Media Bias: How Your Choice of News Outlet Shapes Your Perception of AI
[Nov. 23, 2023: JJ Shavit, The Brighter Side of News]
The integration of AI into society has raised questions about its implications, biases, and societal impact. (CREDIT: Creative Commons)
As artificial intelligence (AI) continues to permeate various aspects of our daily lives, it has become a topic of significant debate. The integration of AI into society has raised questions about its implications, biases, and societal impact.
In a recent research paper titled "Partisan Media Sentiment Toward Artificial Intelligence," authored by Angela Yi, Shreyans Goenka, and Mario Pandelaere from the Virginia Tech Pamplin College of Business, the divide in public perception of AI is examined through the lens of partisan media sentiment. Their study, published in the journal Social Psychological and Personality Science, sheds light on the differing attitudes toward AI in liberal-leaning and conservative-leaning media outlets.
Divergent Media Sentiments
One of the central findings of the research is the divergence in sentiments expressed by liberal-leaning and conservative-leaning media regarding AI. The analysis revealed that articles from liberal-leaning media tend to convey a more negative sentiment toward AI compared to those from conservative media. This disparity reflects the contrasting viewpoints within these media outlets.
This approach ensured a mix of liberal-leaning and conservative-leaning sources, including well-known publications such as The New York Times, The Washington Post, The Wall Street Journal, and the New York Post. (CREDIT: Sage Publications)
The source of this opposition, as elucidated by the study, lies in the concerns expressed by liberal-leaning media regarding AI's potential to exacerbate societal biases, including those related to race, gender, and income disparities. In contrast, conservative-leaning media appears to be less apprehensive about these issues.
The study also explored how media sentiment toward AI evolved after the tragic death of George Floyd and the ensuing national conversation on social biases in society. Angela Yi, a Ph.D. student in the marketing department at Virginia Tech, noted, "Since Floyd’s death ignited a national conversation about social biases in society, his death heightened social bias concerns in the media." This heightened awareness contributed to an even more negative portrayal of AI in the storytelling of the media, particularly in liberal-leaning outlets.
The study also explored how media sentiment toward AI evolved after the tragic death of George Floyd and the ensuing national conversation on social biases in society. (CREDIT: Sage Publications)
The findings of this research carry significant implications for future political discussions and policymaking related to AI. Media sentiment often serves as an indicator of public sentiment, which can subsequently influence policymakers' positions on contentious issues. The observed differences in partisan media sentiment could lead to divergent public opinions about AI.
Angela Yi and Shreyans Goenka emphasize the importance of recognizing the power of media sentiment in shaping public opinion. Yi noted, "Media sentiment is a powerful driver of public opinion, and oftentimes policymakers look toward the media to predict public sentiment on contentious issues." This suggests that understanding the media's role in shaping public perceptions of AI is crucial for policymakers who seek to navigate the complexities of this emerging technology.
Related Stories
To investigate partisan media sentiment toward AI, the researchers undertook a comprehensive data collection process. They compiled a diverse selection of articles from various media outlets, with the political leaning of each outlet determined using the ratings from the Media Bias Rating Chart by AllSides, a company specializing in measuring the perceived political bias of online written news content.
This approach ensured a mix of liberal-leaning and conservative-leaning sources, including well-known publications such as The New York Times, The Washington Post, The Wall Street Journal, and the New York Post.
The selection criteria for articles included specific keywords like "algorithm" or "artificial intelligence" and a date range spanning from May 2019 to May 2021. This careful selection process resulted in a dataset comprising over 7,500 articles from diverse sources.
Media sentiment is a powerful driver of public opinion, and oftentimes policymakers look toward the media to predict public sentiment on contentious issues. (CREDIT: Sage Publications)
To gauge the emotional tone of each article, the researchers employed an automated text analysis tool. This tool enabled them to measure the emotional tone by calculating the difference between the percentage of positive emotion words and the percentage of negative emotion words within each text. The resulting emotional tone measure was then standardized on a scale of 0 to 100, providing a quantifiable representation of each article's sentiment.
Shreyans Goenka, an assistant professor of marketing at Virginia Tech, emphasized that the research is descriptive rather than prescriptive. The study does not take a stance on the "right" way to discuss AI. Goenka clarified, "We are not stating whether the liberal media is acting optimally, or the conservative media is acting optimally. We are just showing that these differences exist in the media sentiment and that these differences are important to quantify, see, and understand."
In a rapidly evolving technological landscape, where AI's implications are far-reaching and often debated, this research serves as a significant step toward comprehending the diverse viewpoints that inform our collective understanding of artificial intelligence.
For more science news stories check out our New Discoveries section at The Brighter Side of News.
Note: Materials provided above by The Brighter Side of News. Content may be edited for style and length.
Like these kind of feel good stories? Get the Brighter Side of News' newsletter.
Tags: #New_Discoveries, #News, #Media, #Fake_News, #Reporting, #Bias, #Science, #Research, #The_Brighter_Side_of_News
