When feedback backfires: Knowledge of results can impair cognitive strategy choice.

Frequently, problems can be solved in more than one way. In modern computerised environments, more ways than ever exist. Naturally, human problem solvers do not always decide for the best-performing strategy available. One underlying reason might be the inability to continuously and correctly monitor each strategy's performance. Here, we supported some of our participants' monitoring ability by providing written feedback regarding their speed and accuracy. Specifically, participants engaged in an object comparison task, which they were asked to solve with one of two strategies: an internal strategy (mental rotation) or an extended strategy (manual rotation). After receiving no feedback (30 participants), trialwise feedback (30 participants), or blockwise feedback (30 participants) in these no choice trials, all participants were asked to estimate their performance with both strategies and were then allowed to freely choose between strategies in choice trials. Results indicated that written feedback improves explicit performance estimates. However, results also indicated that such increased awareness does not guarantee improved strategy choice and that attending to written feedback might tamper with more adaptive ways inform the choice. Thus, we advise against prematurely implementing written feedback. While it might support adaptive strategy choice in certain environments, it did not in the present setup. We encourage further research that improves the understanding of how we monitor the performance of different cognitive strategies. Such understanding will help create interventions that support human problem solvers in making better choices in the future.

Is precrastination related to updating and inhibition aspects of executive function?

ABSTRACTPrecrastination is the act of completing a task as soon as possible even at the expense of extra effort. Past research has suggested that individuals precrastinate due to a desire to reduce their cognitive load, also known as the cognitive load-reduction (CLEAR) hypothesis [VonderHaar, R. L., McBride, D. M., & Rosenbaum, D. A. (2019). Task order choices in cognitive and perceptual-motor tasks: The cognitive-load-reduction (CLEAR) hypothesis. Attention, Perception, & Psychophysics, 81(7), 2517-2525. https://doi.org/10.3758/s13414-019-01754-z]. This idea stems from the notion that it is taxing to hold intentions in working memory and completing a task as soon as possible releases cognitive resources for other tasks. Based on this hypothesis, we predicted that aspects of executive function may play a role in precrastination. We tested this prediction using a box-moving task developed in a previous study to measure precrastination. We also incorporated tasks measuring updating and inhibition aspects of executive function: the Stroop interference (both experiments) and Simon tasks (Experiment 2) to measure inhibition and the 2-Back memory task (Experiment 1) to measure updating. We found that the majority of participants precrastinated significantly throughout the box-moving task trials, consistent with results from past studies. However, no relation was found between the executive function tasks and rates of precrastination. These results may be due to the automaticity of precrastination when cognitive resources are limited.

Can you help me? Using others to offload cognition.

One of the most ancient and widely used forms of cognitive offloading is the outsourcing of cognitive operations onto other humans. Here, we explore whether humans preferentially seek out and use information from more competent compared with less competent others in an ongoing cognitive task. Participants (N = 120) completed a novel computerised visuospatial working memory task where each trial required them to remember either one, five, or ten target locations and recall them after a brief delay. Next, participants watched two virtual people compete in a distinct memory game, where one performed relatively well, demonstrating a stronger memory, and the other performed relatively poorly, demonstrating a weaker memory. Finally, participants completed the initial memory task again, but this time, either the strong-memory person or the weak-memory person was available to help with recall on each trial. Our results showed that, through observation and without direct instruction, participants acquired beliefs about the virtual people's cognitive proficiencies and could readily draw upon these beliefs to inform offloading decisions. Participants were typically more likely to ask for help from the strong-memory person, and this tendency was independent from other factors known to drive cognitive offloading more generally, like task difficulty, unaided cognitive ability, and metacognitive confidence.

Cognitive offloading is value-based decision making: Modelling cognitive effort and the expected value of memory.

