Wednesday, October 2, 2019

Word of the Day: cognitive bias

 
Word of the Day WhatIs.com
Daily updates on the latest technology terms | October 2, 2019
cognitive bias

Cognitive bias is a limitation in objective thinking that is caused by the tendency for the human brain to perceive information through a filter of personal experience and preferences. The filtering process is called heuristics; it's a coping mechanism that allows the brain to prioritize and process the vast amount of input it receives each second. While the mechanism is very effective, its limitations can cause errors that can be exploited.

It may not be totally possible to eliminate the brain's predisposition to take shortcuts, but understanding that bias exists can be useful when making decisions. A continually evolving list of cognitive biases has been identified over the last six decades of research on human judgment and decision-making in cognitive science, social psychology and behavioral economics. They include:

Anchoring effect - the tendency for the brain to rely too much on the first instance of information it received when making decisions later on.

 

Availability bias - the tendency for the brain to conclude that a known instance is more representative of the whole than is actually the case.

 

Bandwagon effect - the tendency for the brain to conclude that something must be desirable because other people desire it.

 

Bias blind spot - the tendency for the brain to recognize another's bias but not its own.

 

Clustering illusion - the tendency for the brain to want to see a pattern in what is actually a random sequence of numbers or events.

 

Confirmation bias - the tendency for the brain to value new information that supports existing ideas.

 

Framing effect - the tendency of the brain to arrive at different conclusions when reviewing the same information depending upon how the information is presented.

 

Group think - the tendency for the brain to place value on consensus.

 

Negativity bias - the tendency for the brain to subconsciously place more significance on negative events than positive ones. This bias probably evolved as a survival technique. Assuming the worst of a situation that turns out not to be dangerous is much safer than not expecting danger that turns out to be present.

 

Recency bias - the tendency for the brain to subconsciously place more value on the last information it received about a topic.

 

Sunk cost effect - the tendency for the brain to continue investing in something that clearly isn't working in order to avoid failure.

 

Survivorship bias - the tendency for the brain to focus on positive outcomes in favor of negative ones. A related phenomenon is the ostrich effect, in which people metaphorically bury their heads in the sand to avoid bad news.

Cognitive bias and its impact on data analytics

Being aware of how human bias can cloud analytics analysis is an important first step toward preventing it from happening. While data analytics tools can help business executives make data-driven decisions, it is still up to humans to select what data should be analyzed. This is why it is important for business managers to understand that cognitive biases that occur when selecting data can cause digital tools used in predictive analytics and prescriptive analytics to generate false results.

Throughout history, analysts have learned the hard way about the pitfalls of deploying and using predictive modeling without examining the data selected for analysis for cognitive bias. For example, pollsters and election forecasters predicted large margins of victory for Hillary Clinton in the 2016 United States presidential election. The culmination of many types of bias played a part in predictions that inaccurately forecast Hillary Clinton would be elected president and reliance on weak polling data and flawed predictive models resulted in an unpredicted outcome.

Quote of the Day

 
"Analytics can help businesses make data-driven decisions, but common cognitive biases can skew how the information is interpreted." - Scott Robinson

Learning Center

 

Data science storytelling emerges as top analytics skill
Data science storytelling isn't the most technical aspect of advanced analytics, but it is one of the most important skills for data scientists to possess. Read on to see why it's so important.

Common biases that can taint analytics analysis
Businesses are increasingly using data to drive decisions, but these common biases can still muddle analytics analysis.

Interview: Innovating with data science
Amadeus's head of data science for innovation, Baptiste Chatrain, discusses his GitHub page and how the business innovates with data.

Big data throws bias in machine learning data sets
Data bias in machine learning data sets is a big problem for AI, and correcting it is no small feat.

Software testing techniques: Overcoming biases
Expert Gerie Owen offers software testing techniques to help overcome biases and boost code quality and answers the pressing question: 'How did I miss that bug?'

Quiz Yourself

 
A cursory ________ of the document was enough to reveal that the discrepancy in amounts resulted from an accounting error rather than fraud.
a. review
b. scrutiny

Answer

Stay in Touch

 
For feedback about any of our definitions or to suggest a new definition, please contact me at: mrouse@techtarget.com

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