Interface and interaction design: How mobile touch devices foster cognitive offloading

Influence of the physical effort of reminder-setting on strategic offloading of delayed intentions

Intention offloading involves using external reminders such as diaries, to-do lists, and digital alerts to help us remember delayed intentions. Recent studies have provided evidence for various cognitive and metacognitive factors that guide intention offloading, but little research has investigated the physical cost of reminder-setting itself. Here, we present two pre-registered experiments investigating how the cost of physical effort associated with reminder-setting influences strategic intention offloading under different levels of memory load. At all memory loads, reminder-setting was reduced when it was more effortful. The ability to set reminders allowed participants to compensate for the influence of memory load on accuracy in the low-effort condition; this effect was attenuated in the high-effort condition. In addition, there was evidence that participants with less confidence in their memory abilities were more likely to set reminders. Contrary to prediction, physical effort had the greatest effect on reminder-setting at intermediate memory loads. We speculate that the physical costs of reminder-setting might have the greatest impact when participants are uncertain about their strategy choice. These results demonstrate the importance of physical effort as one of the factors relevant to cost-benefit decision-making about cognitive offloading strategies.

Switching between different cognitive strategies induces switch costs as evidenced by switches between manual and mental object rotation

Switching between tasks entails costs when compared to repeating the same task. It is unclear whether switch costs also occur when repeating the same task but switching the underlying cognitive strategy (CS). Here, we investigated whether CS switch costs exist despite overlap in mental processing between CSs and a lack of abstract goal (always "solve task X") or answer key binding switches. Specifically, we asked participants to judge the identity of two misaligned objects by either mental or manual computer-mediated object rotation. In each trial of Block 1, to measure switch costs without choice-related cognitive processes, a cue indicated which CS (mental/manual) to use. In Block 2, the CS was freely chosen. Participants exhibited considerable CS switch costs for both cued and freely chosen switches. Moreover, Block 1 switch costs moderately predicted Block 2 switch frequency, while an overall tendency for CS repetition was observed. In sum, we found that switch costs are not confined to situations in which tasks are switched but generalize to situations in which the task stays identical and the CS is switched instead. The results have implications for modern computerized cognitive environments in which a multitude of cognitive strategies is available for the same task.

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.

Framing cognitive offloading in terms of gains or losses: achieving a more optimal use of reminders

Nowadays individuals can readily set reminders to offload intentions onto external resources, such as smartphone alerts, rather than using internal memory. Individuals tend to be biased, setting more reminders than would be optimal. We address the question whether the reminder bias depends on offloading scenarios being framed as either gains or losses, both between-participants (Experiment 1) and within-participants (Experiment 2). In both experiments, framing of reminders in terms of gains resulted in participants employing a risk-averse strategy and using more reminders than would be optimal. Importantly, however, participants used reminders more optimally and were more willing to choose the risk-seeking option of remembering internally when reminders implied a loss. Based on metacognitive measures in Experiment 2, the reminder bias increased the more underconfident participants were about their memory abilities in both framing scenarios. Framing did not alter this relationship between erroneous metacognitive underconfidence and reminder bias but provides an additional influence. We conclude that emphasizing the losses (costs) associated with external reminders helps in achieving more optimal decisions in offloading situations, and that in addition to cognitive effort and metacognitive judgments, framing needs to be considered in improving individuals’ offloading behavior.

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.

Impact of Intrinsic Cognitive Skills and Metacognitive Beliefs on Tool Use Performance

Cognitive tools (e.g., calculators) provide all users with the same potential. Yet when people use such cognitive tools, interindividual variations are observed. Previous findings have indicated that 2 main factors could explain these variations: intrinsic cognitive skills (i.e., the “non–tool use” cognitive skills associated with the task targeted) and metacognitive beliefs about one's performance with tool use. In this study we sought to reproduce these findings and to investigate in more detail the nature of the relationships (i.e., linear vs. exponential) between tool use performance and intrinsic cognitive skills. In Experiment 1, 200 participants completed 2 cognitive tasks (calculation and geography) in 2 conditions (non–tool use vs. tool use). In Experiment 2, 70 participants performed a geography task in 2 conditions (non–tool use vs. tool use) and estimated their performance in each condition before completing the task. Results indicated that intrinsic cognitive skills and, to a lesser extent, metacognitive beliefs improved tool use performance: The higher the intrinsic cognitive skills and the higher participants estimated their tool use performance, the higher this tool use performance was. The nature of the relationship between tool use performance and intrinsic cognitive skills appeared to be linear rather than exponential. These findings extend previous research showing a strong impact of intrinsic cognitive skills on the performance associated with the use of cognitive tools or external aids.