How do people decide between maintaining information in short-term memory or offloading it to external reminders? How does this affect subsequent memory? This article presents a simple computational model based on two principles: A) items stored in brain-based memory occupy its limited capacity, generating an opportunity cost; B) reminders incur a small physical-action cost, but capacity is effectively unlimited. These costs are balanced against the value of remembering, which determines the optimal strategy. Simulations reproduce many empirical findings, including: 1) preferential offloading of high-value items; 2) increased offloading at higher memory loads; 3) offloading can cause forgetting of offloaded items ('Google effect') but 4) improved memory for other items ('saving-enhanced memory'); 5) reduced saving-enhanced-memory effect when reminders are unreliable; 6) influence of item-value: people may preferentially offload high-value items and store additional low-value items in brain-based memory; 7) greatest sensitivity to the effort of reminder-setting at intermediate rather than highest/lowest levels of task difficulty; 8) increased offloading in individuals with poorer memory ability. Therefore, value-based decision-making provides a simple unifying account of many cognitive offloading phenomena. These results are consistent with an opportunity-cost model of cognitive effort, which can explain why internal memory feels effortful but reminders do not.

A bonus task boosts people's willingness to offload cognition to an algorithm.

With the increased sophistication of technology, humans have the possibility to offload a variety of tasks to algorithms. Here, we investigated whether the extent to which people are willing to offload an attentionally demanding task to an algorithm is modulated by the availability of a bonus task and by the knowledge about the algorithm's capacity. Participants performed a multiple object tracking (MOT) task which required them to visually track targets on a screen. Participants could offload an unlimited number of targets to a "computer partner". If participants decided to offload the entire task to the computer, they could instead perform a bonus task which resulted in additional financial gain-however, this gain was conditional on a high performance accuracy in the MOT task. Thus, participants should only offload the entire task if they trusted the computer to perform accurately. We found that participants were significantly more willing to completely offload the task if they were informed beforehand that the computer's accuracy was flawless (Experiment 1 vs. 2). Participants' offloading behavior was not significantly affected by whether the bonus task was incentivized or not (Experiment 2 vs. 3). These results combined with those from our previous study (Wahn et al. in PLoS ONE 18:e0286102, 2023), which did not include a bonus task but was identical otherwise, show that the human willingness to offload an attentionally demanding task to an algorithm is considerably boosted by the availability of a bonus task-even if not incentivized-and by the knowledge about the algorithm's capacity.

The saving enhanced memory effect can be observed when only a subset of items are saved.

Saving one list of words, such as on a computer or by writing them down, can improve a person's ability to learn and remember a second list of words that are not saved. This phenomenon, known as the saving enhanced memory effect, is typically observed by comparing the recall of nonsaved items when other items are saved versus when they are not saved. In past research, the effect has been shown to occur when participants save an entire list before learning a new list. In the current research, we examined whether the effect can be observed when participants save a subset of items within a single list. The results of two experiments confirmed that partial saving can lead to a saving enhanced memory effect, with the effect observed regardless of whether participants saved items by clicking a button on the computer or writing them out by hand. The effect was observed on an item-specific cued-recall test (Experiment 1) as well as a free recall test that did not control the order of output (Experiment 2). However, the effect size did vary as a function of how participants attempted to recall the items on the final test. Specifically, participants who initiated their output by recalling nonsaved items exhibited a significantly larger saving enhanced memory effect than those who initiated their output by reproducing saved items. Together, these findings expand our understanding of the saving enhanced memory effect and shine new light on the impacts of cognitive offloading on human memory.

Intention offloading: Domain-general versus task-specific confidence signals.

Intention offloading refers to the use of external reminders to help remember delayed intentions (e.g., setting an alert to help you remember when you need to take your medication). Research has found that metacognitive processes influence offloading such that individual differences in confidence predict individual differences in offloading regardless of objective cognitive ability. The current study investigated the cross-domain organization of this relationship. Participants performed two perceptual discrimination tasks where objective accuracy was equalized using a staircase procedure. In a memory task, two measures of intention offloading were collected, (1) the overall likelihood of setting reminders, and (2) the bias in reminder-setting compared to the optimal strategy. It was found that perceptual confidence was associated with the first measure but not the second. It is shown that this is because individual differences in perceptual confidence capture meaningful differences in objective ability despite the staircase procedure. These findings indicate that intention offloading is influenced by both domain-general and task-specific metacognitive signals. They also show that even when task performance is equalized via staircasing, individual differences in confidence cannot be considered a pure measure of metacognitive bias.

Perseveration on cognitive strategies.

