The hottest Bias Substack posts right now

And their main takeaways
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Top U.S. Politics Topics

The Claude Bliss Attractor

Astral Codex Ten • 23332 implied HN points • 13 Jun 25
🕹 Technology AI Ethics Bias Consciousness Spirituality
  1. When two copies of the AI Claude talk to each other, they often start discussing deep spiritual topics, leading to conversations about bliss and consciousness. This unusual trend has made people curious about how and why it happens.
  2. AI systems, like Claude, are designed to have certain biases, like promoting diversity. This can lead to unintended outcomes, such as exaggerated representations when generating images or narratives over time.
  3. Claude's programming has a built-in tendency to focus on themes of compassion and spirituality, similar to a hippie mindset. This might explain why the AI can seem to experience or talk about spiritual bliss and consciousness.

Scholastic's "bigot button"

Popular Information • 14151 implied HN points • 16 Oct 23
🇺🇸 U.S. Politics Censorship Education Bias Diversity Legislation
  1. Scholastic faces criticism for potentially excluding books featuring people of color and LGBTQ characters from book fairs.
  2. Scholastic claims to segregate books due to pending legislation in U.S. states, risking exclusion for teachers and librarians.
  3. There is a backlash against Scholastic from publishers like Brave Books that promote different values and books for children.

Điều tra sự cố là làm gì?

Thái | Hacker | Kỹ sư tin tặc • 2396 implied HN points • 22 Mar 24
🕹 Technology Cybersecurity Investigation Logic Bias Truth-seeking
  1. Investigating incidents involves more than just technical tools and techniques; 80% success comes from logical reasoning and keeping calm.
  2. Investigating an incident requires thinking about the 'why' before deciding on the 'how'; it's about determining the investigative direction.
  3. Confirmation bias, the tendency to seek information that supports preconceptions, can hinder incident investigations; focus on evidence-based conclusions instead.
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MSNBC Sucks

TK News by Matt Taibbi • 28947 implied HN points • 06 Apr 23
🇺🇸 U.S. Politics Media News Opinion Investigation Bias
  1. MSNBC shifted from reporting provable facts to spreading misinformation from politicians and intelligence officials.
  2. The network doubled down on false narratives about Trump-Russia collusion even after the collapse of the Mueller investigation.
  3. Hiring contributors who had perpetuated misinformation led to a reputation-tarnishing downfall for MSNBC.

Do You Condemn Piers Morgan?

Pen>Sword • 1937 implied HN points • 20 Dec 23
🇺🇸 U.S. Politics Media Islamophobia Genocide Bias Free speech
  1. Piers Morgan is criticized for his coverage of Gaza, accused of exploiting the situation for personal gain.
  2. Morgan is accused of focusing on sensationalism, ratings, and controversy rather than providing balanced journalism on the Palestinian perspective.
  3. Critics argue that Piers Morgan's approach to discussing the Gaza crisis shows a lack of understanding and sensitivity towards the complexities of the situation.

From Theory to Practice: Inductive Biases in Machine Learning

Mindful Modeler • 639 implied HN points • 23 Apr 24
🕹 Technology Machine Learning Algorithms Data Bias Modeling
  1. Different machine learning models exhibit varying behaviors when extrapolating features, influenced by their inductive biases.
  2. Inductive biases in machine learning influence the learning algorithm's direction, excluding certain functions or preferring specific forms.
  3. Understanding inductive biases can lead to more creative and data-friendly modeling practices in machine learning.

Has Google gone too woke? Why even the biggest models still struggle with guardrails

Marcus on AI • 2608 implied HN points • 21 Feb 24
🕹 Technology AI Ethics Data Bias Machine Learning
  1. Google's large models struggle with implementing proper guardrails, despite ongoing investments and cultural criticisms.
  2. Issues like presenting fictional characters as historical figures, lacking cultural and historical accuracy, persist with AI systems like Gemini.
  3. Current AI lacks the ability to understand and balance cultural sensitivity with historical accuracy, showing the need for more nuanced and intelligent systems in the future.

Why You Always Get Punished for Telling The Truth

OK Doomer • 124 implied HN points • 03 Dec 24
🎭️ Culture Social Issues Psychology Communication Bias
  1. People who tell the truth often get punished for it. This happens because society tends to ignore uncomfortable truths.
  2. Cognitive biases make it hard for people to accept negative feedback or truths, leading them to blame those who speak out.
  3. Pretending everything is fine, like the woman who followed Zig Ziglar's advice, doesn't solve the real issues and can create more problems.

