Artificial Intelligence (AI) is influencing people’s everyday lives and playing a key role in digital transformation through its automated decision-making capabilities. The benefits of this emerging technology are significant, but so are the concerns. In this recent report, The EU Agency for Cybersecurity (ENISA) warns that AI may open new avenues in manipulation and attack methods, as well as new privacy and data protection challenges.
According to Dave Deppe, president of UnitedLex, “To fill the void in preexisting legal technology, UnitedLex has developed a significant library of custom-tailored AI solutions for our clients based on their industry, types of litigation, investigations and regulatory demands. Combining our 13 years of development in Questio and Vantage with a powerful suite of technology assembled by Reveal, we will accelerate the expansion of the digital solutions we deliver to our clients.”
According to Wendell Jisa, founder and CEO of Reveal, “This solution confirms that a combination of AI technology and human legal expertise can solve complex issues such as cartel activity detection. Our platform allows DLA Piper’s Aiscension to build powerful AI models to meet their client’s needs. Aiscension will apply these AI models to future cases. Our partnership with DLA Piper allows lawyers to work hand-in-hand with data scientists – continuing Reveal’s mission to further the impact of automation in the practice of law.”
Published originally on Independence Day in Estonia, the vision and concept paper “#KrattAI: The Next Stage of Digital Public Services in #eEstonia” highlights one country’s practical vision for how public services should digitally work in the age of artificial intelligence. Released by the Republic of Estonia GCIO Office and authored by the Government CIO, CDO, and CTO, the paper presents commentary and considerations for the problems, business challenges, and technological challenges involved integrating AI into public services. The vision and concepts shared may be useful for data discovery and legal discovery professionals as they consider plans, projects, and programs relating to the practical application of AI in their infrastructures and offerings.
Based on recent advances in artificial intelligence (AI), AI systems have become components of high-stakes decision processes that ultimately require a level of trust for user confidence. This draft publication and solicitation for comment from NIST highlights the importance of user trust in considering AI decisions and presents four principles for explainable AI, principles designed to capture a broad set of motivations, reasons, and perspectives regarding outputs from AI systems.
Recently published by the European Commission, the white paper “On Artificial Intelligence – A European Approach to Excellence and Trust” presents a human-centric approach to the development of AI that is worth reading and reflection by data discovery and legal discovery professionals as they consider legal, ethical, and commercialization issues and opportunities relating to AI.
As shared by Steve McNew, an MIT trained blockchain/cryptocurrency expert and senior managing director at FTI Consulting, “Online videos are exploding as a mainstream source of information. Imagine social media and news outlets frantically and perhaps unknowingly sharing altered clips — of police bodycam video, politicians in unsavory situations or world leaders delivering inflammatory speeches — to create an alternate truth. The possibilities for deepfakes to create malicious propaganda and other forms of fraud are significant.”
In her recent article, “Fighting Fake News with Blockchain,” e-Estonia Briefing Centre Communication Manager Mari Krusten highlights how the innovative use of blockchain can help in ensuring data integrity and serve as a trustworthy tool for addressing challenges ranging from alternative facts to deepfakes.
“It’s now recognized that systems aren’t unbiased. They can actually amplify existing bias because of the historical data the systems train on,” said Ellen Voorhees, a NIST computer scientist. “The systems are going to learn that bias and recommend you take an action that reflects it.”
The emergence of ML and AI is already shaping society, political systems and our economies. The underlying assets driving such changes are largely informational. Access and licensing of data can thus be understood as one of the cornerstone of the development of ML and AI. This is true in an abstract sense, but when combined to the fact that there exists a widening data gap between multinational firms with platform-based business models on one hand, and governments, citizens and other businesses on the other, the need for clarity in data licensing becomes imperative.