iStock/klyaksun In this issue, our community addressed advantageous, and disadvantageous, utilization of capacity in society. We assessed constraints that limit capacity. We addressed underutilization of capacity. We explored the potential for adjustments to throughput, with the hopes of improving capacity.
As populations increase, the volume of man and materials increases [1]. Demand can exceed capacity. This is evidenced when cars (with increased capacity) encroach on pedestrian spaces and thereby reduce people flow on sidewalks. Capacity becomes constrained. As our colleagues debated the usability [2] and sustainability [3] of driverless cars and/or railway systems, we contemplate such societal constraints to capacity as traffic congestion, and aging infrastructure. We identify underutilized capacity; automobiles designed to transport multiple people, are often utilized by only one. We pondered the impact of autonomous vehicles on human capacity, if wasted driving time is converted into hands-free work productivity. Authors also showed us how to advance capacity sustainably across cities through more strategic organization and management of mobility as-a-service (MaaS).
Our colleagues also explored nudging, dynamic consent, cyber arms, and predictive policing. We were exposed to flaws in the non-physical throughput of information processing. We wrestle with nudging; information flow is manipulated. With dynamic consent, we feel the benefit of removing unnecessary constraints through real-time consent, yet also the risks associated with circumventing necessary regulatory countermeasures. We recognize constraints caused by expanding gaps and ambiguity in the legal environment relative to cyber arms. We were also cautioned to better design throughput with an Ethics of Care approach to better understand computational techniques of predictive policing, so as to avoid underlying bias in the data relative to certain populations.
In the battle against cancer, authors presented comprehensive methodology to reduce such capacity constraints as time-consuming and resource-demanding computations for more effective personalized cancer treatments. Their incremental approach to capacity management when processing data is methodology likely to make the difference between life and death.
Everyday life requires movement up, down, and across capacity in our world [1]. Our community came together brilliantly, taking into account this movement in both the physical and non-physical spheres. Our community assessed well the utilization of technology, to help society better align capacity to demand.
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