Argument

Internet Protection Laws: Deepfake Technology Protection Policy

Abrahim Ibrahim

Cal State Los Angeles

Comm 1200

Dr.Grau

3/13/23

Internet Protection Laws: Deepfake Technology Protection Policy

Internet laws, regularly called cyber laws, are a collection of legal regulations and principles that guide different parties on how they will use the internet. Unlike most other laws, internet laws differ from one jurisdiction to the other. Internet law is not also static. Changes in the technology field have made it necessary among parties interested in internet regulation to have left the option of ensuring that they provide the bare minimum requirements that would guide the technology industry rather than having definite positions (Savin, 2020, p.88-128). Internet laws stem from other forms of laws. One of the areas where Internet laws heavily borrow from contract and privacy laws. Like in any other field, several challenges are encountered in implementing internet laws, including the rise of deep fake technology.

Deepfakes use deep learning, a type of artificial intelligence, to make images that resemble actual events, but those events do not exist. There is an emerging concern among experts that deep fakes can be used as tools of misinformation or to spread fake news. In one of the most high-profile deep fakes, in 2018, a deep fake was realized depicting Barack Obama making a public service announcement (Electronica, n.d.). Recently, there has been an increase in the number of instances of deep fake technology. For example, according to the McAfeE report (Labs, 2018), from 2018 to 2019, there was an increase in the number of deep fake technology incidents by 900%. Legally speaking, deep fake technology has been used to invade the rights to privacy and individual reputation. It can also be used as a tool through which various criminal activities can take place. With these statistics, there is a dire need to evaluate the potential causes of the problem and synthesize a solution for the same.

The leading cause of deep fake technology is the use of AI. With the increased use of computer technology and AI there has been a surge in digital criminal activities, and deep fakes are not an exemption. Using deep learning algorithms, computer users have developed software that can effectively swap faces in videos so accurately that other people can't recognize the difference. Persons behind the deepfake videos need to establish a target video and then use auto-encoders to affect the face-swapping. The videos do not need to be related, and they can be randomly picked from the internet. Then the video developer uses the auto-encoders to create a convincing environment to persuade people that they are listening to or watching the acclaimed individual.

There are various ways through which deep fake technology can be controlled. Foremost, using technology-based solutions has proven to be one of the effective ways to control the problem. According to Labs (2018), coming up with deep fake-identification algorithms can help establish a solution to the problem. Blockchain technology and generative adversarial networks have been fronted as some of the best methods which can be used to detect and label deep fake videos. Appropriate legislation can also help in mitigating the problem. There is a need to create a multi-faced legal system that seals all the loopholes in the current internet laws (Savin, 2020). The technology field is faced with continuous changes, and those spearheading legislation on the same should ensure that they undertake appropriate measures to keep the legislative agenda on information technology-based issues open. Consultation on legislations on deep fake technology should be the guiding force of the government before it implements any law. Equally, it remains within the realm of the government that it should implement the laws that are formulated. Lastly, media literacy can also help the public appreciate the need to protect personal space. Policymakers should use the multi-faced approach to solving the problem in relation to deep videos.

References

Electronica. (n.d.). Obama Deep fake. https://ars.electronica.art/center/en/obama-deep-fake/

Labs, M. (2018, November 29). McAfee Labs 2019 Threats Predictions Report | McAfee Blog. McAfee Blog. https://www.mcafee.com/blogs/other-blogs/mcafee-labs/mcafee-labs-2019-threats-pre dictions/

Savin, A. (2020). EU internet law. Edward Elgar Publishing.