Hedge Against Election Day Surprises with AI

Hedge against election day surprises with Calibrate 720

Hedge Against Election Day Surprises with AI

Artificial intelligence (AI) still seems like a fantastical and futuristic notion for most of us, but in reality, markets are embracing this new technology at an impressive rate. Everything from environmental protection to car sales has seen the introduction of this technology in some sort of way.

Systems like our own Calibrate720 typify how AI and machine learning, when coupled with Natural Language Processing, can provide powerful decision-making tools for an industry often thought of as slow to embrace new things: political campaigns. At 720, we’ve coupled our usual pioneering spirit with this new technology and incorporated it into our grassroots advocacy campaigns. 

Despite its successful track record across a variety of industries, employers, campaign managers, and politicos still have reservations about AI capabilities and benefits to their political campaigns. So, we’ve compiled a few key takeaways to show how AI tech can be a gamechanger for campaigns and even help campaign managers avoid the dreaded Election Day surprise — because let’s face it, every campaign wants to know what’s potentially headed their way and begin to strategize on how to deal with it.

How does it work?

Calibrate720 scrapes 300,000 discrete sources of publicly available data, then analyzes and categorizes it by the AI. It reads a tweet, Facebook post, news article, letter to the editor, etc., down to the sentence level and thinks the same way an intern cutting press clippings would. 

“Is this article or tweet beneficial to the campaign? Is it harmful?” The system then further categorizes the data into a series of other considerations. The considerations include factors such as location, gender, language preference and, of course, political leaning. 

The results are stunning. The system answers questions such as: How are my candidate’s issues (or my candidate) covered in large left-leaning outlets? How does that differ from right-leaning outlets?

Social media data is then fused to traditional media for an even clearer picture of the media landscape. What is the narrative around my candidate’s issues for older female Republicans in Wisconsin? How about blue-collar Democrats in upstate New York? How does the narrative between the press and social media discussion align? How does it differ? Are you in a bubble?

Typical capabilities fail to segment audiences by demographics, use over-simplified methodologies or fail to combine traditional and social media insights into a picture that is more comprehensive and, ultimately, more useful. 

Human, all too human.

For all too human pundits and analysts, there is an important lesson in this. Because of the way the AI is taught to analyze and “think” about articles, it is largely devoid of bias. It’s diligence in reading everything it can find means that confirmation bias did not create a false perception of reality.

The data is not quantitative, per se, but the quantities are so vast and can be organized to understand so much about news outlets and the general populace, that the data is compelling enough to make a decision. These are decisions that can lead a campaign to change its strategy and/or tactics based on the real-time synthesis of large amounts of data offering campaign staff a glimpse around the proverbial corner.

Where next?

Present-day tools that analyze social media or traditional media help you monitor the news. Calibrate720 is part of the next generation of tools that synthesizes and contextualizes data for decision-making. Campaigns will better understand voters and issues in new and more nuanced ways, which means better campaigns more attuned to the will of the people.

And all of this can be done without being overly invasive to the individual or their personal information and represents the aggregate interests and behaviors of groups of people that are analyzed by the system.

You won’t be replaced by a machine.

AI has a bright future in political campaigns. But for professionals, you are not going to be replaced by a robotic campaign manager anytime soon. There is a great deal of confusion, and as a consequence, the mystery surrounding “Big Data” and AI concepts sometimes dissuades operatives from employing the very thing that will give them the edge toward winning.  

AI-enabled capabilities and decision-making are nowhere near the sophistication where jobs for campaign professionals are at stake. When massive data sets are required, AI capabilities serve as a “legion of interns” doing media clippings and analysts alerting decision-makers to even the most hidden inflection points that can help propel a campaign to victory. Tailor your creative, smith your words further or even change the size of a media buy based on how prevalent an issue is — all these pillars of a campaign can be affected. 

Check to make sure that you don’t start to believe your own PR. In other words, stay humble and inquisitive. New ways to approach the problems before you are here, and for campaigns with fewer data to crunch, there is still good news: AI can shed your bias and offer critical analysis so you can put in the real work of refining your messages and engaging voters. Together you can go a long way to avoiding Election Day surprises.

Christopher Alexander is vice president of government services and strategic communication and Ryan Shucard is vice president of media relations at 720 Strategies.