Coping with phenomena that evolve rapidly and on a large scale – like pandemics, climate change, artificial intelligence, etc. – poses a significant challenge for humanity. Here are some general trends and issues:

1. Information Gap: In any rapidly evolving scenario, one of the primary struggles is the information gap. The lag time between collecting data, analyzing it, making decisions based on it, and then implementing those decisions can be significant. By the time a decision is implemented, the situation may have changed, making the decision less effective or even counterproductive. This is what happened during the COVID-19 pandemic, where the virus was mutating faster than we could study and respond.
2. Political Limitations: Sociopolitical pressures often limit the speed and extent of response to such phenomena. Political leaders have to weigh the benefits of immediate action against the potential social, economic, and political fallout. Public opinion and political considerations can often slow the necessary response, as we’ve seen with both the COVID-19 pandemic and climate change.
3. Infrastructure and Resource Constraints: The ability to respond rapidly and effectively is often constrained by available resources and infrastructure. For example, in many countries, the healthcare system was unable to cope with the surge in COVID-19 patients. Similarly, shifting to renewable energy sources requires a significant investment in infrastructure, which can be a major hurdle.
4. Cultural and Behavioural Resistance: Human behaviour and cultural norms can slow down the response to rapidly evolving situations. For instance, people’s reluctance to follow public health measures such as mask wearing or social distancing during the pandemic, or resistance to reducing consumption as part of climate change mitigation efforts.
5. Global Coordination and Cooperation: Challenges like pandemics or climate change are global, and hence require international cooperation. But geopolitical tensions, economic disparities, and differing national interests can hamper this cooperation.

Despite these challenges, humanity has also demonstrated remarkable resilience and innovation. Rapid development of vaccines for COVID-19 is a great example. The use of AI and data analysis in epidemiology, climate science, and many other fields is also speeding up our ability to understand and respond to these challenges. The global cooperation in sharing research, though imperfect, has been critical.

It is vital for us to learn from these experiences and strive for improved cooperation, investment in science and infrastructure, and public education to better prepare for and cope with such rapidly evolving phenomena in the future.

COVID-19 and AI, although drastically different in nature, do share some similarities when it comes to the challenges humanity faces in understanding and managing them. Here are a few:

1. Rapid Evolution: Both AI and COVID-19 have shown a capacity for rapid evolution. COVID-19 mutates frequently, creating new strains with different characteristics. Similarly, AI is evolving quickly as algorithms improve and computational power increases. The speed of this evolution can outpace our ability to fully understand and respond to these phenomena.
2. Unpredictable Outcomes: With both COVID-19 and AI, there are large degrees of uncertainty and unpredictability. For COVID-19, it is difficult to predict how the virus will mutate and how virulent new strains will be. For AI, while we can control its initial programming, it is hard to predict how it will “learn” and evolve over time, especially with advanced systems using reinforcement learning or other unsupervised methods.
3. Global Impact: Both COVID-19 and AI have the potential to affect people around the world, regardless of borders. While COVID-19 can spread globally, the influence of AI is also pervasive, affecting global economies, labor markets, and societies at large.
4. Data Dependency: Effective response to both COVID-19 and AI requires extensive, high-quality data. For COVID-19, it is data about infection rates, hospitalisation rates, vaccine efficacy, etc. For AI, it is data to train and refine algorithms. In both cases, there are significant challenges in obtaining reliable, comprehensive, and unbiased data.
5. Regulation and Governance: Both COVID-19 and AI pose challenges in terms of regulation and governance. For COVID-19, it is about implementing effective public health measures, which must often balance individual liberties with collective wellbeing. For AI, it is about creating laws and ethical guidelines that ensure AI is used safely and responsibly, without impinging on privacy or other rights.
6. Existential Risk: Both COVID-19 and AI pose potential existential risks. While a pandemic could result in widespread death and societal disruption, uncontrolled or maliciously used AI could lead to unintended consequences on a global scale – from job displacement due to automation to more dystopian scenarios envisioned by thinkers like Nick Bostrom and Elon Musk.
7. Social Resistance and Misinformation: In both situations, there can be resistance to change and misinformation. For COVID-19, there was resistance to lockdowns and masks, and a spread of misinformation about the virus and vaccines. For AI, there can be resistance to changes it brings in the job market or society, and misconceptions about what AI can and cannot do.

In both cases, education, transparent communication, and proactive policy-making are crucial to mitigate risks and leverage potential benefits.

Jeez. Right. I continued.

CW: “But I’m wondering whether at the heart of this it is about us not being able to cope with complexity of human affairs? All the issues you mention except ‘rapid evolution’ are about how human beings function individually or collectively. So I am searching for more fundamental issues (some you have mentioned already).”