In one of my posts from a recent series titled A Journey through the Looking Glass, I focused on the complexity, uncertainty, and volatility of our current environment. Although this dynamic makes it difficult to envision possible futures, the “Future of” question is a growing focus among leaders around the world. While many themes have emerged, mobility is a common topic of discussion. Current conversations are dominated by electric vehicles, batteries, and charging infrastructure. However, the future of mobility is much bigger than our current focus.
In the looking glass series, I referenced complexity science and our need to understand the building blocks that shape the future. If you are focused on the future of mobility, what are the building blocks that you envision shaping that future? As described in the series, a convergence model helps us explore those questions. A broad macro-level model identifies a comprehensive number of building blocks across critical domains that have historically shaped a given future. You can then attempt to identify those building blocks that are likely to influence the path of a domain, in this case, mobility. You choose the building blocks that we believe create possible mobility futures. Since convergence across these building blocks is a key determinant of outcomes, you must then understand how these building blocks may converge. A story begins to emerge that allows us to describe possible futures. Storytelling then takes over, utilizing visualization and crisp messaging. Give it a try, this visual depicts the approach.
Let’s use an example from a recent article that describes the convergence across technology and societal domains. The article focuses on the role that mobility likely plays in reducing fatalities associated with drunk driving. A building block utilized to accomplish this is affective computing – a building block on the technology side of the convergence model. It is defined by the Future Today Institute (FTI) as follows: affective computing is an interdisciplinary field spanning computer science, psychology, neurobiology, and cognitive science, and it intersects directly with AI. A scenario is described in the FTI 2022 trends report that provides an example of affective computing in mobility:
Affective computing focused on automotive applications will help cars manage their drivers rather than the other way around. By recognizing emotional and cognitive states from deep learning, computer vision, and voice analytics, affective computing systems in vehicles will prevent drivers from doingFuture Today Institute – Tech Tends 2022
dangerous things. Basic driver-monitoring tools are already available that monitor eye movements and blink rates to determine if the driver is impaired, but affective computing promises to alert a driver when it detects fatigue or drowsiness, even going so far as to suggest places for the driver to purchase
a strong cup of coffee. While vocal cues serve as potential inputs for affective computing systems, biological data from other sources—our skin, our faces, our DNA—can be useful, too
Our life experiences in the context of mobility will change considerably. Going back to the article on drunk driving, we can see how convergence works. Our cars will determine if we are fit to drive, initially by monitoring the performance of the car, but ultimately by monitoring you. Driving monitoring and assistance systems (DMAS) have focused on the driver specifically, using real-time video to track things such as head position, eyelid closure and eye gaze direction to detect driver impairment. The article states that in an emergency, these systems can work together to prevent a crash. The cameras can establish a driver’s impairment, for example, while the automated driving technology steers the vehicle to safety.
If you experience physical distress like a large rise in blood pressure or signs of a heart attack, the car becomes part of a preventative healthcare ecosystem. It will recognize your distress and autonomously take you to the hospital. These are signs of multiple ecosystems converging. If we shift to a focus on convergence across the domains identified by the model, we find an example in the article.
These technologies will at least reduce the likelihood of people’s interactions with the criminal justice system and subsequent legal repercussions, which can have lifelong consequences.Kyle J.D. Mulrooney, Guy C. Charlton – New drink-driving technology could soon be a fixture in all cars. Here’s why it’s a game changer
Incarceration rates in places like the U.S. are very high, with focus on punishment versus attention to social, cultural and health-based interventions. This is one example of a future of mobility that intersects with multiple domains. A broad focus across all domains is therefore required. As you strive to address the “Future Of” question, think building blocks, critical domains, and convergence.