Forecasting

Forecasts describe potential future evolutions of a specific topic. Our experience has shown that looking at a range of alternative futures usually proves more useful than a single-point prediction of a future state. Therefore a set of forecasts is developed that bounds the uncertainty associated with a given driver. Usually, our clients have identified with us those topics that contain the key forces driving the future of the system or issue under study. This set of alternatives is usually qualified by an assessment of likelihood and preferability. In this way, forecasts can also be understood as statements that reveal the potential of a change.

Here is a provocative forecast that we have recently developed for an international board:

 
Intelligent Global Networks by 2030

During the years leading to 2030, online networks of knowledgeable humans and intelligent systems evolved to form a vast and virtual neural network capable of acting almost like a global brain capable of generating new thoughts. Communication flows reached an ever growing percentage of the global population. Social media and content aggregators increasingly merged into platforms tailored to the needs of specific communities of interest. Intelligent man-machine interfaces fused biological and computational capacities as biosensors and nanosensors using cognitive computing became ubiquitous by the 2020s.

Advanced software became more effective at mining huge datasets flowing from social networks, government databases, and other online sources, and at providing answers that informed decisions and were tailored to users’ learning style and context. These systems increasingly offered a predictive capacity by combining multiple real-time data flows. However, the inability to anticipate major disruptions and non-linear changes prevented these systems from solving the most pressing challenges. Further, while these systems were able to answer many questions that humans had asked in the past, their utility was constrained by humans’ inability to ask the right questions for the future.

The fact that major portions of the infrastructure underlying the intelligent global networks were owned by governments or corporations created differentials of power and access that effectively cut large segments of the global population off from the benefits offered by the knowledge network. Some incumbent corporations sought to expand their control of the network by acquiring companies offering disruptive innovations and by setting new restrictions on Internet traffic, search algorithms, and communication tools. Concentration of data storage points in the hands of a few large organizations also heightened concerns about cybersecurity.

(Courtesy of IEEE)