By Seda Japp, Ph.D.
We humans tend to think that there are many factors that differentiate us from computers. While doing that, we focus on things that make us unique, things humans can do but computers cannot for now. But, from a human factors perspective, focusing on the strengths of computers and weaknesses of humans might give interesting insights as well. If we know what makes computers unique, we might leverage those aspects in product design to minimize use errors. What do computers really do better than us?
One major difference between the human brain and computers is the way they store information. Computers use electronic circuits that store information digitally. The human brain, on the other hand, stores information on nerve cells using complex biological coding mechanisms (1). One major consequence of this digital vs. biologic way of storing information is that computer memory is more literal and less prone to corruption whereas human memory is a reconstruction and is more subject to corruption.
Cognitive neuroscience and psychology studies suggest that the brain has separate systems for storing short term vs. long term information. Short term memory, also called the working memory, has a limited capacity and stores information for a short period of time (i.e. in the order of seconds). Long term memory has a storage system that is more unlimited in capacity and spans a longer duration. Long term memory appears to have many subsystems, including explicit and implicit memory. Explicit memories are for facts, events, people, places, and objects, whereas implicit memories support perceptual and motor skills. These two memory systems are responsible for learning and storing different types of information, and that information is processed by different systems of the brain. Explicit memories are represented in a network comprising the hippocampus and medial temporal lobes, whereas implicit memories are supported by networks that incorporate subcortical regions such as the cerebellum, striatum and amygdala.
While both types of memory have interesting implications for human factors and usability, this post will focus on explicit memories as they represent factual knowledge including knowledge about how to use a product. Factual memory, along with other types of explicit memory, is formed using a cellular mechanism called synaptic plasticity. Synaptic plasticity is comprised of long term potentiation (LTP) and long term depression (LTP). LTP refers to the idea that neurons that are activated together end up having stronger connections with each other over time, leading to memory formation.
LTP can occur via different mechanisms, including homosynaptic plasticity and heterosynaptic plasticity. In homosynaptic plasticity, only the neurons that are activated together develop stronger connections whereas in heterosynaptic plasticity, adjacent neurons develop stronger connections as well even if they are not activated together. Hence, when a memory is encoded (created) or retrieved (e.g., recalled or recognized), it is not just stored in a single place but rather represented by a network of neurons (1). This network-based coding in the brain gives us more flexibility in terms of connecting semantically related things to each other but also means that sometimes we might accidentally activate a related yet incorrect network, store or retrieve inaccurate information and create what is called a ‘false memory’ (2).
A false memory is a phenomenon that happens when people report remembering information that is wrong, for example that they have seen faces they have never actually seen, or recall events that never actually happened. Such fallibility of human memory has huge implications for our society. One striking example comes from the courtroom. Researchers investigating witness behavior have shown people faces that they have never seen before and asked them if they recognize the offender from a crime scene they witnessed. Surprisingly, many people confidently identified a person they had never seen as the criminal, which in real life could lead to false convictions (3). For our purpose of considering human factors, the question then arises: what are the implications of the fallibility of human memory for the usability of products?
According to Don Norman and James Reason, memory lapses are common causes of human error and can lead to different types of error, including skipping steps necessary for use, and failing to finish the process and reach the outcome desired by use (4). There are various ways to prevent such memory lapses in product use. One method is to minimize the steps required to successfully use the product. Another is to provide reminders of the steps that need to be completed. The strongest strategy is to simply design out the potential for the use error by implementing what is called a forcing function. A forcing function basically prohibits the possibility of a use error by enforcing the user to perform a preventive action (e.g. ATM machines requesting the bank card to be removed before giving the money). In particular, reminders and forcing functions may be where the strengths of computers over human memory could be best leveraged. This is an example where the Human Factors Engineering comes into play during product development.
Human Factors Engineering enables companies to investigate where their products gloss over the boundaries of human mind. For potentially high-risk products like medical devices and combination products, safety is tied to usability. Per FDA’s guidance, one should understand the potential use-related risks for a medical product in development. One method of gaining this understanding is to use the Perception, Cognition and Action model (PCA). The PCA model provides a framework for assessing potential use errors by trying to understand whether a difficulty related to perception (e.g. the user did not ‘see’ or ‘hear’ something), cognition (e.g. the user did not remember or did not know to do something) or action (e.g. the user could not open the box) could occur with real-life use of a product. A memory lapse is a good example of a cognitive difficulty that could generate use errors if safe and correct use of the product requires keeping a lot of critical information in mind.
A well-designed Human Factors Engineering program can help a product’s design overcome the limitations of human memory and guide safe and usable product development by reducing the potential for memory-related errors in use.
(1) Kandel E. R., Dudai Y., Mayfords R. M., The Molecular and Systems Biology of Memory. Cell, 2014. https://doi.org/10.1016/j.cell.2014.03.001
(2) Chadwick M. J., Anjum S. R., Kumaran D., Schacter D. L., Spiers H. J., Hassabis D. (2016). Semantic representations in the temporal pole predict false memories. PNAS September 6, 2016. 113 (36) 10180-10185. https://doi.org/10.1073/pnas.1610686113
(3) Lacy, J. W., & Stark, C. E. L. (2013). The Neuroscience of Memory: Implications for the Courtroom. Nature Reviews. Neuroscience, 14(9), 649–658. http://doi.org/10.1038/nrn3563
(4) Don Norman. The Design of Everyday Things, Basic Books 2013