Markus SpiskeAs AI continues to transform our personal and professional lives, global advisor, speaker, filmmaker and AI Policy Fellow at the University of Bath Walter Pasquarelli, discusses the role of geopolitics in the AI sector and how businesses can stay ahead of the technological curve with FM Magazine.
How is AI transforming the future of business and society?
“Picture this: You’re back in the early ’90s. The Internet is still a novelty but a phenomenon that would fundamentally reshape how we connect as humans. Knowing what you know now, how would you have prepared yourself? Positioned, maybe even invested? We’re now at the cusp of a technological transformation that will forever restructure the course of the global economy.
“Generative AI, according to the President of Microsoft, is going to be the steam engine for knowledge work, adding up to 7 per cent to global GDP by 2030. Do you need a marketing plan for a new product? No problem. How about a generative AI assistant who can produce a first draft of a report? Or a tool that can help doctors make better medical diagnoses. Like the web democratized information in the early ’90s, generative AI will democratize productivity, innovation, and creativity. Now is your time to position yourself.”
What role does geopolitics play in implementing AI, big data, and other emerging technologies?
“Geopolitics creates a sense of urgency for companies to adopt generative AI to compete globally. It’s funny because in 2017 when I began analysing and researching the impact of AI, long before ChatGPT took the world by storm, the field looked rather different. Most of the discourse around AI focused on a few niche pockets within society.
“Business adoption had started, but the real hype and adoption were still set to come. Governments are now rushing to develop capabilities to support an AI-driven economy and the infrastructure for tomorrow. So, the straightforward implication for companies that previously considered AI a nice-to-have is now considered a matter of corporate survival.”
Understanding the high-level implications of generative AI is important. But the real work starts when we actually think about how we can bring it into our organisations.
What are your top tips for businesses wanting to stay ahead of the digital curve?
“Understanding the high-level implications of generative AI is important. But the real work starts when we actually think about how we can bring it into our organisations. For that, I typically recommend four steps to think about it. The first step is really about demystifying the technology. When we think about generative AI, often the first picture that comes to mind is some sci-fi concept, something about the far future.
“But in reality, we’re looking at statistical models with computing power. Understanding technology means understanding what it can and cannot do. From there, we can think about how it can benefit your business.
“The second thing is about aligning the AI strategy with the business strategy. Think about the use cases. You will need more than just throwing a neural network at your company to increase revenue. But we really have to think about the areas where generative AI can help our workers do their work better and, in turn, which areas are better left untouched.
“The third step is to understand your constraints or, in other words, my capabilities to bring the technology into my company. The majority of businesses here really have two areas of work that they need to focus on. The first one is about their data. Artificial intelligence fundamentally functions on data, and it ought to be able to build generative AI technologies. Data needs to be high quality and clean. The second point is talent, the people who effectively develop these tools within your company or rely on outside contractors.
“The final step, then, is to start small. But to start, and with that effectively, identify some smaller pilot cases where generative AI could be trialled before spreading it out across the organisation. That has two advantages. The first one is that you can fail fast and create learning experiences without investing too much capital. But the second thing is that once you’re successful, you can create momentum, scale it, and build approval within your company to expand the technology across your whole organisation.”
Privacy breaches are real. Customer data can get leaked or compromised, which can diminish people’s trust in your brands.
How can organisations starting to implement AI prioritise ethics and safety?
“Privacy breaches are real. Customer data can get leaked or compromised, which can diminish people’s trust in your brands. Misinformation and intellectual property breaches are also important and can create serious legal issues for downstream companies. The key thing for organisations is to embed ethical practices from the start. By that, I mean from the moment an idea about a particular AI tool is conceived.
“Think about the moral ramifications that this could have caused. An assessment of the data being used to monitor the use of AI from the beginning to the end user. And, of course, collect feedback from the people most affected by that, as that will provide you a firsthand understanding of how the technology is actually playing out in real life.
“The other thing to add is that our knowledge is limited, and soliciting external feedback from experts who have worked in this field for decades is also a good strategy. This is important because research shows that customers and businesses generally perceive responsible AI as a competitive advantage. So, this is not an issue that excludes innovation, but it’s the different side of the same coin.”
This interview with Walter Pasquarelli was conducted by Mark Matthews.
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