Last year, Facebook created two chatbots and asked them to begin talking to each other, practicing their negotiation skills. The bots, it turns out, were pretty good at negotiating—but they did it using their own made-up language that was incomprehensible to humans.
This is where the world is going. Computers are creating content for each other, not us. Pictures are being taken by computers, for other computers to view and interpret. It's all happening quietly, often without our knowledge...
That’s a pretty amazing claim, don’t you think? It’s also a very annoying looking font but you can download it free so there is that. We’ve written here about font choices a number of times and it appears that the more you have to focus and concentrate to read a font (that disruption is called “creating a disfluency”), the more you will remember. So. This new font is called Sans Forgetica. No. We didn’t make that up.
The font was designed in Australia at RMIT University. The font...
Michael Woodford (Columbia University, Graduate School of Arts and Sciences, Department of Economics; National Bureau of Economic Research (NBER)) has posted Individualistic Welfare Analysis in the Age of Behavioral Science (Capitalism and Society: Vol. 13: Iss. 1, Article 3) on SSRN. Here is the abstract:
Experimental demonstration of systematic errors and biases in human choice behavior might seem to undermine the conceptual basis of the individualistic approach to welfare analysis, in which...
Aggressive incentive schemes that allow individuals to impose economic punishment on themselves if they fail to meet health goals present a promising approach for encouraging healthier behavior. However, the element of choice inherent in these schemes introduces concerns that only non-representative sectors of the population will select aggressive incentives, leaving value on the table for those who don’t opt-in. In a field experiment conducted over a 29-week period on individuals wearing Fitbit...
Blackjack happens to be the perfect Petri dish to remind ourselves about making better decisions. Data is easy to get, and systems never change. At this year’s conference, Jeffrey Ma, former VP of analytics and data science at Twitter and kingpin of the famous MIT blackjack team, shared his thoughts on the future of some of the new capabilities in analytics, arguing that “the biggest misconception is that AI is like magic and solves everything. In reality, it’s only going to be as good as the problems...
Previous research demonstrates that lawyers and law students are, on average, prone to overconfidence bias and self-serving judgments of fairness when they take on a representative lawyering role. This is the first study to investigate individual differences in susceptibility to these biases. Expanding on two previous experiments (Loewenstein, et al., 1993; Babcock, Loewenstein & Issacharoff, 1998), and utilizing as our sample 468 law students from twelve geographically diverse U.S. law schools,...
Our latest Freakonomics Radio episode is called “How to Optimize Your Apology.” (You can subscribe to the podcast at Apple Podcasts, Stitcher, or elsewhere, get the RSS feed, or listen via the media player above.)
You said, “I’m sorry,” but somehow you haven’t been forgiven. Why? Because you’re doing it wrong! A report from the front lines of apology science.
Below is a transcript of the episode, modified for your reading pleasure. For more information on the people and ideas...