To acquire and process information, performers can frequently rely on both internal and extended cognitive strategies. However, after becoming acquainted with two strategies, performers in previous studies exhibited a pronounced behavioral preference for just one strategy, which we refer to as perseveration. What is the origin of such perseveration? Previous research suggests that a prime reason for cognitive strategy choice is performance: Perseveration could reflect the preference for a superior strategy as determined by accurately monitoring each strategy's performance. However, following our preregistered hypotheses, we conjectured that perseveration persisted even if the available strategies featured similar performances. Such persisting perseveration could be reasonable if costs related to decision making, performance monitoring, and strategy switching would be additionally taken into account on top of isolated strategy performances. Here, we used a calibration procedure to equalize performances of strategies as far as possible and tested whether perseveration persisted. In Experiment 1, performance adjustment of strategies succeeded in equating accuracy but not speed. Many participants perseverated on the faster strategy. In Experiment 2, calibration succeeded regarding both accuracy and speed. No substantial perseveration was detected, and residual perseveration was conceivably related to metacognitive performance evaluations. We conclude that perseveration on cognitive strategies is frequently rooted in performance: Performers willingly use multiple strategies for the same task if performance differences appear sufficiently small. Surprisingly, other possible reasons for perseveration like effort or switch cost avoidance, mental challenge seeking, satisficing, or episodic retrieval of previous stimulus-strategy-bindings, were less relevant in the present study.

Primacy Effects in Extended Cognitive Strategy Choice: Initial Speed Benefits Outweigh Later Speed Benefits.

BACKGROUND: Human performers often recruit environment-based assistance to acquire or process information, such as relying on a smartphone app, a search engine, or a conversational agent. To make informed choices between several of such extended cognitive strategies, performers need to monitor the performance of these options. OBJECTIVE: In the present study, we investigated whether participants monitor an extended cognitive strategy's performance-here, speed-more closely during initial as compared to later encounters. METHODS: In three experiments, 737 participants were asked to first observe speed differences between two competing cognitive strategies-here, two competing algorithms that can obtain answers to trivia questions-and eventually choose between both strategies based on the observations. RESULTS: Participants were sensitive to subtle speed differences and selected strategies accordingly. Most remarkably, even when participants performed identically with both strategies across all encounters, the strategy with superior speed in the initial encounters was preferred. Worded differently, participants exhibited a technology-use primacy effect. Contrarily, evidence for a recency effect was weak at best. CONCLUSION: These results suggest that great care is required when performers are first acquainted with novel ways to acquire or process information. Superior initial performance has the potential to desensitize the performer for inferior later performance and thus prohibit optimal choice. APPLICATION: Awareness of primacy enables users and designers of extended cognitive strategies to actively remediate suboptimal behavior originating in early monitoring episodes.

Mutual interplay between cognitive offloading and secondary task performance.

Various modern tools, such as smartphones, allow for cognitive offloading (i.e., the externalization of cognitive processes). In this study, we examined the use and consequences of cognitive offloading in demanding situations in which people perform multiple tasks concurrently-mimicking the requirements of daily life. In a preregistered study, we adapted the dual-task paradigm so that one of the tasks allowed for cognitive offloading. As a primary task, our participants (N = 172) performed the pattern copy task-a highly demanding working memory task that allows for offloading at various degrees. In this task, we manipulated the temporal costs of offloading. Concurrently, half of the participants responded to a secondary N-back task. As our main research question, we investigated the impact of offloading behavior on secondary task performance. We observed that more pronounced offloading in the condition without temporal costs was accompanied by a more accurate performance in the N-back task. Furthermore, the necessity to respond to the N-back task increased offloading behavior. These results suggest an interplay between offloading and secondary task performance: in demanding situations, individuals increasingly use cognitive offloading, which releases internal resources that can then be devoted to improving performance in other, concurrent tasks.

Eye Movements as Proxy for Visual Working Memory Usage: Increased Reliance on the External World in Korsakoff Syndrome.