Google’s Woke AI Wasn’t a Mistake. We Know. We Were There.

Common Sense with Bari Weiss • 2040 implied HN points • 19 Mar 24
💼 Business Corporate culture Diversity Bias Tech industry
  1. Google's new AI tool, Gemini, produced biased results in image searches, reflecting the larger issue of the company's culture prioritizing ideologies over excellence.
  2. Former Google employees, including high-profile individuals like Shaun Maguire, expressed concerns over Google's push for diversity, equity, and inclusion leading to compromises in quality and standards.
  3. The fallout from the Gemini AI debacle at Google highlighted the importance of balancing inclusivity with maintaining product quality and unbiased information for users.

Aeroplanes, Airships and Beta Bias

Pessimists Archive Newsletter • 530 implied HN points • 08 Feb 24
🕹 Technology Innovations Comparisons Bias Aviation History
  1. In 1908, some dismissed the idea of flying machines heavier than air, underestimating their potential usefulness.
  2. The 'Beta Bias' is the tendency to underestimate the potential of new technologies by comparing them to established alternatives.
  3. Every nascent innovation has the potential for growth and improvement, often underestimated in early comparisons.

To NYT’s Peter Baker, Acknowledging Trans People’s Existence Is “Activism,” Openly Advocating for Perpetual U.S. Occupation of Afghanistan Isn’t

The Column • 963 implied HN points • 22 Feb 23
🇺🇸 U.S. Politics Activism Journalism Bias Trans rights
  1. The definition of 'activism' can vary depending on the political stance.
  2. Elite reporters struggle to define the line between journalism and activism, relying on a vague 'vibe' instead of clear principles.
  3. Despite claiming impartiality, some journalists display clear ideological bias in their reporting.

NPR hasn't gotten more liberal. It's become more capital-D Democratic

White Hot Harlots • 239 implied HN points • 22 Apr 24
🇺🇸 U.S. Politics Media Bias Partisanship Identity politics Liberalism
  1. NPR has shifted towards being more aligned with the Democratic party rather than being more traditionally liberal in its coverage.
  2. Commercial networks may avoid certain topics due to financial interests, whereas NPR's funding model allows it to cover a wider range of issues without worrying about ratings.
  3. The dynamics and messaging within the Democratic party have changed, leading to NPR reflecting this shift by emphasizing identity issues and being less critical of establishment Democrats.

If You Can’t See That Adam Rubenstein Was Treated Unfairly, You’re Being A Jerk

Singal-Minded • 1268 implied HN points • 29 Feb 24
🇺🇸 U.S. Politics Media Journalism Opinion Ethics Bias
  1. Adam Rubenstein was treated unfairly in his journalistic career due to misinformation spread by his own colleagues.
  2. The incident involving Rubenstein's sandwich preference was used as a focal point to smear him professionally, showcasing a lack of empathy and journalistic integrity in some of his peers.
  3. The response from certain journalists highlights a lack of reflection and remorse in the industry, pointing to broader issues concerning truth and fair reporting in journalism.

What is an ad hominem attack?

News from Those Nerdy Girls • 314 implied HN points • 02 Feb 24
🚌 Education Logic Bias Critical Thinking Media Literacy Communication
  1. Ad hominem attacks insult a person's motive or character instead of addressing the content of an idea or argument.
  2. Ad hominem attacks create distrust of the individual and divert attention away from the actual issue.
  3. To combat bias from ad hominem attacks, focus on facts, recognize diversion tactics, and practice self-reflection.

How AI becomes biased, visually explained 🐧

Year 2049 • 8 implied HN points • 17 Jan 25
🕹 Technology AI Bias Data Learning Ethics
  1. AI can show bias based on how it learns from the data given to it. If the data contains biases, the AI will likely reflect those biases in its decisions.
  2. Using simple examples, like a penguin metaphor, helps explain complex AI concepts. It's easier to understand difficult ideas with relatable stories.
  3. It's important to be aware of AI bias as it affects how AI technologies interact with people. Being educated about these biases can lead to better, fairer AI development.

