Pollsters Embrace AI Revolution in This Election Season

In a striking development following President Joe Biden’s announcement that he will not seek re-election, polling organization Siena College Research Institute has focused its research on Vice President Kamala Harris and her potential appeal to voters. The survey explores the sentiments of “persuadable” voters and how they perceive Harris’s candidacy.

One notable response came from a 37-year-old Republican who expressed a general preference for Donald Trump due to his assertiveness. However, when asked about authenticity and empathy, this voter highlighted a pivotal moment: “I lost a lot of faith in Trump when he didn’t even contact the family of the supporter who died at his rally,” they shared, indicating a shift toward Harris based on personal connection.

This conversation occurred not with a human pollster but with an AI chatbot named Engage, underscoring a growing trend in polling methodology. The shift toward artificial intelligence arises from a significant reduction in traditional participation rates, prompting pollsters to seek innovative avenues for gathering insights.

The practice of polling has deep roots, tracing back 200 years to the 1824 presidential race which ushered John Quincy Adams into the White House. Originally informal gatherings of voters, polling has since evolved into a sophisticated business that academic institutions and news organizations utilize to understand public opinion.

Rachel Cobb, an assistant professor of political science at Suffolk University, explains the varied purposes polls serve. For campaign teams, polls illuminate pressing issues that resonate with voters. News outlets use metrics to contextualize events, while citizens rely on polling data to gauge election dynamics and assuage anxieties regarding their candidates.

However, the landscape of polling is rapidly changing. Cobb has noted a significant decline in response rates. Traditional methods like phone calls and in-person surveys no longer suffice due to people’s reluctance to participate. “The time invested in getting the appropriate balance of people has increased,” she said, prompting pollsters to adapt.

The relentless pace of information dissemination through social media necessitates that pollsters evolve their methods. According to Leib Litman, co-CEO of CloudResearch, the incorporation of AI enables rapid data collection and analysis, allowing thousands of responses to be gathered in mere hours. This efficiency is crucial in the fast-moving world of election campaigns.

AI tools, such as Engage, are revolutionizing market research, particularly in the election sphere. They do not intend to replace human input but aim to augment it, providing a broader reach and more nuanced understanding of public sentiment. Some companies have taken a step further, employing “sentiment analysis AI” to interpret sentiments from publicly available data.

The Heartland Forward think tank utilized such technology to gauge public opinions on artificial intelligence, combining it with traditional polling methods. Executive Vice President Angie Cooper noted the results from AI and in-person gatherings aligned closely, indicating a cross-validation of data sources.

Sentiment analysis utilizes advanced machine learning to delve deeper into the intent behind words, moving beyond surface-level responses. Zohaib Ahmed of Resemble AI emphasizes that this technology, while relatively new, can enrich the data pool for pollsters and help understand nuanced opinions.

Researchers like Bruce Schneier at Harvard have identified the complexities in political polling, acknowledging that translating human responses into valuable data involves intricate calculations. Despite advancements, challenges remain, such as timely data relevance and addressing ambiguous responses effectively.

AI-assisted polling confers distinct advantages. Pollsters facing declining response rates find these technologies useful for obtaining insights on sensitive topics, allowing respondents to share opinions more freely. However, drawbacks include potential biases, as AI may misinterpret context or fail to capture underrepresented demographics actively.

Experts agree that while AI holds potential, a balanced approach remains essential. Cobbs highlights the importance of combining AI capabilities with human insights to optimize accuracy. The future of polling likely merges advanced technology with traditional methods, expanding our understanding of public sentiment in an ever-evolving political landscape.