In this episode, I speak with Byron Reese, an acclaimed author, futurist, and entrepreneur, who shares his insights on the concept of ‘Agora’, a superorganism formed by the collective interactions of human beings. Drawing parallels complex adaptive systems like beehives, Reese argues that just as individual bees come together to create an entirely new organism with emergent properties, humans too form a higher-order entity through their differentiated roles and interactions. 

Reese delves into the idea of life spreading through the universe via panspermia and the role of natural selection in the evolution of intelligent life on planets. He posits that the purpose of Agora is to protect life on Earth from existential threats, such as asteroids, and that the optimal number of intelligent species on a planet is one, as too many would lead to self-destruction, while too few might fail to protect the planet.

In our discussion, we also touch upon the potential co-evolution of humans and artificial intelligence, the consolidation of human knowledge through language models, and the importance of individual actions in contributing to the well-being of the superorganism. 

5 Key Takeaways

1. Agora, a superorganism formed by human interactions, emerges from the differentiated roles and specialized interactions of individuals, much like a beehive.

2. Life may have spread throughout the universe via panspermia, and natural selection favors planets with a single intelligent species capable of protecting it from existential threats.

3. The purpose of Agora could be to safeguard life on Earth from catastrophic events, such as asteroid impacts, highlighting the importance of collective action.

4. The co-evolution of humans and artificial intelligence, along with the consolidation of human knowledge through language models, may significantly shape the future of society and decision-making.

5. Individual actions, such as kindness and personal growth, play a crucial role in contributing to the well-being and progress of the superorganism, potentially leading to a utopian future.

What are the new challenges that generative AI is creating for copyright law? In this episode, I speak with Matt Hervey, the head of AI law at Gowling, to explore the legal intricacies surrounding the creation of content and ideas by large language models. In our discussion, Matt sheds light on the complex landscape of AI ownership, highlighting the differences in legal frameworks across various jurisdictions, such as the UK, EU, and US. 

In Matt’s view, a key issue for leaders to consider in determining the ownership and protectability of AI-generated works, is the degree of human involvement and the level of effort contributed. We also touch upon the controversial issue of training data and the potential liabilities arising from the use of scraped content from the internet.

In this episode, we further explore the transformative potential of AI in industries like life sciences, where AI-powered drug discovery and clinical trials are already making significant strides. Matt discusses the importance of documenting the AI development process to mitigate risks and the need for organizations to develop proprietary models to safeguard their intellectual property.

The 5 Key Takeaways:

1. Understand the legal implications of AI ownership and the varying levels of protection across different jurisdictions to inform strategic decisions and mitigate risks.

2. Assess the potential liabilities associated with training data and implement measures to ensure the ethical and responsible use of AI within the organization.

3. Recognize the transformative potential of AI in industry-specific applications and invest in proprietary models to leverage unique data assets and gain a competitive edge.

4. Foster collaboration between legal, technical, and domain experts to develop a comprehensive understanding of AI's impact and potential within the organization.

5. Prepare for the future of AI-powered organizations by building interdisciplinary teams and upskilling employees to effectively navigate the complexities of AI implementation and governance.

Mikko Hyppönen is a renowned Finnish cybersecurity expert and the Chief Research Officer at WithSecure. In our discussion, we delved into the rapidly evolving landscape of cybersecurity threats, particularly focusing on the impact of artificial intelligence and large language models. 

Mikko and I covered a wide range of topics, from the scalability of AI-powered scams and phishing attacks to the emergence of "cybercrime unicorns" - highly organized and well-funded criminal organizations. Hyppönen emphasized the importance of visibility, anomaly detection, and the use of AI in defending against these threats. He also touched upon the need for regulation and the establishment of principles to guide the development and use of AI systems.

The 5 Key Takeaways:

1. AI-powered scams and phishing attacks are becoming more sophisticated, personalized, and scalable, posing significant challenges for organizations and individuals.

2. The rise of "cybercrime unicorns" - well-organized and funded criminal organizations - is a growing concern in the cybersecurity landscape.

