Author Archives: alee9

The Identifiable Victim Effect & Rational Helping

What inspires you to help? You’re certainly more motivated to contribute to causes which hold some particular significance to you, or which are connected to you in some meaningful way. You are also more likely to take action when you feel a sense of personal responsibility and you are provided with the resources necessary to make a difference. We like to think that, when we put our time, effort, and money towards something that we are doing so rationally. But are we?

Around a year back, the story of a group of young boys trapped in an underwater cave in Thailand received international attention and feverish round-the-clock coverage from global news media for nearly three weeks. Volunteer divers and specialists from around the world were flown in to help with the massive rescue effort. Story rights were bought to make a movie about the incident, with filming for The Cave apparently in production at the time of this post.

We might correctly praise the Thai cave rescue as an admirable example of human empathy, or of good people rising to the occasion to save lives, but it is also a prime example of the identifiable victim effect (IVE), whereby people contribute disproportionately to causes which feature a distinct beneficiary rather than an equal (or even greater) number of anonymous or statistical victims. According to a meta-analytic review by Seyoung Lee and Thomas Hugh Feeley, a major component of the IVE lies in the emotional response invoked, as observers are able to make genuine, sympathetic connections to, say, a child living on the street compared to the statistic that an estimated 2.5 million children in the US are homeless at any given time. Similarly, specificity also tends to imply greater perceived impact and responsibility, as volunteers will only stand to receive tangible outcomes on the individual level, finding a home for one identified child or seeing the twelve boys successfully brought to safety.

There are several mitigating factors which are worth noting at this point. For one, according to Lee and Feeley, the effect is strongest with a single individual, with a precipitous decline that tends to exclude groups from benefiting, making the cave rescue a rare case. They also found that the effect size tends to be conventionally small, though it is still significant enough to be of consideration in practical applications. Additionally, according to analysis by Tehila Kogut, only certain types of victims can be expected to gain from the IVE as a function of perceived responsibility for their condition. For example, individual children living in poverty or victims of uncontrollable circumstances like cancer or natural disasters are prime examples. On the other hand, homeless adults are much less likely to receive assistance under the same isolation, as they are then subject to other social judgments as being potentially to blame for their situation. This can also be seen in our example, where international support was given to the twelve boys, but less so to the assistant coach, who had guided the boys’ trip into the cave and was accused of negligence for placing them at risk despite minimal evidence to support this viewpoint.

Another study by Karen E. Jenni and George Loewenstein from 1997 systematically examined a few suggested contributing elements and concluded that the biggest factor they examined with the above considerations in mind was certainty. In the case of an identified victim or (less frequently) a group, there is an exact number of people at risk, whereas larger statistical risk groups lack this exactness. Jenni and Loewenstein inferred that there is an unconscious heuristic which gives preference to risks characterized by certainty over probabilistic risks. They argued that the effect could better be described for the percentage of potential victims which could be saved if action is taken, where the identified victim(s) form a mental reference group for themselves of which a much larger percentage can be saved. By contrast, significant effects were not found for the vividness of presentation and whether the presentation comes before or after the risk occurs.

So what does this tell us about helping behavior? First, as with many heuristics identified in cognitive psychology, the identified victim effect serves a practical purpose in simplifying the world around us, but leads to ‘irrational’ behavior in the victims we choose to prioritize when offering aid. Second, while the IVE does not occur in a vacuum and research shows that it is one of many factors at play in prosocial decision-making, it is arguably still useful for charity organizations to include identified victims on their donations pages. Lastly, it is important to be cognizant of the ways in which the heuristic is applied to sway public attitudes in the real world. We’ve seen that it can be used to draw attention to important issues, as with the Clery Act, a campus crime disclosure statute named for a college student who was raped and murdered in her residence hall. In other cases though, anecdotes about isolated victims can be used to draw attention away from larger statistical arguments in public policy debates, as with individual workers at risk of losing the jobs in trade deals which will create a greater number of statistical jobs.

The Planning Fallacy: When the Hourglass is Half Full

Sometime in the middle of my freshman year, at the advice of a friend, I took a walk to the local dollar store and bought myself a calendar style daily planner. For years before then, I had relied entirely on a to-do list on my phone, adding and removing obligations as needed. It turned out to be a major improvement; I missed significantly fewer deadlines and it gave me the opportunity to get a general idea of what to expect from each coming week. Naturally, at the beginning of my sophomore year, I decided to take the next logical step and start scheduling hour-by-hour, at which point I promptly lost all the progress I had made. The problem was that, even when I added ‘buffer time’ to compensate, I still found myself underestimating the time I needed for anything that didn’t have a built in beginning and end, like classes and meetings.

