The global information infrastructure already consumes more electricity than is produced by all of the world’s solar and wind farms combined. Far from saving energy, our AI-enabled workplace future uses more energy than ever before.
An epic number of citizens are video-conferencing to work in these lockdown times. But as they trade in a gas-burning commute for digital connectivity, their personal energy use for each two hours of video is greater than the share of fuel they would have consumed on a four-mile train ride. Add to this, millions of students ‘driving’ to class on the internet instead of walking.
Meanwhile in other corners of the digital universe, scientists furiously deploy algorithms to accelerate research. Yet, the pattern-learning phasefor a single artificial intelligence application can consume more compute energy than 10,000 cars do in a day.
This grand ‘experiment’ in shifting societal energy use is visible, at least indirectly, in one high-level fact set. By the first week of April, U.S. gasoline use had collapsed by 30 percent, but overall electric demandwas down less than seven percent. That dynamic is in fact indicative of an underlying trend for the future. While transportation fuel use will eventually rebound, real economic growth is tied to our electrically fueled digital future.
The COVID-19 crisis highlights just how much more sophisticated and robust the 2020 internet is from what existed as recently as 2008 when the economy last collapsed, an internet ‘century’ ago. If a national lockdown had occurred back then, most of the tens of millions who now telecommute would have joined the nearly 20 million who got laid off. Nor would it have been nearly as practical for universities and schools to have tens of millions of students learning from home.
Analysts have widely documented massive increases in internet traffic from all manner of stay-at-home activities. Digital traffic measures have spiked for everything from online groceries to video games and movie streaming. So far, the system has ably handled it all, and the cloud has been continuously available, minus the occasional hiccup.
There’s more to the cloud’s role during the COVID-19 crisis than one-click teleconferencing and video chatting. Telemedicine has finally been unleashed. And we’ve seen, for example, apps quickly emerge to help self-evaluate symptoms and AI tools put to work to enhance X-ray diagnoses and to help with contact tracing. The cloud has also allowed researchers to rapidly create “data lakes” of clinical information to fuel the astronomical capacities of today’s supercomputers deployed in pursuit of therapeutics and vaccines.
The future of AI and the cloud will bring us a lot more of the above, along with practical home diagnostics and useful VR-based telemedicine, not to mention hyper-accelerated clinical trials for new therapies. And this says nothing about what the cloud will yet enable in the 80 percent of the economy that’s not part of healthcare.
For all of the excitement that these new capabilities offer us though, the bedrock behind all of that cloud computing will remain consistent — and consistently increasing — demand for energy. Far from saving energy, our AI-enabled workplace future uses more energy than ever before, a challenge the tech industry rapidly needs to assess and consider in the years ahead.