3. Visibility, anomaly detection, and the use of AI in defensive strategies are crucial for organizations to protect themselves against evolving threats.

4.  Regulation and the establishment of guiding principles are necessary to ensure the responsible development and use of AI systems in cybersecurity.

5. Organizations must have well-defined plans and the ability to adapt quickly when faced with cybersecurity incidents, such as ransomware attacks.

Most are familiar with the story of how Moderna was able to rapidly develop and deploy a successful COVID19 vaccine during the pandemic. Not long after Chinese scientists first put the genetic sequence of the novel coronavirus online, Moderna went from sequencing to shipping in a matter of months. To put that in perspective, a vaccine typically takes ten years to bring to market. What is less known is that Moderna never intended to be a company focused on making coronavirus vaccines - it was simply an opportunity that emerged out of having the right capabilities and infrastructure in place.

When Moderna was founded in 2010, it set the vision of being a digital biotech platform capable of broadly exploring the potential of mRNA technology. When news of the pandemic first emerged, Moderna was working on a number of mRNA-based medicines, including those focused on heart disease, Zika, and cancer. However, Moderna's founders believed that if mRNA technology worked for one application, it could work for countless more, and all that would be needed was to change the information and code it for a new application. 

When I spoke with Dave Johnson, Chief Data and AI Officer at the company, he explained that mRNA is an information-based platform. Similar to a computer's operating system, researchers can insert new genetic code from a virus to create a novel vaccine quickly and safely. In fact, it was the software-like, digital nature of mRNA technology that inspired Moderna to fashion themselves in the form of a new type of digital biotech company with AI, algorithms, and automation at its core.

Dave Johnson is Chief Data and Artificial Intelligence Officer at Moderna, where he is responsible for all enterprise data capabilities from data engineering, data integration, data science, and software engineering. Johnson holds a PhD in Information Physics and has over 15 years of experience in software engineering and data science. He has spent more than a decade working exclusively in enterprise pharma and biotech companies.

In this episode you will learn: 

02:13 How Moderna brought a COVID19 vaccine to market so quickly
04:10 The value of investing in capabilities rather than competencies
06:20 How Moderna is different from a more traditional pharma company
10:02 The future of personalized cancer vaccines
11:27 Why there is so much misplaced optimism about AI in biotech
13:33 The Moderna digital platform
18:34 Why data scientists are not data analysts

What if within the span of the next decade, we could live for an additional ten years or more? A hundred years ago, advances in infection control and public health led to a near doubling of the human life span. For us to achieve a similar feat today, we will need more than just scientific breakthroughs. Despite the rise of AI, powerful computation platforms and new discoveries in genomics, there is still a gap between everyday medical practice and technological innovation.

Jo Bhakdi is the founder and CEO of Quantgene, a biotechnology and data company. In his view, when it comes to medical diagnoses, we are largely reliant on snapshot testing, quick discussions regarding patient symptoms, and the brain power of the practicing physicians.

AI-powered genomics, by contrast, allows us to now turn biology into a data problem, moving at the speed of statistical model development and falling computation costs. Genetic testing has the potential to uncover the root cause of disease and reveal its progression in the body - thus redefining the healthcare paradigm.

One area where this technology has the potential to impact our life expectancy is early stage cancer detection. Many cancers are treatable if caught early enough. While traditional medicine tends to intervene only when a tumor is advanced enough to warrant investigation, Quantgene has developed he capability to detect multiple types of cancer from a simple blood test. By identifying cellular mutations using artificial intelligence analytics and big data, they can unlock where a cancer is encoding itself into the human genome.

In this episode you will learn:

01:28​ The unexpected implications of extreme longevity

04:31​ Jo's origin story

06:19​ Reimagining cancer detection

15:38​ Healthcare is a system of broken incentives

30:20​ Digital transformation & Big Pharma

35:29​ Delivering innovation at scale

43:35​ Privacy, rights and personal data