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73 I L T A N E T . O R G A dvances in artificial intelligence (AI) are impacting industries worldwide, transforming how we do business, manage workloads, and advance with technological tools. The legal sector is no exception. We can identify ways that AI and automatic speech recognition software are changing the processes for how courts, attorneys, and court reporters preserve and interpret records. AI-powered software is a game-changer when it comes to collecting and analyzing digital evidence. It enables legal professionals to navigate through vast amounts of complex data, such as emails, computer documents, text messages, and audio and video files, with unprecedented speed and efficiency. This is a stark contrast to the previous labor-intensive, error-prone processes that relied heavily on high-quality audio and video. Digital evidence plays a crucial role in understanding the facts of any case, and AI (and generative AI) can play an essential role in collecting that evidence. By effectively and accurately analyzing large volumes and different types of evidence, identifying critical information, extracting insights, and overcoming the limitations of poor-quality audio and video data, AI is revolutionizing legal investigations, saving time and resources. While AI can provide valuable insights, it's crucial to ensure the data fed into the program is valid and accurate. The reliability of AI's outputs is directly proportional to the quality of the information it processes, underscoring the importance of data accuracy in AI-driven processes. AI's Role in Capturing Digital Evidence Identifying and categorizing relevant information within digital evidence's massive datasets can be daunting, requiring a combination of advanced technological tools and human oversight. And like physical evidence, digital evidence must be handled carefully to ensure its usefulness during legal proceedings and criminal investigations. Effective digital evidence capture is crucial, yet it presents significant challenges for attorneys. Below are a few examples of digital evidence, its challenges, and how AI can assist. • Text Documents: The volume and diversity of text documents – PDFs, emails, Slack messages, Teams chats, social media posts, etc. – make capturing and processing this data challenging. Extracting information from various sources, especially email attachments, poses a significant hurdle, and once captured, organizing and categorizing the data for future searchability is another complex task. AI and machine-learning algorithms can quickly pore through large amounts of textual data, sorting, categorizing, and filtering information, highlighting key details, identifying patterns, and sometimes detecting sentiment or intent, which might "The reliability of AI's outputs is directly proportional to the quality of the information it processes."

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