Digital evidence appears in nearly 90 percent of all crimes committed today.1 This is a massive increase. Only 20 years ago it was unusual to have digital evidence at the center of a case. It is now a big part of what juries and judges expect to see as part of the evidence that proves innocence or guilt. To learn more about how Microsoft technology can help, visit our booth 5410 at the International Association of Chiefs of Police (IACP) Annual Conference 2022 in Dallas, Texas from October 15 to 18.

With the widespread integration of AI in everyday and critical technologies, it seems inevitable to witness increasing instances of failure in AI systems. In such cases, there arises a need for technical investigations that produce legally acceptable and scientifically indisputable findings and conclusions on the causes of such failures. Inspired by the domain of cy-ber forensics, this paper introduces the need for the establishment of AI F orensics as a new discipline under AI safety. Furthermore, we propose a taxonomy of the subfields under this discipline, and present a discussion on the foundational challenges that lay ahead of this new research area. Introduction Recent advances in Artificial Intelligence (AI) have given rise to the rapidly growing adoption of such techniques by a vast array of industries and technologies.

Increased adoption of cloud applications, such as Dropbox and Google Drive, by private users has increased concern about use of cloud information for cybercrimes such as child exploitation, illegal drug trafficking and illegal firearm transactions. Researchers at Purdue University have developed a cloud forensic model using machine learning to collect digital evidence related to illegal activities on cloud storage applications. "It is crucial to detect illegal cloud activities in motion," said Fahad Salamh, a Ph.D. student in the Purdue Polytechnic Institute, who helped create the system. "Our technology identifies and analyzes in real time incidents related to these cybercrimes through transactions uploaded to cloud storage applications." Salamh worked on the technology with Marcus Rogers and Umit Karabiyik, professors in Polytechnic who specialize in computer and information technology.

Technology is infiltrating dispute resolution at multiple points in the litigation process, from claims portals to online dispute resolution (ODR) platforms to court modernisation. Attendees at this Gazette roundtable discuss the IT and cultural challenges of bringing civil justice online. Tony Guise, director of eARB and eCOURT platforms refers to chapter 43 of Lord Justice Jackson's Review of Civil Litigation Costs: Final Report, which defines effective information technology (IT) as'a central place to which and from which one can find all of the documents relating to a piece of civil litigation'. But in recent years litigation technology has broadened significantly from the document management and case management capability outlined by Lord Justice Jackson, into a confusing collection of online systems and applications that deal with various aspects of dispute resolution. Masood Ahmed, associate professor at the University of Leicester, defines litigation technology as the online processes for dispute resolution.

Police and prosecutors face a daunting task of identifying, managing and reviewing a veritable tsunami of digital evidence generated daily by officer bodycams, jail house calls, interrogation videos, dispatch calls and closed caption television, which stretches staffing capabilities and resources. Today, Vū Digital for Law Enforcement's A.I. capabilities deliver a robust and dynamic evidence management solution for law enforcement agencies worldwide. The layer recognizes and identifies events, keywords and sequences of words generated by Vū's automated tagging engine to tag and identify instances of significance, including confessions, identification of personal information and references to certain "trigger" words. "Data can exist without A.I., but not vice versa," said Wade Smith, vice president of operations for Vū Digital. "First, we create data where it otherwise didn't exist, then we apply an artificial intelligence layer to identify relevant events from the digital evidence. In the end, artificial intelligence is only as powerful as the data it considers."