Even this blog post was underestimated. A few days ago, I told myself I could definitely start and finish on Saturday night, leaving myself all of Sunday night to study for my exam at noon on Monday. How did things go so wrong? We might begin to answer that question by considering this explanation from a paper on intuitive prediction by Daniel Kahneman and Amos Tversky, which distinguishes between singular and distributional data. The former, according to the authors, is based on the various factors which characterize a scenario, while the latter is based on comparisons with other similar scenarios. In other words, as applied to homework, a singular approach might be based on the time needed to choose a topic, conduct my research, pull useful information from my sources, and so on. A distributional approach, by contrast, would draw on my prior experience in similar assignments (including the last two blog posts), as well as any information I happen to have about how long it takes my peers.

Kahneman and Tversky identify the over-reliance on internal models (singular data) as the primary component of what they called ‘the planning fallacy’. Even disregarding the complementary effects of wishful thinking, it seems that even experts tend to create unreasonable time estimates based on a preference for internal rationalizations. The article reasons that external (distributional) assessments tend to yield more accurate results because they account for the multitude of possible complications which would otherwise be unaccounted for on the basis of individual improbability.

A research paper from 1994 by Buehler, Griffin, and Ross built on this dichotomy. Their first two studies concerned the completion of an Honors Thesis project and either an academic or personal task, respectively. Earlier predictions were correlated with earlier completion times but, in all cases, participants took consistently longer than they had planned despite reporting high levels of confidence in their numbers and even when asked to give a pessimistic estimate. In fact, the best predictor available turned out to be the externally established deadline for a project’s completion, although time-to-deadline was shown to have minimal influence on estimation.

The third study in the same paper asked participants to reason aloud while making their predictions, showing that future plans are disproportionately favored over all other considerations, although this study failed to support the researchers’ hypothesis that those who favored past experiences would generate more accurate estimates. However, the subsequent study was able to improve guesses under the specific case in which subjects were not only asked to consider similar past experiences, but were also forced to describe how said experiences were relevant to the future they were planning for.

Perhaps most interesting was the fifth and final study, in which observers were brought in and asked to make their own independent estimates for other participants after being given necessary information about the person they were assessing and the parameters of the project. These social predictions were consistently more conservative, with a day and a half on average more time given for one-week deadlines and over four days greater for two-week deadlines when compared to the individual predictions of those actually performing the task. Observers, as predicted, were more likely to use impersonal distributional data and were thus more accurate, just as with the prior task in which subjects were manipulated to relate their plans to past actions.

So what can we do differently to improve planning in our own lives? First, it is important to consider the task at hand in relation to similar tasks from past experience, which requires overcoming the mental bias towards viewing past complications as relatively externally caused and unique. Try to find ways in which the upcoming situation is specifically similar to what you already know about yourself and others, which will help to decrease the effects of over-optimism. Perhaps an even more practical approach is to outsource the planning entirely and enlist your friends to help. Due to their external perspective, they are far more likely to make estimates which prioritize their general knowledge over your best intentions, which leads to more realistic expectations.

Weapon Focus & Witness Reliability

When discussing the reliability of memory, one will frequently come across the research of Elizabeth Loftus, who has written extensively on the tendency for misinformation presented after the fact to distort the accuracy of later recall. A sample case presented in this summary by Loftus of memory distortion references multiple studies in which participants who were shown a video of a car accident can be misled to report having seen a yield sign when, in fact, there was a stop sign instead. This occurs because, in the window of time between the experience of an event and its retrieval from long-term memory, the witness is vulnerable to receiving new information about the event and incorporating that into their understanding of what actually happened. It is beneficial, of course, when the brain is given accurate feedback that helps it to contextualize and fill in details that may have been missed or partially forgotten, but it also leaves the door open for false memories. The process of recall is, to quote, ‘a highly constructive activity that gathers bits and pieces from other sources’, and it is precisely this activity that researchers are able to manipulate to ‘create’ the non-existent yield sign or, in perhaps a more popular example, increase participants’ estimates of a car’s speed in hindsight of an observed crash with leading questions and biased language.

Overall, Loftus identified a number of factors which influenced the likelihood of creating false memories, to include how long ago the event occurred, the age of the subject, the way that post-event information is presented, and certain elements of the nature of the event itself. This research has contributed appreciably to the treatment of eyewitness accounts in the judicial system as we now have a greater awareness of people’s tendencies to believe in and testify on memories that turn out to be counterfactual. For this entry, I intend to focus on a specific type of memory distortion known as weapon focus, which was also researched by Loftus. In essence, it is a tendency also connected to inattentional blindness in which someone who has witnessed a crime involving a weapon will vividly remember the weapon itself but may struggle to bring back other relevant information from the scene.

