Artificial intelligence assistants in legal practice: enhancing productivity while preserving human expertise

Authors

  • Iris Shehaj

DOI:

https://doi.org/10.55312/op.vi2.6171

Abstract

The industrial revolution marked a fundamental change in history as physical work became increasingly automated, leading to the replacement of muscle power by machines. However, in the modern era, a new revolution is underway—the AI-powered revolution—which is transforming the nature of work by automating mental tasks. From being mere science fiction in the past, it has now become a real practice, playing an important role in the field of law. This paper will address how legal practitioners conduct research, manage documents, conduct defense, and even how trials are conducted in the courtroom. The research process went through three phases, which included data collection, analysis of the main findings and elaboration using a qualitative research methodology, which includes literature review, case studies from practice, and aims to present the new opportunities that AI offers. However, the application of AI also presents new challenges such as algorithmic biases, the fallibility of AI systems, the violation of personal data, and the need for new regulatory frameworks. Questions about accountability, legal liability, and whether AI technology could replace human lawyers and undermine the expertise and judgment that legal professionals bring to their work are causing an intense debate. With the development of artificial intelligence on the rise, this paper aims to further explain what artificial intelligence is and how it is currently being used in the legal field.

Keywords:

Artificial Intelligence (AI), legal technology, legal professions, robot judges, legal practice, algorithmic biases

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Author Biography

Iris Shehaj

Shkolla e Avokatisë së Shqipërisë, Dhoma Kombëtare e Avokatisë

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Published

2024-12-20

How to Cite

Shehaj, I. (2024). Artificial intelligence assistants in legal practice: enhancing productivity while preserving human expertise. Optime, (2), 326–333. https://doi.org/10.55312/op.vi2.6171

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