Psychology and Technology

Psychology is a field that not only applies to human behavior, but with the development of technology and AI programs like Apple’s SIRI, artificial intelligence is rapidly emerging using psychological theories as a foundation for their programming. B.F. Skinner was influential in the area of behavior with his theory of operant conditioning by identifying the factors which caused behavior. In doing so, he was able to develop his theory of positive and negative reinforcement as a tool to teach and modify behavior through operant conditioning (Iversen, 1992). It is through this process of reinforcement learning that developers program artificial intelligence and bring psychological methods into the fields of technology and engineering.

Reinforcement learning (RL) is used to program artificial intelligence software programs like SIRI. However, reinforcement learning is not only used in programs to make adaptable software for consumer use, it is also used for the adaptions involved in the learning of robots. This occurs when reinforcement learning algorithms can be applied to the machines themselves in order to assist them in making adaptations and adjustments in their abilities as they learn. A set of behaviors are programmed into the robot, along with parameters and rules which assist the robot in perceiving the situation and then corresponding it to a specific behavior rule. The robot then learns which behaviors are needed and which strategies should be used, thus modifying its behavior to accomplish a task (Song, Li, Wang, Ma, & Ruan, 2014).

These types of reinforcement learning behaviors and modifications to artificially intelligent robots are paramount in order for them to meet their potential (Hester & Stone, 2013). To best serve mankind, robots can visit places that are far too dangerous for man to explore. For example, the MARS Rover is able to retrieve samples and data from the planet Mars in order to further scientific research on other planets. However, it is still very reliant upon communications from NASA and regular software updates to keep it running (Wright, 2013). The future of these types of missions could improve vastly if AI robots could think for themselves, and be able to tackle challenges without communications from earth. This is where the future of psychology and technology lies, and its potential is as far reaching as the galaxy itself.

References

Hester, T., todd@cs.utexas.edu, & Stone, P., pstone@cs.utexas.edu. (2013). TEXPLORE: Real-time sample-efficient reinforcement learning for robots. Machine Learning, 90(3), 385-429. doi:10.1007/s10994-012-5322-7

Iversen, I. H. (1992). Skinner's early research: From reflexology to operant conditioning. American Psychologist, 47(11), 1318-1328. doi:10.1037/0003-066X.47.11.1318

Song, Y., Li, Y., Wang, X., Ma, X., & Ruan, J. (2014). An improved reinforcement learning algorithm for cooperative behaviors of mobile robots. Journal of Control Science & Engineering, , 1-8. doi:10.1155/2014/270548

Wright, A. (2013). Revving the rover. Communications of the ACM, 56(2), 14-16. doi:10.1145/2408776.2408782

Catheryn Reardon, M. Ed.
Adjunct Professor
Georgia Military College-Online Campus