A 1987 research study by Loftus, Loftus, and Messo provided the first empirical evidence for weapon focus with an experiment in which subjects were shown a given set of eighteen slides in rapid succession. There were two possible scenes of an interaction between a cashier and a customer which were nearly identical, save for four slides in which the customer either presents a check to pay for a purchase or pulls a gun and is given money. The first piece of evidence came from eye movement tracking, where observers in the gun condition showed consistently more visual fixations on the gun and held their gaze for longer by comparison to subjects in the check condition. This should not be considered remarkable in and of itself; it’s hardly a stretch to assume that a gun would draw greater attention than something as contextually mundane as a paper check. The more compelling finding is that, when compared to the check condition, the gun had a significant negative impact on a viewer’s subsequent performance questions about the scene, and they were only able to correctly identify the actor from their scene 15% of the time from a twelve person line-up, compared to 35% in the control group. This shows that, contrary to popular belief, heightened awareness alone does not necessarily aid in better future recall. This result is consistent with other research into inattentional blindness, where unattended items in an individual’s visual field can be excluded from conscious processing despite being fully in view.

With discussion on this effect, the authors note that there are multiple potential explanations. In a 2007 study by Lorraine Hope and Daniel Wright, it was found that one key factor may be the emergence of unexpected stimuli. Hope and Wright provided volunteers with a similar scene to the previously mentioned study, but this time the man could be holding either a gun, an ordinary wallet, or a brightly colored feather duster, which is notably unusual but also non-threatening. Here, the unusual object condition showed comparable mental processing demand for subjects, although participants in the weapon condition still performed worse in contrast to the other two groups on both accuracy and confidence of recall for aspects of the scene not directly related to the object itself.

Another study by Kerri Pickel offers two more experiments related to context in which a gun is presented either at a baseball field or at a shooting range, then held either by a police officer or by a priest. In both trials, the weapon effect was only demonstrated in cases where a gun was unexpected and not when the presence of a gun could be reasonably anticipated based on prior knowledge. Importantly, when participants were asked to provide a qualitative threat assessment to the scene they viewed, there was no statistically significant impact of higher threat levels on the effects of weapon focus. In combination with the aforementioned study, it would seem that the context hypothesis is better supported by academic literature on the subject, although, with regards to the former, it may not be the only contributing factor. Other general attributes of unreliable witness memory, as discussed at the top of this post, are also considered likely contributors to the phenomenon.

Speed Reading & Subvocalization

The accompanying article comes from Iris Reading, LLC, an online company which offers classes in speed reading, which they claim helps you ‘read faster, remember more, and boost your overall productivity’. In the article, they claim that the mental process of subvocalization, which was discussed in Chapter One lectures and in the textbook, limits reading speed to an average of 150 to 250 wpm depending on the person by forcing the reader to ‘say’ each word in their head. The key to reading faster is then, according to Iris, suppressing subvocalization, for which they provided five tips.


Now, before addressing that proposal, it would be good to review the concepts in play. According to the textbook, subvocalization is ‘silent speech’ which can be utilized in the production of a phonological buffer, which is an internal auditory representation of the words on the page. It only lasts for a brief time, but it’s an important part of the working memory system, which in turn will feed into your long-term memory of whatever it is you’re reading.

The concurrent articulation task study we discussed in class becomes relevant at this point. In the experiment, a subject is asked to memorize a sequence of numbers or letters (a span task) while simultaneously repeating a simple sound. It turns out that the subject’s ability to recall longer sequences is negatively impacted when compared to their performance in ordinary silent span tests. This result demonstrates that the mental systems required for overt speech are the same mechanisms behind the phenomenon of subvocalization. Thus, when they are already occupied, the so-called ‘inner voice’ is suppressed, throwing off the brain’s internal rehearsal loop. For our purposes, the other important takeaway is that inhibiting subvocalization, at least in this case, seems to have a significantly detrimental effect on memory, suggesting a potential major drawback for the speed reading tips advocated for by the article.


So what exactly does the article advise? One of the tips involves a method similar to the conditions of the concurrent articulation task, repeating ‘one, two, three’ repeatedly with the express intention of preventing yourself from saying the words you read in your head. Three more are tips that force you to read faster – by guiding your eyes with your hand, with a rapid presentation reading app, and simply by forcing yourself to take less time on each line – in order to avoid subvocalizing so many of the words. The last tip is to listen to music to help you concentrate, which supposedly helps to minimize the ‘habit’ of subvocalization.

If what we learned about the working memory applies, it would seem that what is really being offered here is training in skimming text, which, while perhaps efficient for quickly gathering key points, is going to minimize actual learning of information in the process. This seems to be backed by recent research on the subject; a 2016 study ( which reviewed the efficacy of speed-reading techniques similar to those listed in the Iris Reading article states that there is a trade-off between speed and accuracy such that trying to read much faster than one’s natural pace is likely to prevent desirable comprehension of the text. Instead, Rayner et al. suggests that the best way to increase reading speed without sacrificing understanding is to focus on your linguistic abilities directly, improving things like your vocabulary instead of trying fighting subvocalization, an essential part of reading.

Test Post

My name is Alexander Lee, I’m a sophomore planning to double major in psychology and political science, and this is my test post with a photo from the UC.