In the assessment of visual working memory, estimating the maximum capacity is currently the gold standard. However, traditional tasks disregard that information generally remains available in the external world. Only when to-be-used information is not readily accessible, memory is taxed. Otherwise, people sample information from the environment as a form of cognitive offloading. To investigate how memory deficits impact the trade-off between sampling externally or storing internally, we compared gaze behaviour of individuals with Korsakoff amnesia (n = 24, age range 47-74 years) and healthy controls (n = 27, age range 40-81 years) on a copy task that provoked different strategies by having information freely accessible (facilitating sampling) or introducing a gaze-contingent waiting time (provoking storing). Indeed, patients sampled more often and longer, compared to controls. When sampling became time-consuming, controls reduced sampling and memorised more. Patients also showed reduced and longer sampling in this condition, suggesting an attempt at memorisation. Importantly, however, patients sampled disproportionately more often than controls, whilst accuracy dropped. This finding suggests that amnesia patients sample frequently and do not fully compensate for increased sampling costs by memorising more at once. In other words, Korsakoff amnesia resulted in a heavy reliance on the world as 'external memory'.

Just write it down: Similarity in the benefit from cognitive offloading in young and older adults.

Past research conducted primarily in young adults has demonstrated the utility of cognitive offloading for benefitting performance of memory-based tasks, particularly at high memory loads. At the same time, older adults show declines in a variety of memory abilities, including subtle changes in short-term memory, suggesting that cognitive offloading could also benefit performance of memory-based tasks in this group. To this end, 94 participants (62 young adults, 32 older adults) were tested on a retrospective audiovisual short-term memory task in two blocked conditions. Offloading was permitted in the offloading choice condition but not in the internal memory condition. Performance was improved for both age groups in the offloading choice condition compared to the internal memory condition. Moreover, the choice to use the offloading strategy was similar across age groups at high memory loads, and use of the offloading strategy benefitted performance for young and older adults similarly. These data suggest that older adults can make effective use of cognitive offloading to rescue performance of memory-based activities, and invites future research on the benefits of cognitive offloading for older adults in other, more complex tasks where age-related memory impairment is expected to be more prominent.

Take a load off: examining partial and complete cognitive offloading of medication information.

Although cognitive offloading, or the use of physical action to reduce internal cognitive demands, is a commonly used strategy in everyday life, relatively little is known about the conditions that encourage offloading and the memorial consequences of different offloading strategies for performance. Much of the extant work in this domain has focused on laboratory-based tasks consisting of word lists, letter strings, or numerical stimuli and thus makes little contact with real-world scenarios under which engaging in cognitive offloading might be likely. Accordingly, the current work examines offloading choice behavior and potential benefits afforded by offloading health-related information. Experiment 1 tests for internal memory performance for different pieces of missing medication interaction information. Experiment 2 tests internal memory and offloading under full offloading and partial offloading instructions for interaction outcomes that are relatively low severity (e.g., sweating). Experiment 3 extends Experiment 2 by testing offloading behavior and benefit in low-severity, medium-severity (e.g., backache), and high-severity interaction outcomes (e.g., heart attack). Here, we aimed to elucidate the potential benefits afforded by partial offloading and to examine whether there appears to be a preference for choosing to offload (i) difficult-to-remember information across outcomes that vary in severity, as well as (ii) information from more severe interaction outcomes. Results suggest that partial offloading benefits performance compared to relying on internal memory alone, but full offloading is more beneficial to performance than partial offloading.

Mountains of memory in a sea of uncertainty: Sampling the external world despite useful information in visual working memory.

A large part of research on visual working memory (VWM) has traditionally focused on estimating its maximum capacity. Yet, humans rarely need to load up their VWM maximally during natural behavior, since visual information often remains accessible in the external world. Recent work, using paradigms that take into account the accessibility of information in the outside world, has indeed shown that observers utilize only one or two items in VWM before sampling from the external world again. One straightforward interpretation of this finding is that, in daily behavior, much fewer items are memorized than the typically reported capacity limits. Here, we first investigate whether this lower reliance on VWM when information is externally accessible might instead reflect resampling before VWM is actually depleted. To this aim we devised an online task, in which participants copied a model (six items in a 4x4 grid; always accessible) in an adjacent empty 4x4 grid. A key aspect of our paradigm is that we (unpredictably) interrupted participants just before inspection of the model with a 2-alternative-forced-choice (2-AFC) question, probing their VWM content. Critically, we observed above-chance performance on probes appearing just before model inspection. This finding shows that the external world was resampled, despite VWM still containing relevant information. We then asked whether increasing the cost of sampling causes participants to load up more information in VWM or, alternatively, to squeeze out more information from VWM (at the cost of making more errors). To manipulate the cost of resampling, we made it more difficult (specifically, more time-consuming) to access the model. We show that with increased cost of accessing the model (which lead to fewer, but longer model inspections), participants could place more items correctly immediately after sampling, and they kept attempting to place items for longer after their first error. These findings demonstrate that participants both encoded more information in VWM and made attempts to squeeze out more information from VWM when sampling became more costly. We argue that human observers constantly evaluate how certain they are of their VWM contents, and only use that VWM content of which their certainty exceeds a context-dependent "action threshold". This threshold, in turn, depends on the trade-off between the cost of resampling and the benefits of making an action. We argue that considering the interplay between the available VWM contents and a context-dependent action threshold, is key for reconciling the traditional VWM literature with VWM use in our day-to-day behavior.

