Unmitigated climate change poses an existential threat to our way of life.
A major economic study projects a long-term 20 percent reduction in global gross domestic product from climate change. To avoid such unprecedented declines, we must reduce our greenhouse emissions in the U.S. by 80 percent by 2050. This goal is realistic, but a major undertaking that requires deliberate action.
Numerous economic models demonstrate that transitioning to renewable energy is likely to result in a net economic gain for our society. That does not mean that every individual will benefit, nor that the transition with be without pain, but it does mean that the transition is likely to result in more jobs and a more efficient and resilient electricity system. A recent study by the Risky Business Project provides a framework for an approach that is both technically and economically feasible. It is based on three principal transitions: shifting from fossil fuels to electricity, generating electricity from low- and zero-carbon sources and using all energy more efficiently.
The shift from fossil fuels to electricity includes the gradual adoption of electric vehicles, electric and geothermal heat pumps, and electricity in industrial processes. The shift to renewable electricity production requires a rapid transition to zero-carbon sources, like wind, solar, geothermal and nuclear, along with an expansion of energy-storage technologies and a redesigned grid to reduce the variability impacts of wind and solar. The potential for increased efficiency in energy use is significant, as we lose about half of all electricity generated in the U.S. to system losses. A redesigned distributed generation grid could dramatically reduce those losses.
The cost of this particular plan would be around $320 billion a year from 2020 to 2050, but the returns over the life of the transition would be substantially larger and would continue indefinitely. The savings would start at around $65 billion a year in the 2020s, increasing to over $700 billion a year in the 2040s. Around 1 million additional jobs would be created during the 30-year transition, with many of the largest gains being in the domestic construction and utilities sectors. While other approaches may offer greater or fewer costs or benefits, the important point is that the renewable energy transition can be a win-win proposition for our economy.
KATHERINE ELKINS | Associate Professor of Comparative Literature and Humanities JON CHUN | Visiting Instructor of Humanities, Affiliated Scholar in Scientific Computing
When IBM Deep Blue defeated chess champion Garry Kasparov in 1997, The New York Times reported it would take 100 years before a computer could defeat a human Go master. Go is a vastly more complex game than chess that requires computers to rely on heuristic shortcuts that mimic human intuition.
Yet it was just 20 years later when AlphaGo twice defeated Lee Sedol, an 18-time world Go champion, and became the first computer to beat a top-ranked human in a Go match.
Astonishing advances like this have led to a global “arms race” in artificial intelligence, as companies compete to acquire top AI talent. Last year, China announced a multibillion-dollar initiative to become the world leader in AI and, recently, Russian President Vladimir Putin proclaimed, “Whoever becomes the leader in this sphere will become the ruler of the world.”
While AI experts work to develop smarter AI applications for all of us — from driverless cars to personal assistants — fewer have taken up the broader challenge to ensure we don’t become, in Henry David Thoreau’s words, “the tools of our tools.”
What we need now are humanists conversant in AI who can critique and shape the future that AI may restructure. After all, AI forces us to ask questions about what it means to be human. And answering these questions will, in the end, be more important than AI milestones like AlphaGo. The only way to answer these questions is to develop an understanding of the world that is both broad and deep, since these questions cannot be answered within any single discipline or major.
No one in 1997 could have predicted the advances in big data, computational power and algorithms that are making AI increasingly powerful and inexpensive. How, then, can we predict what AI will look like 20 years from now? Even the experts are poor at forecasting this future. But the rapid and revolutionary changes being brought on by AI compel us to continue putting the human at the center of our technological world.