There are many examples of weak signals that heralded emerging trends: the inception of the first social network, the launch of the first public bicycle service, the initial trade of lab-grown meat, and the first system to send e-mails; the list of such signals is virtually endless. Many times, when looking back, it seems easy to appreciate the significance of a particular event. We all recall the cumbersome mobile phones of the 1980s, which appeared more as a luxury than a necessity, yet they marked the beginning of a profound transformation. As mobile phones progressively became smaller, and with the introduction of the Blackberry, 20 years later, these signals grew stronger. The trend culminated with the debut of the first iPhone in 2007.
For future intelligence, a "weak signal" can be understood as an early indication of a possible significant or emerging change, which is neither evident nor widely recognized. It could be, among many others, a new technology, a social phenomenon, a scientific advancement, or a political event.
Sometimes weak signals speak loudly
Signals are diverse, lack a consistent pattern, and can sometimes emerge abruptly. Consider the surge of Generative Artificial Intelligence at the end of 2022. GPT-1 was a subtle hint, but GPT-4 is a stronger indicator, making it apparent that it's set to bring about substantial changes. However, predicting exactly what and how it will change things remains a challenge.
Furthermore, the rapid advancements in generative AI underscore the need for collective intelligence tools. Without them, it becomes virtually impossible to manage the exponentially increasing array of new options, tools, and facts that are emerging. The importance of fostering a knowledge-building team environment becomes even more evident when considering the vast array of emerging technologies.
Identifying and interpreting weak signals is knowledge-teamwork
Consider the vast array of signals as a puzzle with a million pieces. While this sounds like a very hard task for an individual alone, imagine a team of experts taking care of this.
The team possesses the capability to identify and analyze a broader range and scope of signals, given that individuals are receptive to varying types of information.
Engaging in team-based discussions and debates around ambiguous facts and data enhances comprehension and cultivates the ability to assess their potential impact.
Consensus among diverse experts diminishes cognitive biases and misinterpretations. Thus, a range of viewpoints influences the interpretation of signals.
A blend of perspectives helps balance our thinking, enhancing our ability to interpret signals.
The capacity to identify, understand, and react to weak signals is largely contingent on an organization's culture. It is only through a blend of curiosity, openness, formal collaboration, and a readiness to take risks that an organization can effectively detect and leverage these weak signals.
Understanding Weak Signals: Sources and further readings:
Hiltunen, E. (2008). The future sign and its three dimensions. Futures, 40(3), 247-260.
Radford, A., Wu, J., Amodei, D., Amodei, D., Clark, J., Brundage, M., & Sutskever, I. (2019). Better
language models and their implications. OpenAI blog, 1(2).
Josep Monguet Fierro
Professor at the UPC. Founder of SmartDelphi, Onsanity, and Innex Experience in digital healthcare innovation. Research coordinator of “Master Barcelona Design” UPC-UB.
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