Political favors turn to AI in the race for cash | Tech Rasta

An example of a dollar sign made of binary code becoming a checkmark made of binary code.

Illustration: Brendan Lynch/Axios

Innovations in artificial intelligence are making political campaigns faster and cheaper to identify, convert and raise money for voters.

Big picture: Consultants from both major parties collected voter data to hone sophisticated fundraising and persuasion tactics. These data tools are especially useful in down-ballot local races.

  • Consultants say they can dramatically improve campaigns by asking machines to synthesize massive amounts of data — from incomes to consumer buying habits — to predict how people donate and vote.

What’s happening: Many consultancies are now marketing the use of AI and machine learning to boost political clients.

  • Sterling Data Company, a Democratic organization, claims that digital fundraising can double performance in the immediate term.
  • Numinor, a Republican startup, touts highly effective voter modeling and predictive capabilities.
  • Veteran Democratic fundraiser Anne Lewis’ firm, MissionWired, recently unveiled a fundraising product called AdvantageAI.

What they say: “This is the super-weapon that Democrats have,” boasted Sterling’s managing partner Martin Kuruz, who said his firm has worked with about 1,000 Democratic campaigns and political committees.

  • “It’s one of the most overlooked reasons Democrats win the small-dollar fundraising wars against Republicans,” he said.
  • Numinar said it worked with about 300 political clients this cycle, and FEC records show payments from some key Senate and House campaigns this year.
  • “AI and machine learning can really help these campaigns, 80% of which are down-ballot local races, make a huge difference in the performance of their races,” Numinor founder Will Long said in an interview with Axios.

How it works: Every company in the space uses massive amounts of political and consumer data to come up with an ever-improving algorithm that can predict voter or donor behavior.

Sterling uses technology To tailor fundraising strategies to each client, the company says in its marketing materials:

  • “No data analyst in the world can look at 500 variables, from household income to magazine subscriptions, and figure out which factor played the biggest role in the success (or failure) of a fundraising campaign and reframe the goal to maintain or improve results — essentially in less than a minute.”

AI based software It makes it much easier for organizations to identify new donors — people who have the highest propensity to give to a campaign.

  • And Numinar says the ability to predict how a given voter will vote makes its services highly valuable to campaigns trying to allocate scarce resources more efficiently.

Reality check: Some political activists are skeptical, describing it as a marketing gimmick rather than a real advance in political data technology.

  • “Some people are using artificial intelligence as a game changer. And then a lot of people are using artificial intelligence and machine learning to sell a product,” said Democratic digital strategist Mark Jablonowski.
  • When asked about the trend, a veteran Republican consultant captioned the GIF, labeling it “magic.” He described AI as a “catch-all BS term” in the political world.

Yes, but: Numinar’s Long admits the term can be misused, but says AI is an accurate description of some of the most advanced technology being deployed in political races across the country.

  • “We’re actually using machine learning in a very core, fundamental way,” he said, referring to the firm’s internal voter models that improve every time new data — provided by its political clients — is fed into those models.

The bottom line: Whether you like to call it AI, machine learning, or old-fashioned data crunching, the technology underlying political campaigns is evolving rapidly.

  • “Every election cycle, political data, analytics and modeling grow exponentially,” Jablonowski said. “The types of models that are created and the inputs that go into them will grow exponentially.”

Source link