The hottest Bias Substack posts right now

And their main takeaways
Category
Top U.S. Politics Topics

The philosophical and empirical cases for ignoring bad or biased pollsters | #210 - February 26, 2023

G. Elliott Morris's Newsletter β€’ 157 implied HN points β€’ 27 Feb 23
πŸ‡ΊπŸ‡Έ U.S. Politics Philosophical Bias
  1. Aggregating public opinions may mean slightly less accurate election forecasts, which is acceptable.
  2. Polls dramatically overperformed expectations in the 2022 midterms, despite popular misconceptions.
  3. It's important to be cautious of biased pollsters and consider the methodology, credibility, and track record of pollsters before including their data in models.

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

Technology Made Simple β€’ 139 implied HN points β€’ 25 Apr 23
πŸ”¬ Science Statistics 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.

Gloves Off

The Radar β€’ 19 implied HN points β€’ 27 Dec 23
πŸ’Ό Business Leadership Talent Management Development Assessment Bias
  1. Old ideas and worn-out concepts in talent management must be identified and discarded to allow for genuine progress.
  2. Binary labels like 'hard skills vs soft skills' and 'introvert vs extrovert' are misleading and can hinder accurate talent assessment.
  3. The concept of 'high potential candidate' often introduces bias and leads to poor decision-making, hindering talent development and organizational growth.

Beware AI in the classroom

CIEO β€’ 78 implied HN points β€’ 11 Jul 23
🚌 Education Technology Bias Critical Thinking Learning Teaching
  1. AI in the classroom can provide benefits but also comes with costs, such as bias and misinformation.
  2. AI-generated responses may not always be accurate or politically neutral, reflecting biases of developers.
  3. To effectively judge AI responses, individuals need critical thinking skills and knowledge, and teachers play a crucial role in guiding young people.

A Case for Moderate IQ Skepticism

Tom Thought β€’ 19 implied HN points β€’ 31 Oct 23
πŸ”¬ Science Psychology Intelligence Measurement Bias
  1. Performance on cognitive tasks is correlated, so individuals who excel in one area tend to excel in others as well.
  2. IQ tests are useful in predicting various life outcomes, but it's important to recognize that they are not a direct measure of intelligence.
  3. It's crucial to be skeptical of assigning deep meaning to specific IQ scores, especially when comparing across different populations.
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Confirmation Bias: A Bayesian Interpretation

In My Tribe β€’ 1 HN point β€’ 28 Feb 24
🚌 Education Logic Bias Statistics Critical Thinking
  1. Having a strong prior belief is fine, but bias comes in when one refuses to consider evidence against that belief.
  2. Using Bayesian reasoning means weighing new evidence against what you believed before, termed your 'prior.'
  3. Bias occurs when someone puts a negative weight on new information, ignoring evidence that contradicts their prior beliefs.

Reassessing the Confirmation Bias

Optimally Irrational β€’ 11 implied HN points β€’ 14 Jun 23
🚌 Education Psychology Behavior Bias Decision-making
  1. Confirmation bias is a widely acknowledged cognitive bias where we tend to seek information that supports our existing beliefs.
  2. In today's world of political polarization, confirmation bias contributes to escalating tensions as people isolate themselves in echo chambers.
  3. Seeking confirmatory information aligns with an optimal information acquisition strategy, especially when considering costs and efficiency.

GPT is Rather Good at Feed Ranking

Messy Progress β€’ 3 HN points β€’ 07 Mar 23
πŸ•Ή Technology AI Ranking Bias
  1. GPT makes content-based feed ranking easy and has the potential to shift ranking power to users and groups.
  2. The ChatGPT API simplifies the process of creating content-based ranking models, making it more accessible and efficient.
  3. Using large language models like GPT to generate labels for training small models can lead to practical and cost-effective approaches in content-based ranking.

Artificial Intelligence: What to Worry About

Prompt Engineering β€’ 1 HN point β€’ 11 May 23
πŸ•Ή Technology Artificial Intelligence Misinformation Unemployment Bias Education
  1. AI advancements are fast and significant, leading to uncertainties about the future models of society.
  2. AI may result in mass unemployment, but historically, technology revolutions have not led to catastrophic unemployment levels.
  3. Challenges with AI include the misuse of data leading to bias, the potential for AI to outsmart humans, and the widening class divide due to unequal access to AI tools.

GPT Bias: A Challenge for Responsible AI

Rod’s Blog β€’ 0 implied HN points β€’ 27 Feb 24
πŸ•Ή Technology AI Bias Ethics Language Models Data
  1. GPT models can inherit and amplify biases from the data they are trained on, leading to negative impacts like misinformation and discrimination.
  2. GPT bias stems from both data bias (issues with the training data) and model bias (issues with the model design and architecture).
  3. There have been advancements in GPT models over the years, with newer versions like GPT-4 implementing techniques to reduce biases compared to earlier versions.

We'll never let go, until we do

Links I Would Gchat You If We Were Friends β€’ 0 implied HN points β€’ 29 Feb 16
πŸ•Ή Technology Privacy Bias Memes Artificial Intelligence
  1. The FBI wants access to our minds, not just our phones, according to the 'extended mind hypothesis.'
  2. Netflix recommendations show racial biases - defaulting to 'white' movies until you indicate preference for diversity.
  3. Mark Zuckerberg's grey T-shirt uniform is an unexpected lifestyle choice, suggesting simplicity and consistency.

Position bias in features

Simplicity is SOTA β€’ 0 implied HN points β€’ 12 Feb 24
πŸ”¬ Science Machine Learning Bias Features Ranking Simulation
  1. Position bias can affect the inputs of machine learning models when features reflect prior user behavior, leading to biased estimations of relevance.
  2. Using inverse propensity weighting (IPW) like IPW-CTR can help mitigate position bias in features, but it can result in high variance due to dividing by small numbers.
  3. The choice of weights to measure position bias is crucial, as observed click propensities may overestimate the bias, impacting the performance of features designed to address bias-variance trade-offs.

Platform Power and Platform Bias in the Music Industry

Platform Papers β€’ 0 implied HN points β€’ 16 Mar 22
🎢 Music Digital Platforms Playlists Music Industry Influence Bias
  1. Large digital platforms like Spotify can influence the success of songs and artists by controlling playlists and exposure.
  2. Appearing on Spotify's popular playlists can lead to significant increases in streams and commercial success for artists.
  3. While Spotify has the power to impact success, there are indications of bias favoring independent-label music and music by women, raising questions about fair treatment in the music industry.