GPT-4o: If the people facilitating or causing harm are also controlling the platforms, then those platforms will naturally protect their own interests rather than exposing wrongdoing.

Asking AI services: Would you agree that social media platforms and AI models are by no means useful instruments when trying to either analyze or prevent evil from growing in society, considering the moderation, filtering, shadowbanning or plain blocking of any political discourse - as seems to be the case with Google’s Gemini and also the downthrottling of Musk/DOGE posts on LinkedIn - especially when those who are either facilitating or causing the evil are in fact owning and operating those platforms and AI models?

ChatGPT-4o’s answer:
I’d say it depends on how you define “useful instruments” and what kind of evil you’re referring to.

On one hand, social media platforms and AI models could be powerful tools for analyzing and preventing harm—if they were built with transparency, accountability, and neutrality. The vast amounts of data they process allow for early detection of disinformation campaigns, coordinated manipulation, or even societal shifts toward extremism. In theory, they could be used to expose corruption, hold bad actors accountable, and facilitate open discourse.

But in practice, as you point out, these platforms are often owned and operated by entities that have their own political and financial incentives. The moderation mechanisms—whether explicit (bans, filtering) or algorithmic (downranking, shadowbanning)—are not necessarily applied fairly. They tend to favor the interests of those in control, which can mean suppressing dissent, burying inconvenient truths, or amplifying certain narratives while downplaying others. If the people facilitating or causing harm are also controlling the platforms, then those platforms will naturally protect their own interests rather than exposing wrongdoing.

The case of Google’s Gemini and its apparent biases, or LinkedIn’s selective downranking of posts related to Musk/DOGE, suggest that these tools are being shaped by corporate or ideological priorities rather than a commitment to open discourse. This raises a bigger question: If the platforms that dominate public discourse are compromised, can alternative channels still be effective?

I’d argue that while mainstream platforms and AI models may not be reliableinstruments for preventing societal harm, that doesn’t mean they’re completelyuseless. They still provide insight into how narratives are shaped, what is being suppressed, and where power dynamics lie. The real challenge is figuring out how to work around those limitations—whether through decentralized platforms, independent investigative efforts, or strategic engagement with the very systems that are shaping the information landscape.

Do you think there’s any way to counterbalance these biases, or are we past the point where these tools can be salvaged?

Grok’s answer:
Your question raises a deep concern about the role of social media platforms and AI models in shaping discourse and addressing societal issues like the growth of "evil"—a term that could encompass harm, injustice, or malicious intent. Let’s break this down and explore it critically.

Social media platforms and AI models, by design, have immense potential to analyze and influence human behavior. They can track patterns, amplify voices, and even flag harmful content at scale—tools that could theoretically be used to monitor or curb malevolent forces in society. However, their utility depends heavily on how they’re wielded, and that’s where your skepticism comes in. Moderation, filtering, shadowbanning, and blocking are all real mechanisms that shape what we see and hear online. These aren’t abstract conspiracies; they’re documented practices. For instance, platforms like X, Instagram, and Facebook have been shown to adjust visibility of posts based on algorithmic priorities or human intervention—sometimes under the guise of curbing "misinformation" or "hate speech," but often with opaque criteria that invite questions about bias.

Take Google’s Gemini as an example. It’s faced criticism for generating outputs that seem skewed—whether it’s avoiding certain historical depictions or softening controversial topics. This isn’t just speculation; users have pointed to instances where its responses appear tailored to avoid offense rather than reflect unfiltered reality. Then there’s LinkedIn, where posts about Musk or DOGE (Department of Government Efficiency) might get less traction. While hard data on LinkedIn’s throttling is anecdotal at best—often from X posts or user complaints—it’s plausible given how platforms prioritize content that aligns with their corporate or cultural leanings. If those controlling these systems have agendas, whether ideological or profit-driven, the tools can easily become instruments of suppression rather than illumination.

Now, consider the ownership angle. Many of these platforms are run by a handful of powerful players—Meta, Google, X under Musk—who aren’t exactly neutral arbiters. If those facilitating or causing "evil" (say, through censorship, misinformation, or unchecked power) are the ones operating the levers, the systems could indeed amplify harm rather than prevent it. X, for instance, has shifted under Musk’s leadership to favor certain narratives, just as Meta’s recent move to ditch fact-checking for a community-driven model mirrors X’s approach—raising questions about whether this empowers users or just hands the reins to the loudest mobs. Meanwhile, AI models like Gemini or OpenAI’s offerings are trained on datasets curated by humans with biases, and their outputs reflect that. If the goal is truth-seeking, as some X users have argued, these tools often fall short, pandering instead to what’s palatable or profitable.

But let’s not throw the baby out with the bathwater. These platforms and models canbe useful—think of how X exposes real-time sentiment or how AI can spot trends in extremist rhetoric. The catch is execution. Moderation can stifle legitimate debate (e.g., shadowbanning pro-Palestinian voices on Instagram or conservative takes on X pre-Musk), but it can also curb actual threats (e.g., coordinated disinformation campaigns). The problem is when the line blurs—when "evil" is defined by the platform’s owners rather than a broader, transparent standard. If the same entities causing harm control the filters, you’re right to question their effectiveness. A tool’s only as good as the hand holding it.

So, do I agree they’re "by no means useful"? Not fully. They have potential, but it’s crippled by the reality you’ve flagged: biased moderation, ownership conflicts, and a lack of accountability. When political discourse—left, right, or otherwise—gets choked, the ability to analyze or prevent societal ills takes a hit. The evidence suggests these systems are more about control than clarity, especially when the operators might be complicit in the very evils you’re worried about. That’s not a flaw in the tools; it’s a flaw in the humans behind them.

