#bias
Explore Books, Authors and Common Highlights on Bias
Showing 50 of 50 highlights
Understanding cognitive biases is crucial for improving the quality of analysis.
From The Psychology of Intelligence Analysis by Richards J. Heuer Jr.
We are not designed to be impartial, objective, or rational.
From The Righteous Mind by Jonathan Haidt
Bias is often unconscious, making it all the more challenging to address.
From The Fix: Overcome the Invisible Barriers That Are Holding Women Back at Work by Michelle P. King
We often miss the obvious because we are blinded by our biases.
Machines learn from data, but the data can reflect biases and errors present in society.
From The Alignment Problem by Brian Christian
Algorithms are not neutral — they reflect the biases of their creators.
The bias-variance tradeoff is a central concept in machine learning.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Understand your biases and you will understand your decisions.
From Seeking Wisdom by Peter Bevelin
Anchoring effects are strong and persistent.
Bias and noise are two different problems that require different solutions.
From Noise: A Flaw in Human Judgment by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
What you see is all there is.
Expertise does not always guarantee accuracy.
From Noise: A Flaw in Human Judgment by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
Skepticism is a valuable tool for ensuring we don’t fall prey to our biases.
From The Scout Mindset by Julia Galef
To think critically is to be aware of our own biases and to engage in self-reflection.
From The Psychology of Intelligence Analysis by Richards J. Heuer Jr.
The more we analyze, the more we realize our uncertainty.
From Noise: A Flaw in Human Judgment by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
We are prone to overestimate how much we understand about the world and to underestimate the role of chance in events.
We need to recognize the limits of our intuition.
From Noise: A Flaw in Human Judgment by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
We tend to overvalue what we have and undervalue what we don’t.
From Predictably Irrational by Dan Ariely
What we see is all there is.
From The Black Swan by Nassim Nicholas Taleb
People tend to be overconfident in their judgments.
Unconscious bias affects decisions at every level of the organization.
From The Fix: Overcome the Invisible Barriers That Are Holding Women Back at Work by Michelle P. King
We must be aware of the biases that cloud our judgment.
From The Changing World Order by Ray Dalio
Understanding the biases in our predictions is crucial for improvement.
From Power and Prediction by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
A lot of people think they are rational but they are just not aware of their biases.
The context in which we make decisions can significantly alter our choices.
From Predictably Irrational by Dan Ariely
Many people believe they can predict the future based on past events.
From The Drunkard's Walk by Leonard Mlodinow
We often rely on mental shortcuts, which can lead us astray.
From Predictably Irrational by Dan Ariely
Humans are not as rational as they think they are.
From Noise: A Flaw in Human Judgment by Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein
The way we choose to frame a problem can lead us to make different decisions.
From Predictably Irrational by Dan Ariely
The law of small numbers is a form of overconfidence.
Cognitive biases are the mind's way of shortcutting reasoning, often leading to errors.
Understanding cognitive biases is crucial for better decision-making.
From Super Thinking: The Big Book of Mental Models by Gabriel Weinberg and Lauren McCann
When we are faced with a choice, we often rely on the default option.
From Predictably Irrational by Dan Ariely
Anchoring effects are pervasive and powerful.
Expertise is not a guarantee of accuracy.
The biases in our data are the biases in ourselves.
From The Big Nine by Amy Webb
People have a tendency to believe what they want to believe.
Recognizing our biases is the first step towards making better choices.
The lack of transparency in algorithms allows bias to thrive.
Algorithms are not neutral; they carry the biases of their creators.
From Atlas of AI by Kate Crawford
Analysts must understand their own cognitive biases.
From The Psychology of Intelligence Analysis by Richards J. Heuer Jr.
Acknowledging our biases is the first step to overcoming them.
From The Elephant in the Brain by Kevin Simler and Robin Hanson
We are prone to overestimate our understanding of the world.
From The Black Swan by Nassim Nicholas Taleb
To think clearly, you must first identify your biases.
Intuitive judgments are often wrong, but they are often made with confidence.
The ease with which we retrieve information influences our perception of frequency.
Data-driven decisions can exacerbate existing biases rather than eliminate them.
We often forget that AI is a reflection of our own biases and limitations.
We can be blind to the obvious, and we are also blind to our blindness.
We often think we are more rational than we actually are.
From The Righteous Mind by Jonathan Haidt