Non-Knowing in Energy Forecasting

Laozi teaches that claiming complete knowledge creates rigidity: the sage admits what cannot be known. Applied to data center planning, this principle confronts the industry practice of building capacity predictions into permanent infrastructure. Future demand cannot be predicted with certainty—AI adoption, user behavior changes, economic shifts, and technological developments remain genuinely unknown. Rather than designing for supposedly-certain forecasts that inevitably prove wrong, this wisdom suggests building adaptive infrastructure capable of responding to unknown futures. This means preferring modular, scalable systems over monolithic designs, using software-defined approaches that adjust to actual demand, maintaining geographic flexibility to shift load as needs evolve. It requires humility about forecasting ability and acceptance that some over-building or under-building is inevitable. Instead of attempting to optimize for an unknowable future, design for adaptability. This reduces the pressure to guess correctly about decade-long infrastructure needs and instead emphasizes responsive, evolving systems. By acknowledging what cannot be known and designing accordingly, data centers become more resilient to surprises while avoiding the energy waste of designing for scenarios that never materialize.