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.
“The federal government can help the U.S. maintain its leadership in AI by working closely with our experts in industry and academia, investing in research, and engaging with the international standards community,” said Under Secretary of Commerce for Standards and Technology and NIST Director Walter G. Copan. “This plan provides a path to ensure the federal government supports AI standards that are flexible and inclusive—and suited for a world of rapidly changing technologies and applications.”
As AI gains strategic importance, it is essential to shape global rules for its development and use. In promoting the development and uptake of AI, the European Commission has opted for a human-centric approach, meaning that AI applications must comply with fundamental rights. In this context, the rules laid down in the GDPR provide a general framework and contain specific obligations and rights that are particularly relevant for the processing of personal data in AI.
Research suggests that when it comes to evaluating entire documents, human translations are rated as more adequate and more fluent than machine translations. Human raters assessing adequacy and fluency show a stronger preference for human over machine translation when evaluating documents as compared to isolated sentences. This suggests that the way machine translation is evaluated needs to evolve away from a system where machines consider each sentence in isolation.