While artificial intelligence may be a newcomer in some industries, it's had a longstanding relationship with cognitive psychology since the field first emerged.
Cognitive psychology surfaced in the 1960s and is all about information processing. Initially using the computer as a metaphor for human information processing, this way of thinking guided cognitive psychologists’ theories of how humans take in information, transform it, combine it, and create outputs. As computer capacity and computer science developed over time, it made room for more complexity in psychologists' theories on information processing.
As artificial intelligence expands its reach, the technology has quickly gained traction in the cognitive psychology field and is being used to create models that explain how people take in, process, and use information from their environment.
“AI can make our theories and models more sophisticated and give us the opportunity to test much more precise ideas about what's going on in the mind,” says Heather Lacey, Ph.D., Psychology professor and department chair who specializes in risk and decision making. “Instead of trying to identify what people do in an abstract way, there's a new focus growing on the specific mechanisms, looking at how these circuits talk to those circuits to produce some output.”
Lacey adds that AI is making headway in cognitive computational modeling where researchers develop models meant to predict how people learn, remember things, solve problems, and make decisions. Until recently, cognitive computational modeling had been an underutilized tool because it required sophisticated computer science and coding skills.
“The beauty of AI is that you don't have to be a genius coder. You just have to know what you want it to do, and you can ask the AI to get under the hood and do it for you,” Lacey says.
Noting that there is no AI or computer as complex as the human brain, Lacey examines how the tech is being implemented and ethical considerations that need to be addressed.
From a research lens
AI is currently assisting in memory, attention, and decision-making research, says Lacey, adding that the technology is helping in developing faster, more sophisticated data analysis within research and new avenues for stimuli used in experiments.
“Information can be digested much more readily, patterns can be found, and predictions can be made that were not easy for humans using more basic tools,” Lacey says.
For instance, say a student researcher wanted to show a male and female face that were the same in every way except their gender. This could be achieved through careful image editing, but Lacey notes that this is often beyond the scope of a typical student researcher. Meanwhile, AI could create those images for the experiment to see how someone responds to the two faces.
RELATED ARTICLE: 'AI is becoming more prevalent and changing every day'
“That's something that, now, any researcher in any lab has the capacity to do,” Lacey says.
She adds that historically at the college level, there have been limits to what labs can do because of resources and funding.
“AI opens the capacity to run more sophisticated experiments than most small programs would be able to do,” Lacey says.
Strides with careful consideration
While there are many benefits to AI, Lacey notes that ethical considerations, such as bias, should be kept in mind. There are already many ways in which human thinking is flawed, and while it is tempting to think that computers are bias-free, it’s vital to remember that these models are programmed by humans and trained on human information.
“Whatever vast bodies of information it's drawing on means it's being trained on our biases, so our biases are in there. Just as it's hard to recognize our own human fallibility, we're going to have to work hard to recognize AI's fallibility. It'll take some clear-eyed criticism to keep that in mind,” Lacey says.
RELATED ARTICLE: From chatbots to robots, Bryant students are building the future now in new AI Lab
She adds that attention needs to be given to how the research process and dissemination of information from studies will be reshaped. Like any academic field, psychology research includes intellectual property and individual voice in the writing — everything from how the experiment was conducted to explaining the theories that were developed and why. While the concept of AI use and support in psychology research is promising, how it will be implemented, ethically and transparently, remains to be seen.
“That very specific voice and very specific expertise is going to get shaped very differently,” Lacey says. “But, as far as what we can produce, I think it’s going to explode.”