Abstract

In today’s world there is a growing uncertainty in terms of the truthfulness of what we see and hear. People digest a great amount of information throughout the day using their devices, yet the quality and credibility of content is in question. People question if we are experiencing and perceiving the same reality at this point. This issue is not novel, however, it has progressed and developed to a level of realism that deceives people and affect their comprehension of information. Rapid technological advancement has raised the concern of what is referred to as “Deepfakes”, a machine learning technique that allows the manipulation of media content, including, videos, photographs and voice. In present time, deepfakes is considered as an issue that affects public trust and law enforcement, history has revealed that it developed and progressed with time, however we are unsure of what the future of deepfakes holds, it has a high uncertainty and impact on public trust and law enforcement. The policing sector common goal is to provide safety and security for citizens, therefore, proactive and reactive measures that are future oriented are important since the progression of crimes in the realm of artificial intelligence are accelerating. This paper aims to illustrate the future outlook for deepfakes and analyze its results’ using future foresight methods, including; the futures wheel, a swot analysis and scenario planning. The study will also examine the complex ethical, legal, and social issues surrounding the use of deepfakes on the policing sector through an interdisciplinary method that draws on theories of technology, criminology, and future foresight. The paper will conclude by providing recommendations for mitigating the risks of deepfakes, while highlighting the potential opportunities for leveraging this technology to enhance public safety and trust.

Library of Congress Subject Headings

Deepfakes--Forecasting; Deepfakes--Prevention; Law enforcement--Forecasting; Machine learning

Publication Date

8-2023

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Khalil Al Hussaeni

Campus

RIT Dubai

Plan Codes

PROFST-MS

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