Data Skeptic15 Jan 2016

Detecting Pseudo-profound BS

A recent paper in the journal of Judgment and Decision Making titled On the reception and detection of pseudo-profound bullshit explores empirical questions around a reader's ability to detect statements which may sound profound but are actually a collection of buzzwords that fail to contain adequate meaning or truth. These statements are definitively different from lies and nonesense, as we discuss in the episode.

This paper proposes the Bullshit Receptivity scale (BSR) and empirically demonstrates that it correlates with existing metrics like the Cognitive Reflection Test, building confidence that this can be a useful, repeatable, empirical measure of a person's ability to detect pseudo-profound statements as being different from genuinely profound statements. Additionally, the correlative results provide some insight into possible root causes for why individuals might find great profundity in these statements based on other beliefs or cognitive measures.

The paper's lead author Gordon Pennycook joins me to discuss this study's results.

If you'd like some examples of pseudo-profound bullshit, you can randomly generate some based on Deepak Chopra's twitter feed.

To read other work from Gordon, check out his Google Scholar page and find him on twitter via @GordonPennycook.

And just for fun, if you think you've dreamed up a Data Skeptic related pseudo-profound bullshit statement, tweet it with hashtag #pseudoprofound. If I see an especially clever or humorous one, I might want to send you a free Data Skeptic sticker.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(601)

Measuring Web Search Behavior

On the show, Aleksandra Urman and Mykola Makhortykh join us to discuss their work on the comparative analysis of web search behavior using web tracking data. They shared interesting results from their...

21 Nov 202236min

StrategyQA and Big Bench

Did Aristotle Use a Laptop? That's a question from the StrategyQA benchmark which highlights the stretch goals for current artificial intelligence systems. Answering a question like that requires se...

18 Nov 202241min

Ad Blockers Effect on News Consumption

While at first glance, the use of ad blockers drops the revenue of news publishers, this may not be completely true. On the show today, Shunyao Yan, an Assistant Professor in Marketing at Leavey Schoo...

14 Nov 202238min

Your Consent is Worth 75 Euros a Year

People who do not want their data tracked and shared online can pay a token for a cookie paywall. But are the websites keeping to their side of the bargain? Victor Morel, a Postdoc candidate at the Ch...

7 Nov 202224min

Automated Email Generation for Targeted Attacks

The advancement of generative language models has been a force for good, but also for evil. On the show, Avisha Das, a post-doctoral scholar at the University of Texas Health Center, joins us to discu...

31 Okt 202245min

Tribal Marketing

Peter Gloor, a Research Scientist at the MIT Center for Collective Intelligence, takes us on a new world of tribe classification. He extensively discussed the need for such classification on the inter...

24 Okt 202237min

Nano-targetted Facebook Ads

17 Okt 202244min

Debiasing GPT-3 Job Ads

We hear about the impeccable achievements of GPT-3 models, but such large generative models come with their bias. On the show today, Conrad Borchers, a Ph.D. student in Human-Computer Interaction, joi...

10 Okt 202248min