Kay Firth-Butterfield is a globally recognized leader in ethical artificial intelligence and a distinguished AI Ethics Speaker. As the former head of AI and machine learning at the World Economic Forum (WEF) and one of the leading voices in AI governance, she has dedicated her career to supporting technology that enhances society rather than harms it.
We discussed with Kay the promise and pitfalls of productive AI, the future of the Metaverse, and how organizations can prepare for a decade of unprecedented digital transformation.
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The Promise of Productive AI:
Productive AI has garnered global attention, but there is still much misunderstanding about what it actually entails. Could you guide us on what Productive AI is, how it works, and how it can pave the way for what is considered such a transformative evolution of artificial intelligence?
Productive AI is very exciting because it represents the next iteration of artificial intelligence. What enables Productive AI is the ability to ask questions of the world’s data simply by writing a prompt. If we think back to science fiction, this is exactly what we’ve always envisioned – being able to just ask a computer a question and have it draw on all its knowledge to provide an answer.
How does it do this? Well, it predicts which word will come next in a sequence. It does this by accessing enormous amounts of data. We call these large language models. Essentially, it ‘reads’ – or at least accesses – all the data on the open web. In some cases, and this is a legal grey area, it also accesses IP-protected and copyrighted material. There could be a lot of legal discussions in this area.
Once the model has ingested all this data, it begins predicting which word naturally follows another and allows it to generate incredibly complex and nuanced responses. Anyone who has tried this knows that it can turn out remarkably effective and insightful content through this predictive ability.
Of course, sometimes it gets things wrong. In the AI community, we call this ‘hallucination’ – essentially the system generating information. This is a serious issue because we need to reach a point where we can trust the answers that we rely on from the outputs created by AI. The problem is that when a hallucination enters the data pool, it can be repeated and reinforced by the model.
Social and Business Benefits of Productive AI:
While much is said about the technical potential of Productive AI, what do you see as its most meaningful societal and business benefits offered? And what challenges should we address to ensure the equitable realization of these advantages?
AI is now accessible to everyone, and it is incredibly powerful. This is an extremely democratizing tool. This means that small and medium-sized businesses that previously could not benefit from AI can now do so.
However, we need to be aware that most of the world’s data is created, first, in the United States, then Europe and followed by China. There are clear challenges with the datasets on which these large language models are trained. They are not really ‘global’ datasets. They work with a limited subset. This has sparked discussions around digital colonization, where content generated from American and European data is reflected to the rest of the world with an implicit expectation that others will embrace and use it.
Different cultures require different responses, of course. So, while there are numerous benefits to Productive AI, there are also significant challenges that need to be addressed if we want to ensure fair and inclusive outcomes.
The Role of Metaverse:
The Metaverse has seen both hype and skepticism in recent years. From your perspective, what is the current trajectory of the Metaverse, and how do you see its role evolving in workplaces in the next five years?
We have moved beyond the excitement phase around the Metaverse that everyone wanted to be a part of. However, as it became evident how challenging it is to create compelling content for these immersive spaces, we may have entered more of a Metaverse winter or perhaps autumn.
We see strong use cases in industrial applications, but we are still far from reaching the Ready Player One vision where we live, shop, buy property, and interact entirely in 3D virtual environments. This is largely due to the immense level of computational power and creative resources required to create truly immersive experiences.
Within the next five years, I believe we will start to see the Metaverse deliver more than just promises for businesses. Customers can enjoy extraordinary shopping experiences – they can enter virtual stores instead of just browsing online, ‘feel’ fabrics almost in these virtual stores, and make informed decisions in real-time.
We may also see the development of remote collaboration where employees collaborate as if they were in the same room in the Metaverse. A study found that young workers often lack sufficient oversight when working remotely. In a Metaverse environment, you can provide real, interactive oversight and mentorship. Furthermore, it can help foster colleague relationships that are often missed in remote working settings.
Ultimately, the Metaverse eliminates physical constraints and offers new ways of working and interacting – but we need balance. Not everyone may want to spend all their time in fully immersive environments.
Global Impact of Emerging Technologies:
When you look ahead to the next decade, which emerging technologies and AI-driven trends do you believe will have the deepest global impact? And how should we prepare for their economic and ethical implications?
This is a great question. It’s a bit like gazing into a crystal ball. However, undoubtedly, productive artificial intelligence is one of the most significant changes we see today. As technology becomes more refined, it will increasingly empower new AI applications through natural language interactions.
Natural Language Processing (NLP) is a term in AI for the machine’s ability to understand and interpret human language. In the near future, only select developers will need to code manually. The rest of us will interact with machines through writing or speech requests. These systems will not only respond but also write code on our behalf. It’s an incredibly powerful, transformative technology.
However, there are downsides. One major concern is that AI sometimes generates information. And as productive AI becomes more productive, it generates large amounts of data 24/7. Over time, the data generated by machines may outweigh human data that could distort the digital landscape. We must ensure that AI does not perpetuate past mistakes.
Looking further ahead, this transformation raises profound questions about the future of human work. If AI systems can outperform humans in many tasks without fatigue, what will our role be? It may lead to cost savings but also poses a risk of widespread unemployment.
AI also empowers the Metaverse, so progress is contingent upon advancements in AI capabilities. I am also very excited about synthetic biology, where we can see advancements that can be transformative. There is likely to be a significant interaction between quantum computing and AI that can bring both benefits and serious challenges.
We will also see more Internet of Things (IoT) devices – but they bring new issues regarding security and data protection.
It’s an extraordinary time of opportunity, but also serious risks. Some are concerned about artificial general intelligence becoming sentient, but I don’t see that yet. Existing models lack causal reasoning. They are still predictive tools. To reach human-level intelligence, we fundamentally need to add something different. But make no mistake – we are entering an incredibly exciting era.
Digital Transformation and AI Adoption:
The adoption of new technologies can be both an opportunity and a risk for businesses. In your view, how can organizations strike the right balance between embracing digital transformation and AI adoption to make strategic, informed decisions?
I believe adopting the latest technologies is crucial, just as it is important for Kodak to recognize the shift in the photograph industry. Businesses that fail to recognize the risk of digital transformation are being left behind.
However, a word of caution: It is easy to jump too quickly and end up with the wrong AI solution for your business – or entirely wrong systems. Therefore, I recommend approaching digital transformation thoughtfully. Stay vigilant and treat each step as an intentional, strategic business decision.
When you decide you are ready to adopt AI, it is crucial to consider your suppliers. Ask the tough questions. Ask detailed questions. Make sure you have someone within a company or a consultant who knows enough to question the technology properly.
As we all know, one of the biggest wastes of money in digital transformation occurs when the right questions are not asked upfront. Making a mistake can be incredibly costly, so take the time to get it right.
Image by Petr Sidorov via Unsplash.
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