

“But sometimes it gets things wrong. In the AI community, we call that ‘hallucinating’. It’s essentially lying. That’s a problem, because we need to be able to trust the machine’s output. When it repeats its own fabricated content, it reinforces those falsehoods.”

Q: Democratising access to technology is often cited as one of generative AI’s greatest strengths. In practical terms, what are the real benefits of this shift—and where should we be cautious as its influence expands globally?

Kay Firth-Butterfield: “All of us can use AI now—it’s a hugely democratising tool. It means small and medium-sized enterprises, which previously could not access AI, now can.

“But we must also recognise that most of the world’s data is created in the United States, followed by Europe and China.

“There are several data challenges related to the training of these large language models. They aren’t actually using the world’s data—they’re using a limited subset. We’re now beginning to talk about digital colonisation.

“We’re projecting content derived from data created in the US and Europe onto the rest of the world—and expecting those regions to adopt it.

“Of course, different cultures need different answers.

“So yes, there are many, many positive aspects to generative AI, but also some very serious global challenges ahead of us.”

This exclusive interview with Kay Firth-Butterfield was conducted by Mark Matthews.

For more information, visit: Champions AI Speakers