Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. Instead of watching as non-banking organizations or fintech start-ups set expectations, the banking industry can now offer individualized engagement, integrating advanced analytics, artificial intelligence, machine learning, robotics and even blockchains to build a cognitive bank. The banking industry continues to be challenged be a low interest rate environment, intense competition from new market entrants, and heightened consumer experience expectations set by highly digital non-bank organizations. It is also proposed that cognitive systems can continually build knowledge and learning, providing the insight needed to increase efficiency and effectiveness throughout the organization.

Kevin Ashley is a Professor of Law and Intelligent Systems at the University of Pittsburgh, Senior Scientist, Learning Research and Development Center, and Adjunct Professor of Computer Science. He received a B.A. from Princeton University, New Jersey, a J.D. from Harvard Law School, Massachusetts and a Ph.D. in computer science from the University of Massachusetts. A visiting scientist at the IBM Thomas J. Watson Research Center, New York, NSF Presidential Young Investigator and Fellow of the American Association for Artificial Intelligence, he is co-Editor-in-Chief of Artificial Intelligence and Law and teaches in the University of Bologna Erasmus Mundus doctoral program in Law, Science and Technology.

Many AIs are trained to understand human language by learning from a massive corpus known as the Common Crawl. The Common Crawl is the result of a large-scale crawl of the Internet in 2014 that contains 840 billion tokens, or words. Princeton Center for Information Technology Policy researcher Aylin Caliskan and her colleagues wondered whether that corpus--created by millions of people typing away online--might contain biases that could be discovered by algorithm. To figure it out, they turned to an unusual source: the Implicit Association Test (IAT), which is used to measure often unconscious social attitudes. People taking the IAT are asked to put words into two categories.

The Digital Republic Bill recently gave a unique assignment to the French Data Protection Authority (CNIL) which is to lead a reflection on the ethical and societal matters raised by the rapid development of digital technologies. While algorithms are frequently at play in our everyday lives, only 31% of French people believe that they know precisely what it is all about*: the CNIL thus made the decision to open up in 2017 a large public debate on algorithms and artificial intelligence. Public institutions, associations, companies, research centers: around 40 partners take action to give body to this large and open public debate. Some of the partners of the wide public debate facilitated by the CNIL have favored a sector-based approach according to each of their fields of expertise. The outcomes of the growing use of algorithms will be analyzed for the justice system and the legal profession through several initiatives.

Based on this report's findings, it seems that the smaller firms have a slower rate of awareness and adoption than their colleagues at the bigger firms. Yet, arguably, smaller firms have as much if not more to gain from the rise of legal technology. Recent research from Thomson Reuters suggests that in a solo or smaller firm, up to 31% of their time is swallowed by administrative tasks with a resultant impact on their billable hours. The practice of trademark law tends to lend itself to repetitive, time consuming tasks. While the study didn't look specifically at different areas of law, it may well be that lawyers involved in trademark law carry a heavier administrative burden than some of their colleagues working in other fields.

To really understand the impact of artificial intelligence in the modern world, it's best to think beyond the mega-research projects like those that helped Google recognize cats in photos. According to professor Ajay Agrawal of the University of Toronto, humanity should be pondering how the ability of cutting edge A.I. techniques like deep learning--which has boosted the ability for computers to recognize patterns in enormous loads of data--could reshape the global economy. Making his comments at the Machine Learning and the Market for Intelligence conference this week by the Rotman School of Management at the University of Toronto, Agrawal likened the current boom of A.I. to 1995, when the Internet went mainstream. Gaining enough mainstream traction, the Internet ceased to be seen as a new technology. Instead, it was a new economy where businesses could emerge online.

"Artificial intelligence is as a weapon" and we have to deal with it "as we deal with other weapons," Cindy Smith, director of the United Nations Interregional Crime and Justice Research Institute (UNICRI), said during a panel discussion at an artificial intelligence summit in Geneva this week. The panel discussion focused on preparing a roadmap to ensure that artificial intelligence develops in "a safe, responsible and, an ethical manner" that benefits all the different segments of our society. Please login or subscribe to read the full story.

Editor's Note: This story was originally published on May 9, 2017. It has been updated to reflect developments including Uber's firing of 20 employees following an internal investigation into its corporate culture, as well as self-driving engineer Anthony Levandowski. If you haven't heard (maybe you've been toiling in Elon's tunnels?), Uber has had a rough start to 2017. The Department of Justice has launched a criminal probe into the company's use of "Greyball," a system it used to identify regulatory officials and block them from booking rides. In January, it lost riders who objected to CEO Travis Kalanick's (soon abandoned) seat on President Trump's economic council.

We met up with Jeh Daruvala, CEO of Yactraq, a machine learning company with cutting edge technology that delivers business intelligence using audible or video input. In layman terms, their patent pending technology can be used to accurately search through tens of millions of hours of call center recordings TV shows, movies etc. in a fast and cost effective manner in order to provide actionable insights and intelligence. Here is what he had to say about one of the most coveted spaces in technology. Q: Can you please tell us about your company and the specific challenge that you are addressing? Yactraq empowers SMB & Enterprise clients with machine learning driven insights extracted from any audible media.

Representing the pronoun we have Jacque Derrida and his creation Deconstructionism, our adverb is the thinker Ludwig Wittgenstein and the idea of'Language games'. Moreover, one sees this core value, or use of the pronoun – as being a very suitable metaphor for the Post-structuralist French philosopher Jacque Derrida's work. In his book On Grammatology, Derrida writes, 'Descartes's analyticism is intuitionist, that of Leibniz points beyond mani-fest evidence, toward order, relation, point of view' [5]. Especially when faced with another fact, We humans are the things that create meaning – meaning is not derived from the things we have created.