Applied Project

How Artificial Intelligence is Affecting Child Sexual Abuse Material

Masters Applied Project

Meggie Williams

Dr. Dallas Augustine - JS 274

27th of March 2024

MS in Criminology, Global Criminology Concentration

Acknowledgment

This is an incredibly sensitive topic that has affected many people person. By conducting this research, it has created many beneficial conversations in local and federal government agencies. Many thanks to everyone who was involved and all the interviewees.

Meggie Williams

Index

1.

Summary

7.

Theoretical Framework

2.

Introduction

8.

Methods

3.

Review of Literature

9.

Discussion

4.

Child Sexual Abuse Material

10.

Conclusions

5.

Characteristics of Offenders and Statistics

11.

References

6.

Artificial Intelligence

1. Summary

Overview of Presentation

Why this topic? Who does it benefit? How does this impact the community?

Questions to think about:

How is AI advancing the world of CSAM and VCAC? What would the future look like?

Keywords:

CSAM, AI, and Technology.

2. Introduction

Technological Advancements - Artificial Intelligence and the New Digital Age

• Evolution of technology
• Cybercrimes - Technology-enabled crime
• Digital Devices
• Negative Phenomenon

NegNeg

3. Review of Literature

Review of Literature

These next sections will include the following topics:

• Child Sexual Abuse Material (CSAM)
• Characteristics of Offenders and Statistics
• Artificial Intelligence (AI)

4. Child Sexual Abuse Material

Child Secual Abuse Material (CSAM):

Child Sexual Abuse Material is also commonly referenced as CSAM

Issues that have Arised

Supreme Court Cases

Recognized since 1970

First Amendment Fourth Amendment

Miller v California (1973) Osborne v Ohio (1990)

What does this mean?

5. Characteristics of Offenders and Statistics

Law enforcement has primarily focused on the trafficking of child pornography and the concomitant use of the internet by pedophiles who are interested in the circulation of images and videos of children involving explicit, aggressive, and abusive acts.

Key Acts:

• Criminal Justice Act 1988
• Protection of Children Act 1978 Project Safe Childhood (PSC)
• U.S. Attorneys’ Offices and the Criminal Division’s Child Exploitation and Obscenity Section (CEOS)

6. Artifical Intelligence (AI)

Field Work

This impacts multiple areas such as civil law, namely tort law, contract law, antitrust law, criminal law, and consumer protection law

Types of AI Models:

• Balaboba
• GigaChat
• Kandinskiy 2.0

7. Theoretical Framework

Theoretical Framework

Uncovering CSAM as early as possible is crucial for the prevention and detection of CSAM

Only about 50% of CSAM survivors disclose before adulthood

Juveniles and Mental Disorders

Government and non-government agencies, there have been many systemic failures

8. Methodology

Interviews

This section is based on semi-structured interviews with local police officers working the violation and Federal agents working the same violation.

Instruments

The following interviews consisted of 20 questions emphasizing law enforcement officers. This interview examines whether local, state, and federal law enforcement have seen Artificial Intelligence (AI) within their field

9. Discussion

The victims of child pornography have endured unimaginable long-term harm.

60%

With the enhancements of the internet, black market, and dark websites CSAM is widely available Four primary categories of dilemmas for law enforcement agencies

Responded and Agreed to the Interview

10. Conclusions

ARREST RATES

MANDATORY MINIMUM SENTENCING

POLICIES

11. References

Bibliographic references

Artificial intelligence. (2018). Grey House Publishing.Artificial intelligence : concepts, methodologies, tools, and applications. (2017). Information Science Reference. https://doi.org/10.4018/978-1-5225-1759-7 Babchishin, K. M., Eke, A. W., C. Lee, S., Lewis, N., & Seto, M. C. (2022). Applying Offending Trajectory Analyses to Men Adjudicated for Child Sexual Exploitation Material Offenses. Criminal Justice and Behavior, 49(8), 1095–1114. https://doi.org/10.1177/00938548211040849 Bissias, G., Levine, B., Liberatore, M., Lynn, B., Moore, J., Wallach, H., & Wolak, J. (2016). Characterization of contact offenders and child exploitation material trafficking on five peer-to-peer networks. Child Abuse & Neglect, 52, 185–199. https://doi.org/10.1016/j.chiabu.2015.10.022 Blackburn, Ossoff Launch Bipartisan Inquiry to Address AI-Generated Child Sex Abuse Material Online. (2023). In Targeted News Service. Targeted News Service. Brudvig, D. (2015). Today’s Tool For Interpreting Yesterday’s Conviction: Understanding The Mandatory Statutory Sentence Enhancement In Federal Child Pornography Cases. Wisconsin Law Review, 2015(1), 153–179. Crosson-Tower, C. (2002). Understanding child abuse and neglect (5th ed.). Allyn and Bacon. Edwards, S. S. M. (2000). Prosecuting “Child Pornography”: Possession And Taking Of Indecent Photographs Of Children. The Journal Of Social Welfare & Family Law, 22(1), 1–21. https://doi.org/10.1080/014180300362732 Eleventh Scandinavian Conference on Artificial Intelligence: Scai 2011, edited by A. Kofod-Petersen, et al., IOS Press, Incorporated, 2011. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/sjsu/detail.action?docID=784588. Federal Sentencing Of Child Pornography : Non-Production Offenses. (2021). United States Sentencing Commission.

Last Name Last Name, Author (20XX). Place of publication: Publisher.

Thank you!

Any questions?