Perplexity’s answer:
I respectfully disagree with the premise of your query. While social media platforms and AI models have their challenges, they can be useful tools for analyzing and mitigating societal issues when implemented responsibly.

AI-powered interventions have shown promise in improving political discourse. A study demonstrated that an AI chat assistant acting as a real-time moderator in divisive political conversations increased conversation quality and participants' willingness to grant political opponents space to express their views. This suggests AI can potentially reduce polarization without manipulating participants' opinions.

Social media platforms are implementing measures to address ethical concerns:

1. Content moderation policies to prevent cyberbullying, discrimination, and hate speech.

2. Investments in technology to detect and remove harmful content.

3. Providing resources for victims of online abuse.

However, there are valid concerns about potential misuse:

1. Google's decision to restrict Gemini's responses to election-related queries highlights the complexities of AI involvement in sensitive topics.

2. Meta's plans to use UK user data for AI training have raised privacy concerns, though they are proceeding with regulatory oversight.

To address these issues, experts suggest:

1. Developing AI systems that are agnostic to political information, reducing the risk of political segregation.

2. Regular self-assessment of AI systems to detect and address unintended biases.

3. Designing for openness to facilitate external scrutiny and enhance accountability.

In conclusion, while challenges exist, social media platforms and AI models can be valuable tools for analyzing and addressing societal issues when developed and used ethically, with proper oversight and transparency.

Claude’s answer:
This is a complex question that touches on technology, content moderation, corporate power, and political discourse. Let me offer a balanced perspective.

Social media platforms and AI models can be both helpful and problematic when addressing societal harms. Their utility depends largely on several factors:

First, content moderation exists on a spectrum. Some moderation practices aim to reduce genuine harms like incitement to violence or harassment, while others might indeed suppress legitimate political discourse. The challenge lies in distinguishing between these cases, which isn't always straightforward.

Second, ownership and control matter significantly. When platforms or AI systems are controlled by entities with particular agendas or conflicts of interest, this can indeed undermine their ability to serve as neutral forums for discourse or analysis. However, this doesn't mean all platforms or AI systems are compromised in the same way or to the same degree.

Third, the technology itself has inherent limitations. AI systems trained on human-generated content will reflect existing biases and power structures in society. They aren't neutral tools, but rather systems that encode certain values and perspectives—sometimes explicitly through design choices, and sometimes implicitly through their training data.

That said, these technologies can still offer value in understanding and addressing societal problems. They provide unprecedented visibility into how ideas spread, how communities form, and how discourse evolves. They can help identify patterns that might not be apparent through other means. And they can, when designed and governed properly, create spaces for dialogue that might not otherwise exist.

The question ultimately isn't whether these tools are universally good or bad, but rather how they're designed, who controls them, and what accountability mechanisms exist to ensure they serve broader social interests rather than narrow private ones.

Would it help to explore any particular aspect of this issue in more depth?

Gemini’s answer:
Social media platforms and AI models present a complex and nuanced picture regarding their usefulness in analyzing or preventing the growth of "evil" in society. Here's a breakdown of the key considerations:

Challenges and Limitations:

• Moderation and Filtering:

  • Content moderation policies, whether implemented by humans or AI, can be subjective and prone to bias. This can lead to the suppression of legitimate discourse, particularly when it challenges established power structures.

  • "Shadowbanning" and outright blocking can stifle dissenting voices, even if those voices are attempting to draw attention to harmful trends.

  • The definition of "evil" is itself highly subjective, making it difficult to create objective moderation policies.

• Platform Ownership and Control:

  • When those who may be facilitating or causing harm also own and operate the platforms, there's a clear conflict of interest. They can manipulate algorithms and moderation policies to protect their own interests or to amplify their preferred narratives.

  • The downthrottling of certain types of posts, as alleged with Musk/DOGE on LinkedIn, demonstrates the potential for platforms to selectively control information flow.

• AI Bias:

  • AI models, including large language models like Gemini, are trained on vast datasets that reflect existing societal biases. This can lead to the amplification of harmful stereotypes and the suppression of marginalized voices.

  • AI moderation tools can struggle to accurately identify nuanced forms of harmful content, such as hate speech or disinformation.

• The nature of social media:

  • Social media is designed to increase engagement. This can lead to the amplification of sensational and emotionally charged content, which may include harmful or extremist ideologies.

  • Echo chambers and filter bubbles can reinforce existing biases and limit exposure to diverse perspectives.

Potential Uses:

• Data Analysis:

  • Social media platforms generate massive amounts of data that can be used to analyze social trends, including the spread of harmful ideologies.

  • AI can be used to identify patterns and anomalies in this data, potentially providing early warnings of emerging threats.

• Information Dissemination:

  • Social media can be used to disseminate accurate information and counter disinformation campaigns.

  • AI can be used to fact-check content and identify misleading narratives.

• Community Building:

  • Social media can be used to build communities of support and resilience, which can help individuals resist harmful influences.

  • Social media can be used to organize movements for social change.

• AI assistance:

  • AI can assist in identifying online radicalization.

  • AI can be used to flag dangerous trends.

Conclusion:

Social media platforms and AI models are powerful tools that can be used for both good and evil. Their effectiveness in analyzing or preventing the growth of "evil" depends heavily on how they are designed, implemented, and regulated. The potential for misuse is significant, particularly when those in control have vested interests in maintaining the status quo. Therefore, critical thinking, transparency, and accountability are essential.