On the Blameworthiness of Forgetting

It is a mistake to think that we cannot be morally responsible for forgetting because, as a matter of principle, forgetting is outside of our control. Sometimes we do have control over our forgetting. When forgetting is under our control there is no question that it is the proper object of praise and blame. But we can also be morally responsible for forgetting something when it is beyond our control that we forget that thing. The literature contains three accounts of the blameworthiness of forgetting over which the agent has no control—the tracing account, the liberalized awareness condition, and attributionism. Even though these are competing accounts of the blameworthiness of harmful forgetting they are compatible with one another. In particular, it is possible to come up with a position that endorses the tracing account for certain kinds of harmful forgetting and attributionism for other kinds of harmful forgetting

Forgetting

Forgetting is importantly related to remembering, evidence possession, epistemic virtue, personal identity, and a host of highly-researched memory conditions. In this paper I examine the nature of forgetting. I canvass the viable options for forgetting’s ontological category, type of content, characteristic relation to content, and scale. I distinguish several theories of forgetting in the philosophy and psychology of memory literatures, theories that diverge on these options. The best theories from the literature, I claim, fail two critical tests that I develop (the metacognition and prospection tests), underwriting arguments against the theories. I introduce a new theory about the state of forgetting—the learning, access failure, dispositional (LEAD) theory: to forget is to fail to access something that is both learned and either inaccessible or intended to be accessed. I argue that the LEAD theory of forgetting is the lead theory of forgetting. It passes the metacognition and prospection tests, and has several further virtues at no cost. Finally, I advocate reductionism about the process of forgetting; the process reduces wholly to states of forgetting. In particular, a process of forgetting is just a sequence of increasingly strong states of forgetting

Using recognition-induced forgetting to assess forgetting of racial minority faces

Recognition-induced forgetting is a forgetting effect whereby items held in visual long-term memory are forgotten as a consequence of recognizing other items of the same category. Previous research has demonstrated that recognition-induced forgetting occurs for White faces but not Black faces. Specifically, while recognizing one White face leads to the forgetting of another, memory for Black faces is undisturbed in the same situation. In the real world, the immunity of Black faces to recognition-induced forgetting could cause disproportionately more positive eyewitness identifications of Black suspects than White suspects. Are racial minority faces immune to recognition-induced forgetting? Here we tested recognition-induced forgetting of Asian faces. Despite replicating the immunity of Black faces to recognition-induced forgetting, Asian faces were susceptible to recognition-induced forgetting. These findings suggest that racial minority status of the face does not create immunity to recognition-induced forgetting.No embargoAcademic Major: Psycholog

Survival of the Fittest: Increased Stimulus Competition During Encoding Results in Fewer but More Robust Memory Traces

Forgetting can be accounted for by time-indexed decay as well as competition-based interference processes. Although conventionally seen as competing theories of forgetting processes, Altmann and colleagues argued for a functional interaction between decay and interference. They revealed that, in short-term memory, time-based forgetting occurred at a faster rate under conditions of high proactive interference compared to conditions of low proactive interference. However, it is unknown whether interactive effects between decay-based forgetting and interference-based forgetting also exist in long-term memory. We employed a delayed memory recognition paradigm for visual indoor and outdoor scenes, measuring recognition accuracy at two time-points, immediately after learning and after 1 week, while interference was indexed by the number of images in a semantic category. We found that higher levels of interference during encoding led to a slower subsequent decay rate. In contrast to the findings in working-memory, our results suggest that a "survival of the fittest" principle applies to long-term memory processes, in which stimulus competition during encoding results in fewer, but also more robust memory traces, which decay at a slower rate. Conversely, low levels of interference during encoding allow more memory traces to form initially, which, however, subsequently decay at a faster rate. Our findings provide new insights into the mechanism of forgetting and could inform neurobiological models of forgetting

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting

The effect of job similarity on forgetting in multi-task production

For many decades, research has been done on the effect of learning and forgetting for manual assembly operations. Due to the evolution towards mass customization, cycle time prediction becomes more and more complex. The frequent change of tasks for an operator results in a rapid alternation between learning and forgetting periods, since the production of one model is causing a forgetting phase for another model. a new mathematical model for learning and forgetting is proposed to predict the future cycle time of an operator depending on the product mix of his actual assembly schedule. A main factor for this model is the job similarity between the task that is being learned and is being forgotten. In our experimental study the impact of job similarity onto the forgetting effect is measured. Two groups of operators were submitted to an equal time schedule, with other tasks to perform. At first, both groups were asked to perform the same main task. In the subsequent phase, they were submitted to different assembly tasks, each with another job similarity towards the main task, before again executing that main task. After a period of inactivity, the main task was assembled again by every subject. Results confirm that a higher job similarity results in a lower forgetting effect for the main task