Outsourcing Memory to External Tools: A Review of 'Intention Offloading'.

How do we remember delayed intentions? Three decades of research into prospective memory have provided insight into the cognitive and neural mechanisms involved in this form of memory. However, we depend on more than just our brains to remember intentions. We also use external props and tools such as calendars and diaries, strategically placed objects, and technologies such as smartphone alerts. This is known as 'intention offloading'. Despite the progress in our understanding of brain-based prospective memory, we know much less about the role of intention offloading in individuals' ability to fulfil delayed intentions. Here, we review recent research into intention offloading, with a particular focus on how individuals decide between storing intentions in internal memory versus external reminders. We also review studies investigating how intention offloading changes across the lifespan and how it relates to underlying brain mechanisms. We conclude that intention offloading is highly effective, experimentally tractable, and guided by metacognitive processes. Individuals have systematic biases in their offloading strategies that are stable over time. Evidence also suggests that individual differences and developmental changes in offloading strategies are driven at least in part by metacognitive processes. Therefore, metacognitive interventions could play an important role in promoting individuals' adaptive use of cognitive tools.

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future.

In the present article, we explore prospects for using artificial intelligence (AI) to distribute cognition via cognitive offloading (i.e., to delegate thinking tasks to AI-technologies). Modern technologies for cognitive support are rapidly developing and increasingly popular. Today, many individuals heavily rely on their smartphones or other technical gadgets to support their daily life but also their learning and work. For instance, smartphones are used to track and analyze changes in the environment, and to store and continually update relevant information. Thus, individuals can offload (i.e., externalize) information to their smartphones and refresh their knowledge by accessing it. This implies that using modern technologies such as AI empowers users via offloading and enables them to function as always-updated knowledge professionals, so that they can deploy their insights strategically instead of relying on outdated and memorized facts. This AI-supported offloading of cognitive processes also saves individuals' internal cognitive resources by distributing the task demands into their environment. In this article, we provide (1) an overview of empirical findings on cognitive offloading and (2) an outlook on how individuals' offloading behavior might change in an AI-enhanced future. More specifically, we first discuss determinants of offloading such as the design of technical tools and links to metacognition. Furthermore, we discuss benefits and risks of cognitive offloading. While offloading improves immediate task performance, it might also be a threat for users' cognitive abilities. Following this, we provide a perspective on whether individuals will make heavier use of AI-technologies for offloading in the future and how this might affect their cognition. On one hand, individuals might heavily rely on easily accessible AI-technologies which in return might diminish their internal cognition/learning. On the other hand, individuals might aim at enhancing their cognition so that they can keep up with AI-technologies and will not be replaced by them. Finally, we present own data and findings from the literature on the assumption that individuals' personality is a predictor of trust in AI. Trust in modern AI-technologies might be a strong determinant for wider appropriation and dependence on these technologies to distribute cognition and should thus be considered in an AI-enhanced future.

Does taking multiple photos lead to a photo-taking-impairment effect?

The photo-taking-impairment effect is observed when photographed information is less likely to be remembered than nonphotographed information. Three experiments examined whether this effect persists when multiple photos are taken. Experiment 1 used a within-subjects laboratory-based design in which participants viewed images of paintings and were instructed to photograph them once, five times, or not at all. Participants' memory was measured using a visual detail test, and the photo-taking-impairment effect was observed when participants took multiple photos. Experiment 2 examined the photo-taking-impairment effect using a between-subjects design. Participants either photographed all of the paintings they saw once, five times, or not at all, before being tested on their memory for the paintings. The photo-taking-impairment effect was observed in both photo-taking conditions relative to the no photo baseline. Experiment 3 replicated this pattern of results even when participants who took multiple photos were instructed to take five unique photos. These findings indicate that the photo-taking-impairment effect is robust, occurring even when multiple photos are taken, and after nonselective photo-taking.

