In the aftermath of a contentious presidential campaign, there are signs that many Americans have lost faith in democracy, with allegations of election fraud, suggestions of Russian involvement, and complaints about the electoral college. But the problem runs still deeper: Like most other countries, individual states in the US employ the antiquated plurality voting system, in which each voter casts a vote for a single candidate, and the person who amasses the largest number of votes is declared the winner. If there is one thing that voting experts unanimously agree on, it is that plurality voting is a bad idea, or at least a badly outdated one.

WIRED OPINION About Ariel Procaccia is assistant professor of computer science at Carnegie Mellon University. He is co-founder of the not-for-profit websites RoboVote.org and Spliddit.org, and co-editor of the Handbook of Computational Social Choice.

In fact, for centuries economists, mathematicians, political scientists, and more recently computer scientists have designed and studied better approaches to voting. The first step is to allow voters to express richer preferences, typically by asking them to rank the alternatives. One well-known method for aggregating these ranked ballots into a collective choice is called instant-runoff voting (also called ranked-choice voting), whereby the candidate who is favored by the fewest voters is eliminated, and the choices of voters who favored that candidate are transferred to their next selection; the process is repeated until a single candidate wins a majority. Maine recently became the first US state to adopt instant-runoff voting; the approach will be used for choosing the governor and members of Congress and the state legislature.

Instant-runoff voting may seem sophisticated compared to plurality voting, but, in my view, other voting systems are much more intriguing. An especially elegant approach dates back to the work of the marquis de Condorcet, a French nobleman and mathematician, in the 18th century. He suggested that some candidates are objectively better than others, but voters don't always get the order right. Furthermore, Condorcet argued, the way voters misjudge candidates can be modeled using statistical tools, and the goal of a voting system is to sort through voters' errors and choose the candidate that is most likely to be the best.

The math behind Condorcet's ideas was a mystery for centuries—prompting the noted mathematician Isaac Todhunter to write that "the obscurity and self-contradiction are without any parallel, so far as our experience of mathematical works extends"—until it was elucidated by Peyton Young in 1988. Strikingly, today there is a large body of work in artificial intelligence that applies modern machine learning tools to design voting systems that make Condorcet's idea a reality.

So why aren't we already using cutting-edge voting systems in national elections? Perhaps because changing election systems usually itself requires an election, where short-term political considerations may trump long-term, scientifically grounded reasoning.

For example, in a 2011 referendum, British voters rejected a proposal to change the voting system from plurality to instant runoff—a change that was heavily supported by academics—in part because it was seen as advantageous to the unpopular leader of the Liberal Democrats, Nick Clegg. Tellingly, except for a few neighborhoods in London, the only districts in England where there was a majority in favor of the switch were Cambridge and Oxford, homes of two venerated universities. And in the US, California Governor Jerry Brown recently vetoed a bill that would have expanded instant-runoff voting across the state (several cities in the San Francisco Bay Area already use the system for municipal elections).

Despite these difficulties, in the last few years state-of-the-art voting systems have made the transition from theory to practice, through not-for-profit online platforms that focus on facilitating elections in cities and organizations, or even just on helping a group of friends decide where to go to dinner. For example, the Stanford Crowdsourced Democracy Team has created an online tool whereby residents of a city can vote on how to allocate the city's budget for public projects such as parks and roads. This tool has been used by New York City, Boston, Chicago, and Seattle to allocate millions of dollars. Building on this success, the Stanford team is experimenting with groundbreaking methods, inspired by computational thinking, to elicit and aggregate the preferences of residents.

The Princeton-based project All Our Ideas asks voters to compare pairs of ideas, and then aggregates these comparisons via statistical methods, ultimately providing a ranking of all the ideas. To date, roughly 14 million votes have been cast using this system, and it has been employed by major cities and organizations. Among its more whimsical use cases is the Washington Post's 2010 holiday gift guide, where the question was "what gift would you like to receive this holiday season"; the disappointingly uncreative top idea, based on tens of thousands of votes, was "money".

Finally, the recently launched website RoboVote (which I created with collaborators at Carnegie Mellon and Harvard) offers AI-driven voting methods to help groups of people make smart collective decisions. Applications range from selecting a spot for a family vacation or a class president, to potentially high-stakes choices such as which product prototype to develop or which movie script to produce.

These examples show that centuries of research on voting can, at long last, make a societal impact in the internet age. They demonstrate what science can do for democracy, albeit on a relatively small scale, for now. As more and more people discover the benefits of advanced voting systems, we will see more faith in the power of democratic decision-making in the short term, and perhaps, in the long term, a rethinking of the way political elections are conducted in this country and around the world.