When the authors refer to the use of deepfake in education (...

It’s been four decades since society was in awe of the quality of recordings available from a cassette recorder tape. Today we have something new to be in awe of: deepfakes. Deepfakes include hyperrealistic videos that use artificial intelligence (AI) to create fake digital content that looks and sounds real. The word is a portmanteau of “deep learning” and “fake.” Deepfakes are everywhere: from TV news to advertising, from national election campaigns to wars between states, and from cybercriminals’ phishing campaigns to insurance claims that fraudsters file. And deepfakes come in all shapes and sizes — videos, pictures, audio, text, and any other digital material that can be manipulated with AI. One estimate suggests that deepfake content online is growing at the rate of 400% annually.

There appear to be legitimate uses of deepfakes, such as in the medical industry to improve the diagnostic accuracy of AI algorithms in identifying periodontal disease or to help medical professionals create artificial patients (from real patient data) to safely test new diagnoses and treatments or help physicians make medical decisions. Deepfakes are also used to entertain, as seen recently on America’s Got Talent, and there may be future uses where deepfake could help teachers address the personal needs and preferences of specific students.

Unfortunately, there is also the obvious downside, where the most visible examples represent malicious and illegitimate uses. Examples already exist.

Deepfakes also involve voice phishing, also known as vishing, which has been among the most common techniques for cybercriminals. This technique involves using cloned voices over the phone to exploit the victim’s professional or personal relationships by impersonating trusted individuals. In March 2019, cybercriminals were able to use a deepfake to fool the CEO of a U.K.-based energy firm into making a US$234,000 wire transfer. The British CEO who was victimized thought that the person speaking on the phone was the chief executive of the firm’s German parent company. The deepfake caller asked him to transfer the funds to a Hungarian supplier within an hour, emphasizing that the matter was extremely urgent. The fraudsters used AI-based software to successfully imitate the German executive’s voice. […]

What can be done to combat deepfakes? Could we create deepfake detectors? Or create laws or a code of conduct that probably would be ignored?

There are tools that can analyze the blood flow in a subject’s face and then compare it to human blood flow activity to detect a fake. Also, the European Union is working on addressing manipulative behaviors.

There are downsides to both categories of solutions, but clearly something needs to be done to build trust in this emerging and disruptive technology. The problem isn’t going away. It is only increasing.

Nit Kshetri, Bryan School of Business and Economics, University of North Carolina at Greensboro, Greensboro, NC, USA

Joanna F. DeFranco, Software Engineering, The Pennsylvania State University, Malvern, PA, USA Jeffrey Voas, NIST, USA

Adapted from: https://www.computer.org/csdl/magazine/co/2023/07/10154234/ 1O1wTOn6ynC