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This is a fascinating and I think fun topic and I am hoping others will weigh in with their own experience, particularly as seen or experienced in engineering practice. I first became aware of this topic in the early 1990 when first exposed to the concept of decision quality (a future topic) and in particular the disabling role of anchoring.

As  a brief background, the notion of cognitive biases was first identified by Amos Tversky and Daniel Kahneman in work published in the early 1970s. The role cognitive biases play in everyday life has now become far ranging from Behavioral Economics to baseball's Sabermetrics. They are also also making their into engineering, e.g., February's free paper: Value of Information on Resilience Decision-Making in Repeated Disaster Environments.

Examples of cognitive biases - also referred to as heuristics - include:

• Anchoring - Why we tend to rely heavily upon the first piece of information we receive?
• Availability - Why do we tend to think that things that happened recently are more likely to happen again?
• IKEA effect - Why do we place disproportionately high value on things we helped to create?
• Representativeness  - Why do we use similarity to gauge statistical probability?

Finally, if you read and liked Michael Lewis' book Moneyball I highly recommend his follow up book the Undoing Project. The  provides the why behind former. There's also a nice article from the New Yorker The Two Friends Who Changed How We Think About How We Think that serves as a great intro to the overall subject of cognitive biases.

This is a fascinating and I think fun topic and I am hoping others will weigh in with their own experience, particularly as seen or experienced in engineering practice. I first became aware of this topic in the early 1990 when first exposed to the concept of decision quality (a future topic) and in particular the disabling role of anchoring.

As  a brief background, the notion of cognitive biases was first identified by Amos Tversky and Daniel Kahneman in work published in the early 1970s. The role cognitive biases play in everyday life has now become far ranging from Behavioral Economics to baseball's Sabermetrics. They are also also making their into engineering, e.g., February's free paper: Value of Information on Resilience Decision-Making in Repeated Disaster Environments.

Examples of cognitive biases - also referred to as heuristics - include:

• Anchoring - Why we tend to rely heavily upon the first piece of information we receive?
• Availability - Why do we tend to think that things that happened recently are more likely to happen again?
• IKEA effect - Why do we place disproportionately high value on things we helped to create?
• Representativeness  - Why do we use similarity to gauge statistical probability?

Finally, if you read and liked Michael Lewis' book Moneyball I highly recommend his follow up book the Undoing Project. The  provides the why behind former. There's also a nice article from the New Yorker The Two Friends Who Changed How We Think About How We Think that serves as a great intro to the overall subject of cognitive biases.

This is a fascinating and I think fun topic and I am hoping others will weigh in with their own experience, particularly as seen or experienced in engineering practice. I first became aware of this topic in the early 1990 when first exposed to the concept of decision quality (a future topic) and in particular the disabling role of anchoring.

As  a brief background, the notion of cognitive biases was first identified by Amos Tversky and Daniel Kahneman in work published in the early 1970s. The role cognitive biases play in everyday life has now become far ranging from Behavioral Economics to baseball's Sabermetrics. They are also also making their into engineering, e.g., February's free paper: Value of Information on Resilience Decision-Making in Repeated Disaster Environments.

Examples of cognitive biases - also referred to as heuristics - include:

• Anchoring - Why we tend to rely heavily upon the first piece of information we receive?
• Availability - Why do we tend to think that things that happened recently are more likely to happen again?
• IKEA effect - Why do we place disproportionately high value on things we helped to create?
• Representativeness  - Why do we use similarity to gauge statistical probability?

Finally, if you read and liked Michael Lewis' book Moneyball I highly recommend his follow up book the Undoing Project. The  provides the why behind former. There's also a nice article from the New Yorker The Two Friends Who Changed How We Think About How We Think that serves as a great intro to the overall subject of cognitive biases.