Young children spontaneously devise an optimal external solution to a cognitive problem

Metacognition plays an essential role in adults' cognitive offloading decisions. Despite possessing basic metacognitive capacities, however, preschool-aged children often fail to offload effectively. Here, we introduced 3- to 5-year-olds to a novel search task in which they were unlikely to perform optimally across trials without setting external reminders about the location of a target. Children watched as an experimenter first hid a target in one of three identical opaque containers. The containers were then shuffled out of view before children had to guess where the target was hidden. In the test phase, children could perform perfectly by simply placing a marker in a transparent jar attached to the target container prior to shuffling, and then later selecting the marked container. Children of all ages used this external strategy above chance levels if they had seen it demonstrated to them, but only the 4- and 5-year-olds independently devised the strategy to improve their future performance. These results suggest that, when necessary for optimal performance, even 4- and 5-year-olds can use metacognitive knowledge about their own future uncertainty to deploy effective external solutions.

Evaluating the Influence of Visual Attentional Tracking on Pointing Movement Precision

Multiple object tracking (MOT) and goal-directed movements are both based on attentional processes. This study focused on the instant effect of attentive tracking with respect to pointing performance. We measured the precision of pointing to the targets of an MOT task immediately after the tracking period when all the objects were still in motion, and to the precision of pointing to moving objects in the task without attentional tracking. The results demonstrated that an increase in the attentional tracking load was the primary factor that decreased pointing precision, although visual load may also contribute to this influence. We also manipulated the relationship between the number of targets and the density of the MOT display (the total number of objects displayed), which affected the MOT accuracy but not the pointing precision.

Individual differences in cognitive offloading: a comparison of intention offloading, pattern copy, and short-term memory capacity

The cognitive load of many everyday life tasks exceeds known limitations of short-term memory. One strategy to compensate for information overload is cognitive offloading which refers to the externalization of cognitive processes such as reminder setting instead of memorizing. There appears to be remarkable variance in offloading behavior between participants which poses the question whether there is a common factor influencing offloading behavior across different tasks tackling short-term memory processes. To pursue this question, we studied individual differences in offloading behavior between two well-established offloading paradigms: the intention offloading task which tackles memory for intentions and the pattern copy task which tackles continuous short-term memory load. Our study also included an unrelated task measuring short-term memory capacity. Each participant completed all tasks twice on two consecutive days in order to obtain reliability scores. Despite high reliability scores, individual differences in offloading behavior were uncorrelated between the two offloading tasks. In both tasks, however, individual differences in offloading behavior were correlated with the individual differences in an unrelated short-term memory task. Our results therefore show that offloading behavior cannot simply be explained in terms of a single common factor driving offloading behavior across tasks. We discuss the implications of this finding for future research investigating the interrelations of offloading behavior across different tasks.

From metacognitive beliefs to strategy selection: does fake performance feedback influence cognitive offloading?

The ubiquitous availability of technological aids requires individuals to constantly decide between either externalizing cognitive processes into these aids (i.e. cognitive offloading) or relying on their own internal cognitive resources. With the present research, we investigated the influence of metacognitive beliefs on individuals’ offloading behavior in an experimental setup (N = 159). We manipulated participants’ metacognitive beliefs about their memory abilities by providing fake performance feedback: below-average feedback, above-average feedback, or no feedback (control-group). We then measured offloading behavior, using a pattern copying task in which participants copied a color pattern from a model window into a workspace window. While solving this task, participants could rely either more on an internal memory strategy or more on an offloading strategy. Fake performance feedback affected the participants’ metacognitive evaluations about their memory abilities (below-group < control-group < above-group). Although fake performance feedback did not affect actual offloading behavior, the participants receiving below-average performance feedback reported that they had relied more on an offloading strategy than those participants receiving above-average performance feedback. Furthermore, the participants in the below-group reported lower general memory abilities than the other groups at the end of the experiment. We conclude that while fake performance feedback strongly influenced metacognitive beliefs, this did not transfer into a change of strategy selection, thus not influencing offloading behavior. We propose to consider not only metacognitive beliefs but also metacognitive experiences as potential determinants of cognitive offloading.