Liking/Loving Tendency
Munger argues that we are wired to naturally favor people we like and love to the point of irrationality. In social psychology, this tendency is known as in-group bias. In order to keep liking and loving them, we do the
Influence Yourself
By understanding what really drives you, you can drive yourself. Source: Michael Simmons & Ian Chew
Protect Yourself From Bad Advice.
Munger cautions us to be careful of professional advice that might be shaped by the advisor’s personal interest. Source: Michael Simmons & Ian Chew
Reward & Punishment Superresponse Tendency
Want to get an individual or a team to do something? Munger says you need to answer this question correctly: “What’s in it for them?” Source: Michael Simmons & Ian Chew
Godwin’s Law
“If an online discussion (regardless of topic or scope) goes on long enough, sooner or later someone will compare someone or something to Hitler or Nazism.” (related: “Take the high road.”, “Rise above the fray.”, “Don’t stoop down to their
Micropayment
“A financial transaction involving a very small sum of money and usually one that occurs online.” Source: Gabriel Weinberg's Mental Models I Find Repeatedly Useful
Content Farm
“large amounts of textual content which is specifically designed to satisfy algorithms for maximal retrieval by automated search engines.” (related: click farm — “where a large group of low-paid workers are hired to click on paid advertising links for the
Spamming
“The use of electronic messaging systems to send unsolicited messages (spam), especially advertising, as well as sending messages repeatedly on the same site.” (related: phishing — “the attempt to acquire sensitive information such as usernames, passwords, and credit card details
Botnet
“A number of Internet-connected computers communicating with other similar machines in which components located on networked computers communicate and coordinate their actions by command and control (C&C) or by passing messages to one another.” (related: flash mob) Source: Gabriel Weinberg's
Filter Bubble
“In which a website algorithm selectively guesses what information a user would like to see based on information about the user (such as location, past click behavior and search history) and, as a result, users become separated from information that