Availability Bias

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Have you ever said something like, “I know that [insert a generic statement here] because [insert one single example].” For example, someone might say, “You can’t get fat from drinking beer, because Bob drinks a lot of it, and he’s thin.” If you have, then you’ve suffered from availability bias. You are trying to make sense of the world with limited data.

People naturally tend to base decisions on information that is already available to us or things we hear about often without looking at alternatives that might be useful. As a result, we limit ourselves to a very specific subset of information.

This happens often in the data science world. Data scientists tend to get and work on data that’s easier to obtain rather than looking for data that is harder to gather but might be more useful. We make do with models that we understand and that are available to us in a neat package rather than something more suitable for the problem at hand but much more difficult to come by.

A way to overcome availability bias in data science is to broaden our horizons. Commit to lifelong learning. Read. A lot. About everything. Then read some more. Meet new people. Discuss your work with other data scientists at work or in online forums. Be more open to suggestions about changes that you may have to take in your approach. By opening yourself up to new information and ideas, you can make sure that you’re less likely to work with incomplete information.

Rahul Agarwal writing in Built in

 

The best advice I ever got

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The advice that sticks out I got from John Door, who in 2001 said, “My advice to you is to have a coach.” 

My argument was, How could a coach advise me if I’m the best person in the world at this?  But that’s not what a coach does. The coach doesn’t have to play the sport as well as you do. They have to watch you and get you to do your best. 

Former Google CEO Eric Schmidt quoted in Fortune Magazine

 

What know-it-alls don’t know

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Know-it-alls can be insufferable, and now there’s new evidence that they know less than they’d have you believe. Researchers from Cornell and Tulane universities found that self-proclaimed experts are more prone to “overclaiming”—essentially, pretending to have extensive knowledge of something they’re clueless about. In the study, 100 volunteers were asked to rate their level of knowledge in various subjects, such as biology, literature, and personal finance. When quizzed on 15 different economic terms, the people who fancied themselves financial gurus were far more likely to claim they were familiar with phenomena such as “pre-rated stocks” and “fixed-rate deduction” that were actually complete fictions. Tests on the other topics revealed similar results—even when participants were warned that some terms would be phony. “Our work suggests that the seemingly straightforward task of judging one’s knowledge may not be so simple,” researcher Stav Atir tells Science Daily, “particularly for individuals who believe they have a relatively high level of knowledge to begin with.”

The Week Magazine, August 7, 2015

Try Doing Less 

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When you stop doing the things that make you feel busy but aren’t getting you results (and are draining you of energy), then you end up with more than enough time for what matters and a sense of peace and spaciousness that constant activity has kept outside your reach. We need to identify what not to do. But this determination can’t be random. It must be methodical and evidence-based. For instance, if you’re looking to connect more with your children, you might list a few specific memories or “wins” when you really felt like you were being the best parent you could.

Often the things we think we “must” do are simply because we always have done them or others around us do them and we think we should, too.

Kate Northrup writing in the Harvard Business Review

 

Why Video Conferencing is Exhausting

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Video chats mean we need to work harder to process non-verbal cues like facial expressions, the tone and pitch of the voice, and body language; paying more attention to these consumes a lot of energy. “Our minds are together when our bodies feel we're not. That dissonance, which causes people to have conflicting feelings, is exhausting. You cannot relax into the conversation naturally,” according to Gianpiero Petriglieri.

Silence is another challenge, he adds. “Silence creates a natural rhythm in a real-life conversation. However, when it happens in a video call, you became anxious about the technology.” It also makes people uncomfortable. Even delays of 1.2 seconds made people perceive the responder as less friendly or focused.

An added factor—we are very aware of being watched. You are on stage, so there comes the social pressure and feeling like you need to perform. Being performative is nerve-wracking and more stressful. It’s also very hard for people not to look at their own face if they can see it on screen, or not to be conscious of how they behave in front of the camera.

Read more from the BBC

 

 

unduly influenced by outside suggestion

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Referees favour home teams in judgment calls, particularly those that happen at a crucial stage in a game. If a batter chooses not to swing at a baseball pitch, the pitch is more likely to be called a strike if the home team is pitching. This tendency is most extreme in close games. In soccer, referees are more likely to award penalties to the home team, hand out fewer punishments for offences to home players.

Are referees deliberately biased? The authors (of Scorecasting) think not. Instead, they blame the fact that referees, like the rest of us, tend subconsciously to rely on crowdsourcing, picking up on the mood of the crowd when making their decision.

“Anchoring” is the name economists give to people’s tendency to be unduly influenced by outside suggestion. Take away the crowd and the home bias shrinks, as it did a few years back when 21 Italian soccer matches were played without supporters following incidents of crowd violence. In these games the home bias declined by 23% on fouls called, by 26% for yellow cards and by a remarkable 70% for red cards, which remove a player from the game and have a particularly big impact on the result.

From The Referee's an Anchor in The Economist