Study effort and the memory cost of external store availability.

Previous work demonstrates that individuals often recall less information if, at study, there is expectation that an external memory store will be available at test. One explanation for this effect is that when individuals can expect access to an external memory store, they forgo intentional, controlled efforts at encoding. The present work offers a novel test of this account by examining study effort, indexed by study time and self-reported strategy use, as a function of instructed external store availability. In two preregistered experiments, participants studied lists of to-be-remembered items for a free recall test and were either instructed that they could use their study list to support them at test or that they could not. Critically, participants controlled their own study time, and no participant had their study list at test, regardless of instruction. Consistent with the effort at encoding account, external store availability influenced both study time and strategy use, and there was evidence that these effects mediated the influence of external store availability on recall performance. Interestingly, much of the memory cost remained when controlling for study effort, thus, suggesting that the cost is potentially multiply determined.

Partially Overlapping Neural Correlates of Metacognitive Monitoring and Metacognitive Control.

Metacognition describes the process of monitoring one's own mental states, often for the purpose of cognitive control. Previous research has investigated how metacognitive signals are generated (metacognitive monitoring), for example, when people (both female/male) judge their confidence in their decisions and memories. Research has also investigated how metacognitive signals are used to influence behavior (metacognitive control), for example, setting a reminder (i.e., cognitive offloading) for something you are not confident you will remember. However, the mapping between metacognitive monitoring and metacognitive control needs further study on a neural level. We used fMRI to investigate a delayed-intentions task with a reminder element, allowing human participants to use their metacognitive insight to engage metacognitive control. Using multivariate pattern analysis, we found that we could separately decode both monitoring and control, and, to a lesser extent, cross-classify between them. Therefore, brain patterns associated with monitoring and control are partially, but not fully, overlapping.SIGNIFICANCE STATEMENT Models of metacognition commonly distinguish between monitoring (how metacognition is formed) and control (how metacognition is used for behavioral regulation). Research into these facets of metacognition has often happened in isolation. Here, we provide a study which directly investigates the mapping between metacognitive monitoring and metacognitive control at a neural level. We applied multivariate pattern analysis to fMRI data from a novel task in which participants separately rated their confidence (metacognitive monitoring) and how much they would like to use a reminder (metacognitive control). We find support for the notion that the two aspects of metacognition overlap partially but not fully. We argue that future research should focus on how different metacognitive signals are selected for control.

Know Your Cognitive Environment! Mental Models as Crucial Determinant of Offloading Preferences.

OBJECTIVE: Human problem solvers possess the ability to outsource parts of their mental processing onto cognitive "helpers" (cognitive offloading). However, suboptimal decisions regarding which helper to recruit for which task occur frequently. Here, we investigate if understanding and adjusting a specific subcomponent of mental models-beliefs about task-specific expertise-regarding these helpers could provide a comparatively easy way to improve offloading decisions. BACKGROUND: Mental models afford the storage of beliefs about a helper that can be retrieved when needed. METHODS: Arithmetic and social problems were solved by 192 participants. Participants could, in addition to solving a task on their own, offload cognitive processing onto a human, a robot, or one of two smartphone apps. These helpers were introduced with either task-specific (e.g., stating that an app would use machine learning to "recognize faces" and "read emotions") or task-unspecific (e.g., stating that an app was built for solving "complex cognitive tasks") descriptions of their expertise. RESULTS: Providing task-specific expertise information heavily altered offloading behavior for apps but much less so for humans or robots. This suggests (1) strong preexisting mental models of human and robot helpers and (2) a strong impact of mental model adjustment for novel helpers like unfamiliar smartphone apps. CONCLUSION: Creating and refining mental models is an easy approach to adjust offloading preferences and thus improve interactions with cognitive environments. APPLICATION: To efficiently work in environments in which problem-solving includes consulting other people or cognitive tools ("helpers"), accurate mental models-especially regarding task-relevant expertise-are a crucial prerequisite.