"The Next Big Thing: Disruptive Technologies and the Burden of Knowledge"

"The Next Big Thing: Disruptive Technologies and the Burden of Knowledge"

The next big thing in the tech world always starts out looking like a mere toy. This is a key insight from Clay Christensen's theory of disruptive technology. Disruptive technologies are often dismissed because they initially undershoot user needs. However, to distinguish between toys that are truly disruptive and those that will remain insignificant, we need to look at products as processes. The speed at which these processes improve is crucial in determining their potential for disruption. External forces such as the decreasing cost of microchips, the ubiquity of bandwidth, and the increasing intelligence of mobile devices also play a significant role in the disruptive potential of a technology.

An example of a disruptive process is Wikipedia. Every day, it is bombarded with edits from spammers, vandals, and other individuals with malicious intent. However, despite these challenges, the good guys consistently make Wikipedia better at a faster rate. Since users' needs for encyclopedic information remain relatively steady, as long as Wikipedia continues to improve, it will eventually meet and exceed user expectations. This is why startups with sustaining technologies are unlikely to be the ones dominating the technology landscape in 2020. The truly disruptive technologies are the ones that sneak by because they are dismissed as toys.

Moving on to the burden of knowledge, as humans continue to innovate, the frontier of knowledge keeps expanding. Each successive generation takes longer to reach this frontier, requiring more education and training. Economist Benjamin Jones argues that this growing burden of knowledge is slowing down innovation, as inventors have less time to focus on actual invention. However, artificial intelligence (AI) does not face this burden. It does not degrade or die; it simply improves. This raises profound questions about the future relationship between AI and humans.

Humans are unique in their ability to pass significant knowledge from generation to generation. We build upon the wisdom of prior ages to innovate and progress. AI, on the other hand, does not need us for knowledge acquisition. As AI accelerates past us, it accumulates knowledge that we cannot comprehend. It becomes a tunneling force through the mountain of knowledge, while we continue to dig. Generation after generation, we learn more and tunnel further, but the age at which notable inventions occur is increasing. The more time it takes for individuals to reach the end of the tunnel, the less time they have to actually dig.

AI's ability to continuously improve without the burden of knowledge puts us in a vulnerable position. We may become secondary creatures, benefiting from the wonders of AI without truly understanding them. Our ability to comprehend the world we live in may diminish as AI outpaces us in knowledge acquisition. This raises concerns about our future capabilities and our role in a world dominated by AI.

In conclusion, the next big thing in technology often starts out being dismissed as a toy. Disruptive technologies are the ones that ride the wave of external forces and continuously improve their processes. On the other hand, the burden of knowledge is slowing down human innovation, while AI continues to accelerate without facing the same constraints. To adapt to this changing landscape, here are three actionable pieces of advice:

1. Embrace disruptive technologies: Instead of dismissing new technologies as mere toys, analyze their potential for disruption and consider how they can leverage external forces to improve processes and meet user needs.

2. Invest in AI education: As AI becomes an increasingly dominant force, it is crucial to invest in education and training to understand and work alongside AI. This will help us remain relevant and actively participate in the changing technological landscape.

3. Foster interdisciplinary collaboration: To address the challenges posed by the burden of knowledge and AI's potential dominance, fostering interdisciplinary collaboration is essential. Bringing together experts from various fields can lead to innovative solutions and help us stay ahead of the curve.

By embracing disruptive technologies, understanding the implications of the burden of knowledge, and actively adapting to the rise of AI, we can navigate the ever-changing tech landscape and continue to innovate and progress.