Dr. William Brady on Social Media, Moral Outrage and Polarization
Mar 27, 2024
01:05:30
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Dr. William Brady, expert in group behavior on social media, discusses the influence of social media algorithms on moral outrage, the impact of social learning biases, and the challenges of counteracting extreme opinions online. They also explore personal bravery, individual preferences, and the complexities of balancing life roles in the digital age.
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Quick takeaways
Social media algorithms amplify moral outrage, intensifying differences in online and offline behavior.
Prime information cues influence social learning biases, reinforcing online interactions and content preferences.
Algorithmic promotion of extreme voices distorts social norms, emphasizing the need for diverse content to reduce polarization.
Deep dives
Living Beyond Human Scale: Challenges and Possibilities
Living in a digital era amid social media, artificial intelligence, and 24-hour news poses challenges to our innate need for real-life connections. The podcast explores how living beyond human scale affects our social, biological, and cognitive well-being. Dr. William Brady discusses the impact of digital environments on our sense of connection and the overwhelming nature of today's information overload.
Moral Outrage on Social Media Platforms
Dr. William Brady delves into his research on moral outrage and its expression on social media. He highlights how social media algorithms amplify moral outrage, leading to differences in behavior online versus offline. The podcast discusses the rewarding nature of engaging in moral outrage online and how ideological and political extremes are fueled, along with the use of bots to incite division and outrage.
Social Learning & Prime Information on Social Media
The podcast addresses the concept of prime information related to prestigious, ingroup, moral, and emotional cues that drive social learning biases. Dr. William Brady explains how these biases affect our interactions on social media and how algorithms amplify content that aligns with prime information, leading to a continuous loop of preference for engaging with content that resonates with our biases. The interplay of social learning biases and algorithmic reinforcement influences our online behaviors and expressions.
Algorithmic Influence on Social Media Content
Algorithms on social media platforms tend to promote content that attracts users naturally, leading to the amplification of minority extreme voices, especially in politically charged spaces like Twitter. This skewed representation distorts social norms and fosters misunderstanding of group beliefs. By focusing on diversifying content to include less extreme opinions, algorithms can provide users with a more accurate social understanding, reducing polarization and enhancing democratic conversation.
Challenges of Misinformation and AI Impact
Misinformation and generative AI pose challenges in identifying and countering false content on social media platforms, especially during pivotal events like elections. While platforms have tools to combat misinformation, transparency and user education remain crucial. Addressing discernment fatigue and confirmation bias can enhance user awareness and mitigating misinformation's harmful effects. An emphasis on algorithm transparency and representing a wider range of beliefs can contribute to a healthier online discourse.
This is the second episode in our series on the possibilities and costs of living beyond human scale. In this episode, Brené and William discuss group behavior on social media and how we show up with each other online versus offline. We’ll also learn about the specific types of content that fuel algorithms to amplify moral outrage and how they tie to our search for belonging.