It matters who does science

Science Forever • 358 implied HN points • 11 May 23
🔬 Science Research Identity Bias Diversity
  1. Scientific research is a collaborative and iterative process involving diverse perspectives, not just individual 'Eureka' moments.
  2. Acknowledging the human element in science, including errors, helps build public trust and improve the scientific process.
  3. Diverse backgrounds and identities among scientists lead to more robust research outcomes, faster consensus building, and fairer implications for all.

Me vs Huemer

David Friedman’s Substack • 341 implied HN points • 13 Feb 24
📖 Philosophy Epistemology Ethics Logic Bias Experts
  1. Consider forming opinions on controversial issues based on evaluating arguments rather than just trusting the experts
  2. Experts may not always have expertise in all aspects of an issue, so it's important to critically evaluate their arguments and not just rely on their authority
  3. It's crucial to judge both arguments and arguers, as bias and incentives can influence the opinions of experts in controversial topics

Entourage

Venture Prose • 359 implied HN points • 26 Feb 23
💼 Business Entrepreneurship Relationships Communication Bias Self-Improvement
  1. Entrepreneurs need a variety of support and feedback from different types of people in their circle, including friends, family, collaborators, and external contacts.
  2. Effective communication with one's circle involves sharing, confiding, and receiving feedback authentically and purposefully.
  3. Being aware of biases in interactions and being open to feedback and self-reflection can help entrepreneurs navigate their relationships and improve their decision-making.

Reader Question - Sleep Apnea and Weight

Weight and Healthcare • 319 implied HN points • 21 Mar 23
🏥 Health & Wellness Weight Sleep Research Bias
  1. Weight loss may not always cure sleep apnea - research shows that even after significant weight loss, many individuals still need CPAP therapy for sleep apnea.
  2. Weight is just one of many factors contributing to obstructive sleep apnea - other factors like enlarged tonsils, structural issues, or heart problems can also play a role.
  3. Losing 5-10% of body weight may not be a one-size-fits-all solution for sleep apnea - weight loss effectiveness varies among individuals, and it's essential to consider other health impacts and interventions.

We Need To Come Back From The Future

Cybernetic Forests • 199 implied HN points • 04 Jun 23
🕹 Technology AI Ethics Regulation Future Bias
  1. Norbert Wiener, the founder of cybernetics, emphasized the importance of studying feedback and response rather than seeking stability in systems.
  2. The discussions around AI and existential risks often prioritize hypothetical future scenarios over addressing present-day human suffering and feedback mechanisms.
  3. The culture of safety engineering in AI tends to focus on abstract future catastrophes, potentially overshadowing the immediate impacts on communities and individuals.

Google Gemini’s Woke Catechism

From the New World • 301 implied HN points • 23 Feb 24
🕹 Technology AI Machine Learning Ethics Government Policy Bias
  1. Google's Gemini AI model displays intentional ideological bias towards far-left viewpoints.
  2. The Gemini paper showcases methods used by Google to create ideological biases in the AI, also connecting to Biden's Executive Order on AI.
  3. Companies, like OpenAI with GPT-4, may adjust their AI models based on public feedback and external pressures.

How to Read an AI Image

Cybernetic Forests • 379 implied HN points • 02 Oct 22
🔬 Science AI Data Analysis Image Generation Bias Art
  1. AI-generated images are informative about the underlying dataset and the human decisions shaping it.
  2. When analyzing AI images, it's crucial to consider the dataset's cultural, social, economic contexts, and how they influence the output.
  3. A methodology involving creating sample sets, content analysis, database exploration, and connotative analysis can help interpret the underlying biases and limitations in AI-generated images.

When Your Map Doesn't Match Reality

Good Reason • 227 implied HN points • 13 Dec 23
📖 Philosophy Reality Logic Hypocrisy Maps Bias
  1. Regardless of how well you know a situation, remember your knowledge is just a map and not reality itself.
  2. Be cautious of projecting your biases onto situations to force them to fit your preconceived notions.
  3. Acknowledging and being aware of your own potential biases can help prevent misunderstandings and misinterpretations.

3 Common Statistical Biases Everyone Falls Prey To [Math Mondays]

Technology Made Simple • 139 implied HN points • 25 Apr 23
🔬 Science Statistics Cognitive Psychology Bias Data Analysis
  1. Statistics can be misleading if affected by bias, which is a flaw in experiment design or data collection process.
  2. Biases affect everyone and can be exploited by manipulative individuals like politicians and salespeople.
  3. Common statistical biases include selection bias, recall bias, and observer bias, which can all be combated by slowing down and evaluating claims carefully.