A new law in Illinois will regulate the use of artificial intelligence in job interviews. The Artificial Intelligence Video Interview Act, House Bill 2557, requires companies to notify the applicant when the system is being used, explain how the AI works, get permission from the applicant, limit distribution of the video to people involved with the process and to destroy the video after 30 days. Matthew Jedreski, counsel at Davis Wright Tremaine LLP in Seattle, is a litigator and employment attorney who updates clients on local and state employment laws. Jedreski said AI video interviews apply psychometrics, which is the science of measuring attitude and personality traits. "It's reading data and then analyzing it to determine whether it can draw conclusions about the person being interviewed," Jedreski said.

Understanding how my GPS works doesn't prevent it from degrading my map reading skills. Any skill you don't practice gets rusty. As Dunning-Kruger tells us, the more sure we are about our understanding the less understanding we are likely to have. AI that tells us what we already think to be true may well be simply crystallizing our biases in a non-disputable form. For example there was an article a few months back in Technology Review about using AI to (a) decide which convicted criminals to incarcerate based on an AI-generated "recidivism score", and (b) the use of AI to direct police to places where crime is most likely.

Natural Language Processing (NLP) is a massive space within artificial intelligence (AI), which enterprises are integrating into their existing platforms more each day. As petabytes of textual data become available each day, companies can leverage NLP to retrieve deeper insights. Aspects such as entities, sentiment, emotion, and keywords can be extracted from textual data and enterprises can leverage this information to pivot, understand customer sentiment, and improve internal efficiency. Watson Natural Language Understanding (NLU) and Watson Natural Language Classifier (NLC) are cutting-edge NLP technologies that provide deep insight into textual data. Watson NLU provides insight such as entities, emotion, keywords, sentiment, and categories, while Watson NLC allows users to train a classification model in under 15 minutes and classify text.

SAN FRANCISCO--Guiding Oracle's development of its latest generation of cloud applications are three main business imperatives: help customers innovate rapidly, create nimble processes, and make the most of their mobile, social, and other communications channels. Speaking at Oracle OpenWorld, Steve Miranda, executive vice president of applications development, emphasized the considerable work the company has done incorporating machine learning algorithms into its comprehensive, tightly integrated suites of cloud applications. "We're ready to run your business in the cloud," Miranda said. At Oracle OpenWorld, Steve Miranda, Oracle's executive vice president for applications development, outlines machine learning capabilities in the company's cloud applications. An intuitive, easy-to-use, voice-enabled user interface that runs on various computing platforms but is especially suited to mobile devices.

The phrase "artificial intelligence" in pop culture often conjures up dystopian images such as the sentient computer Hal 9000 from the 1968 film "2001: A Space Odyssey" that killed people for its self preservation; or the cyborg assassin with a metal endoskeleton in director James Cameron's "The Terminator." In recent years, our fascination with the potential of AI has taken a more starry-eyed turn, as shown in the 2013 sci-fi drama "Her," where the main character falls in love with a virtual assistant. In reality, artificial intelligence (AI) technology is quickly permeating every aspect of our lives. From Amazon's voice-activated Alexa to writing technology that helps managers craft job postings, AI is in our hearts, homes and workplaces. And it's only going to become a bigger part of our lives: Experts call the rise of AI the driving force behind the fourth industrial revolution. On a recent afternoon at the NVIDIA robotics research lab in Seattle's University District, researchers use a simulated kitchen to test robots' ability to perform simple tasks such as grabbing objects.

An employer in Spain may not be able to fire a worker caught on a surveillance camera doing something prohibited if the company hasn't informed workers about the video system and its purpose, according to a recent trial court decision. In a case involving an employee fired after a security camera captured him in a parking-lot fight after work hours, a Pamplona labor court ruled that the video evidence was inadmissible under the European Union's General Data Protection Regulation (GDPR) and case law from the European Court of Human Rights (ECHR). "The judgment is of great interest since it is the first ruling by a Spanish court on the validity that can be given to the evidence of video recordings after the publication of the new Spanish Data Protection Law and also an interpretation of the new European Data Protection Regulation," according to a blog post from Manuel Vargas of Barcelona's Marti & Associats law firm. Under Spain's own data-protection law, employers who record a worker doing something illegal are considered to have fulfilled their duty to inform so long as they have posted a sign identifying a video surveillance zone, Vargas wrote. He also noted that recent case law from the Spanish Supreme Court endorses the idea that employers aren't obligated to notify workers that they plan to use video cameras to monitor their activity for possible disciplinary purposes.

The ever-hastening progress of legal technology continues to push law firms to a future where lawyers can do more than ever before, in a manner so efficient that the value being offered to clients is beyond compare. Although practice management, document management, and even legal research platforms have incorporated artificial intelligence and machine learning into their offerings, not all law firms have gotten on board with the new capabilites that this technology has made available to them. Blue J Legal wants to help demystify the many ways lawyers can leverage AI and machine learning in their practices to improve results for clients. It's unlikely that machines will ever replace lawyers, but one thing is becoming clear: lawyers who use artificial intelligence will replace lawyers who don't. Sign up below to join "Exploring artificial intelligence and the law," an on-demand webinar hosted by Blue J Legal's COO, Avi Brudner.

To judge from business book bestseller lists and recent popular conference topics, the question'how can artificial intelligence (AI) improve the way we work?' has become a major topic of interest in today's economy--and in the field of IP law, too. Clear trends are now emerging on how lawyers should be adopting these technologies to improve performance--and success stories abound. For example, many trademark professionals report having used AI to completely reimagine their traditional work processes, with positive effects. Today's programmers are using many different AI techniques--including expert systems, machine learning, deep learning neural networks, natural language processing, and voice and image recognition--to drive better business performance. AI is evolving very quickly and proving very valuable, across many different industries and in the field of law.

On August 9, 2019, the National Institute of Standards and Technology (NIST) released "U.S. Leadership in AI: A Plan for Federal Engagement in Developing.