Read our Chairman Louis' account of his recent experience speaking to the All Party Parliamentary Group on Artificial Intelligence.
On Monday I gave evidence on Democratising Artificial Intelligence (AI) to the All Party Parliamentary Group on AI at the request of AI Chairs, Stephen Metcalfe MP and Lord Clement-Jones CBE, and the Secretariat at Big Innovation Centre.
Here is a summary of what I said:
Introduction: When I was told this would be a six-minute talk, I couldn't help but think about my lawyer, Chris, who bills in six-minute increments. Six minutes can be a long time, especially in the world of generative AI. So, I picked up the phone and called Chris.
Exploring Generative AI: You see, generative AI has the potential to do more with less time, accelerating productivity while reducing costs. But what makes six minutes seem so long in this context? It's the billions of calculations happening during that brief interaction.
AI in Our Lives: Now, imagine if AI were cognisant, perceiving the world at the speed of thought. Those same six minutes would hold immense value for a newborn baby, as well as for children starting their educational journey.
AI's Role in Education: In the lifetimes of these youngsters, AI and generative technology will play a significant role. Critical thinking will become the most crucial skill in an AI-driven world, where individuals must interpret, evaluate, and make judgments based on facts and information.
Access to AI in Education: Just as Article 2 of the Human Rights Act guarantees the right to education, I strongly believe that access to AI should also be universal, starting with our schools. Every child should have the freedom to interact with their AI, confident in the accuracy and privacy of their exchanges.
The Need for Personal and Private AI: AI should not only be correct but also personal and private. It should allow individuals to access sensitive information without compromising privacy.
The Solution: Small Language Models (SLMs): How do we achieve this? Enter SLMs. These models offer the benefits of their larger counterparts while being cost-effective, transparent, and customisable for each user.
Transparency and Control: SLMs are transparent, as we know precisely where their data comes from. For instance, traditional textbooks from teachers can be one of the sources. Each individual can have their own personalised SLM, giving them control over their AI experience.
Data Ownership and Participation: With SLMs, data ownership becomes a reality. You can choose to participate in initiatives like the NHS trial while also reaping the rewards from your data, rather than it benefiting only big pharma companies.
Blockchain and Digital Currencies: Blockchain technology and digital currencies, such as Ether, make this data ownership and profit-sharing possible by enabling transparent tracking of events and microtransactions.
A Visionary Approach: To make this accessible to all, we must adopt a visionary approach, much like when the NHS was created. I propose providing AI as a service to every UK citizen, funded by the government, just like the NHS – perhaps NAIS (National AI Service). Conclusion: In this vision, every individual in the country would have their own private, confident, safe, and participative AI. It's a future where technology empowers, educates, and respects individual rights, ushering in a new era of personal AI for all.
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