Benefits of Artificial Intelligence in the Legal System and Law Enforcement

Kuppala, Jishitha; Srinivas, Kandala Kalyana; Anudeep, P.; Kumar, R. Sravanth; Vardhini, P. A. Harsha

doi:10.1109/mecon53876.2022.9752352

Cited by 5 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These scenarios illustrate a dynamic that can exist in many Human-AI professional interactions, and illuminate the potential influences those interactions can have on peoples' creative agency. The same is true for engineers, students, writers, artists, lawyers, auto mechanics, medical research (Couzin-Frankel, 2019), law enforcement (Kuppala et al, 2022), and others. Yet, the consequences of AI integration don't end with any specific tasks or technical challenges, there are cumulative impacts as well.…”

Section: The Ai Context For Creative Agencymentioning

confidence: 93%

AI’s Influence on Human Creative Agency

Watkins,

Barak-Medina

2023

Preprint

View full text Add to dashboard Cite

Emerging AI capabilities are reshaping traditional creative problem solving roles, creating tensions in various professions. It is therefore time to begin examining the impacts of Artificial Intelligence (AI), including Generative AI (GenAI), on human creative agency. While AI presents challenges to creative agency, it also opens avenues for growth, necessitating a balanced approach to leverage its potential. To initiate a professional dialogue, we propose a framework outlining the influence of three aspects of AI on creative agency: whether the AI system’s perceived functionality is competing or complementing to human skills; the perceived effectiveness or level of performance of AI systems; and, whether the AI systems perform a high-stakes or a low-stakes function. The important moderating role of AI literacy on these three aspects is emphasized.

show abstract

Section: The Ai Context For Creative Agencymentioning

confidence: 93%

AI’s Influence on Human Creative Agency

Watkins,

Barak-Medina

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This procedure entails developing criminal profiles based on previous crime information and patterns. Clustering is critical in combining together crime occurrences with similar features, assisting detectives in comprehending modus operandi, locating probable criminals, and forecasting future criminal behavior [143].…”

Section: Criminal Profilingmentioning

confidence: 99%

A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective

Chaudhry,

Shafi,

Mahnoor

et al. 2023

Symmetry

View full text Add to dashboard Cite

Data mining is an analytical approach that contributes to achieving a solution to many problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable information from massive datasets. Clustering in data mining is used for splitting or segmenting data items/points into meaningful groups and clusters by grouping the items that are near to each other based on certain statistics. This paper covers various elements of clustering, such as algorithmic methodologies, applications, clustering assessment measurement, and researcher-proposed enhancements with their impact on data mining thorough grasp of clustering algorithms, its applications, and the advances achieved in the existing literature. This study includes a literature search for papers published between 1995 and 2023, including conference and journal publications. The study begins by outlining fundamental clustering techniques along with algorithm improvements and emphasizing their advantages and limitations in comparison to other clustering algorithms. It investigates the evolution measures for clustering algorithms with an emphasis on metrics used to gauge clustering quality, such as the F-measure and the Rand Index. This study includes a variety of clustering-related topics, such as algorithmic approaches, practical applications, metrics for clustering evaluation, and researcher-proposed improvements. It addresses numerous methodologies offered to increase the convergence speed, resilience, and accuracy of clustering, such as initialization procedures, distance measures, and optimization strategies. The work concludes by emphasizing clustering as an active research area driven by the need to identify significant patterns and structures in data, enhance knowledge acquisition, and improve decision making across different domains. This study aims to contribute to the broader knowledge base of data mining practitioners and researchers, facilitating informed decision making and fostering advancements in the field through a thorough analysis of algorithmic enhancements, clustering assessment metrics, and optimization strategies.

show abstract

“…That can read about human beings, starting from speech and face, meaning law enforcement processes centered on humans to resolve specific legal issues. This distinguishes the law enforcement process in the previous era from society 5.0, with the support of IoT technology and AI in the law enforcement process [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence of Internet of Things (AIoT) Technology-based Law Enforcement Process

Tarigan,

Sitepu

2023

IOTA

View full text Add to dashboard Cite

Technological developments are increasingly developing in all fields, unstoppable in the area of law and the role of this IoT technology in solving legal problems, considering Society 5.0, which focuses on building a humane and prosperous society, especially people in Indonesia. And the role of IoT on the legal side is expected to be the answer for an appropriate and fair law enforcement process. IoT Technology collaboration with all sectors of human life, for example, legal, social and economic, as well as natural resource factors and human resources, are still needed. IoT is expected to be a tool to achieve a level of accuracy, real-time, fast, and stability. In the era of Society 5.0, all aspects were asked to be fast so as not to be left behind in any sector; the ability factor of the human being, namely human resources, also determines whether a matter or case can be appropriately resolved. This article is one of the review articles on the role of IoT in law enforcement. Some parameters within the Internet of Things form Artificial Intelligence, Deep Learning, Big Data, and Machine Learning. Solutions with AI can be seen in the lie detection system.

show abstract

Benefits of Artificial Intelligence in the Legal System and Law Enforcement

Cited by 5 publications

References 17 publications

AI’s Influence on Human Creative Agency

AI’s Influence on Human Creative Agency

A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective

Artificial Intelligence of Internet of Things (AIoT) Technology-based Law Enforcement Process

Contact Info

Product

Resources

About