Blank Slate: From effortful to automatic
Blank Slate automates recall
Imagine being at a work event and someone asks you about your latest project. Without hesitation, you deliver a detailed, polished explanation. No scrambling for words, no second-guessing, just smooth, confident communication. That’s the power of automatic recall — when information is so well-practiced that it feels second nature to recall it.
While automatic recall is a “nice to have” capability at a work event, it’s often a “need to have” capability for people who work in high-risk environments like law enforcement, security, and national defense. That’s exactly why people in these sectors turn to Blank Slate: to automate workforce knowledge and reduce workplace risk.
Today we want to show you what it actually looks like when Blank Slate transforms knowledge from effortful to automatic.
We took a look at 111 security officers who currently use Blank Slate to support their knowledge of over 100 workplace protocols. As an example of these protocols, one of their questions asks them to recall the specific circumstances under which a screening officer is permitted to touch a visitor’s personal belongings.
For knowledge to become automatic, two things need to happen: knowledge recall needs to be accurate and fast. To demonstrate how Blank Slate accomplishes this over time, we therefore looked at security officers’ accuracy and speed as they answered the same questions again and again.
As you can see in the (unbelievably symmetrical) graph above, by the time security officers had viewed the same Blank Slate questions six times, their accuracy on those questions was quite high and they were answering those questions much faster than when they started. These two patterns–increasing accuracy and decreasing speed–are hallmark indicators of automatic recall.
Blank Slate ensures reliable recall
These data also provide an opportunity to address another common concern we hear from Blank Slate’s clients: whether users can game the system by memorizing surface-level features of questions rather than truly understanding the content. This would undermine the purpose of Blank Slate, where the goal is genuine knowledge retention.
To address this question, we looked at the average time security officers took to answer questions after numerous exposures. If officers were just skimming for familiar patterns, response times would be very short.
Our data suggest this was not the case. After six attempts at each question, the average response time was still about 13 seconds. Given the average length of questions and answer choices (about 39 words) and a typical reading speed of 238 words per minute, it’s estimated that fully reading and processing each question should take approximately 10 seconds. Tacking on a few extra seconds for choosing the correct answer, the 13-second response time indicates that officers were indeed reading and comprehending each question, not merely recognizing patterns.
The method behind the success
When you know how Blank Slate works, it’s not surprising that people still have to read their Blank Slate questions each time they see them. Blank Slate’s approach to knowledge reinforcement relies on a machine learning algorithm that adjusts the frequency of question repetition. After users answer a question correctly a few times, the platform begins to space out the viewings over several days, weeks, and eventually months. This strategic interval ensures that users see their questions often enough to retain the correct answers but, conveniently, not often enough to recall surface-level clues that could lead to rote memorization.
References
Brysbaert, M. (2019). How many words do we read per minute? A review and meta-analysis of reading rate. Journal of Memory and Language, 109, 104047-. https://doi.org/10.1016/j.jml.2019.104047
Racsmány, M., Szőllősi, Á., & Bencze, D. (2018). Retrieval practice makes procedure from remembering: An automatization account of the testing effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(1), 157–166. https://doi.org/10.1037/xlm0000423
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Amy Smith, PhD
Chief Scientist, Blank Slate Technologies
