Tune in to this extraordinary edition of S.M.A.C. Talk Technology Podcast in which we examine how to become a disruptor (not disrupted!) in every industry Innovation itself isn't the entire challenge – pockets of innovation can be found in most any company, from the wildly successful to those that have failed spectacularly. The real challenge is being able to innovate at scale across an entire organization, all while creating a mechanism for those innovations to be shared, sustained, and to drive value back into the core of the business. In this series of podcasts, we'll explore how you can make that happen in your business. Listen in on these talks from your fellow innovators to discover how to embrace digital transformation and become a disruptor in your industry. More than 3,100 global executives took part in the most comprehensive global study of its kind, conducted by Oxford Economics.

Beth is a Senior Principal Technologist for Amazon Robotics. Beth has been Founder and CEO of several successful startups, most notably EXOS, Inc., which was venture capital backed and sold to Microsoft in 1996. Since then she has been involved in 30 start-ups in a variety of fields as a founder, investor, or advisor. She was an advisor and investor in Leap Frog and has been involved in entertainment and mobile companies. Beth is an acknowledged expert in VR, AR and the hand-device interface space and has been an expert in support of prior patent litigations.

In a statement, AP spokeswoman Lauren Easton said that AP journalists "met with representatives from the Department of Justice in an effort to get information on stories they were reporting, as reporters do. During the course of the meeting, they asked DOJ representatives about a storage locker belonging to Paul Manafort, without sharing its name or location."

It's almost comical how surprised we are at the pitfalls of artificial intelligence (AI). After all, we've been making movies for decades warning against the dangerous potential of sentient machines. And yet, the minute Facebook perpetuates foreign interference in a superpower's election or a Twitter bot becomes a marijuana-loving Nazi, we're shocked. And the reality is that our biases (political, racial and gendered) show in the data that we feed to our AI algorithms. As the COO of an AI-powered company that serves clients who also develop AI-powered products, I've come across the potential pitfalls of biased algorithms numerous times.

Whether it is facial recognition tech that is (allegedly) able to pick a wanted criminal out of a crowd of thousands or aerial drones which use image recognition smarts to predict fights before they take place, there is no doubt that we are living through a major paradigm shift for automated surveillance technology. But this kind of tech can have more grounded, everyday applications, too -- like helping prevent shoplifters stealing goods from their local mom-and-pop corner store. That is something seemingly demonstrated by a new artificial intelligence security camera called the "A.I. Guardman," built by Japanese telecommunication company NTT East and startup Earth Eyes Corp. The camera uses a special pose detection system to identify behavior it deems to be suspicious.

A newly launched AI Global Governance commission (AIGG), tasked with forming links with politicians and governments around the world to help develop and harmonise rules on the use of AI, has suggested that at least one key regulation should be that any decisions made by an AI system'must be tracked back to a person or an organisation'. Although the view was only the early product of meetings yesterday ahead of the AIGG launch event, which is backed by the UK Parliament's APPG AI group and the Big Innovation Centre, it could become something of a standard ethical line for the many legal projects now developing in this area. Earlier this month the Law Society launched its own Public Policy Commission on Algorithms and Justice, for example, one of several AI ethics initiatives around the world. Ensuring that any algorithmic decision is traceable and can be tracked back to a person or organisation could provide society with a greater sense that at least someone is responsible for the actions of an automated system, and that important decisions were not being made in a regulatory vacuum and without any recourse for legal action against a party that caused harm to another. In fact, one could argue that not being able to assign responsibility to the actions of an algorithm would in effect undermine the justice system and put AI's outputs on a par with'an act of nature', i.e. beyond the ability of society to apply rules. The AIGG meeting also stressed that regulators needed to move a lot faster than they are, nationally and globally, because AI technology and its use was now moving a lot faster in terms of its development and actual use in society.

'Insider Threat' is a formidable risk to business because it threatens both customer and employee trust. Accidental or malicious misuse of a firm's most sensitive and valuable data can result in customer identity theft, financial fraud, intellectual property theft, or damage to infrastructure. Because insiders have privileged access to data in order to do their jobs, it's usually quite difficult for security professionals to detect suspicious activity; a process even more challenging to automate (and deploy at scale across the large organisations that most need it) as – so I will suggest – computers fundamentally lack semantic understanding of the meaning of the'bits' they so adroitly process. Conversely, in this talk I will outline a new approach to'Insider Threat' detection that draws inspiration from the Traffic Analysis' of encrypted Axis signal traffic' undertaken at Bletchley Park in WW2. A novel approach that (i) conceives companies as complex autonomous autopoietic entities and (ii) deploys state of art computational analysis of the communication flows that so define the company to flag potentially aberrant employee behaviour; intelligence that can be leveraged to help detect HR problematics before they arise.

Silicon Valley has a long and secretive history of building hardware and software for the military and law enforcement. In contrast, a recent wave of employee protests against some of those government contracts has been short, fast, and surprisingly public--tearing through corporate campuses, mailing lists, and message boards inside some of the world's most powerful companies. The revolt is part of a growing political awakening among some tech employees about the uses of the products they build. What began as concern inside Google about a Pentagon contract to tap the company's artificial-intelligence smarts was catalyzed by outrage over Trump administration immigration policies. Now, it seems to be spreading quickly.

French startup Doctrine is raising a $11.6 million funding round (€10 million) from existing investors Otium Venture and Xavier Niel. Doctrine is building a search engine for court decisions and other legal texts. This is a key tool if you're a lawyer or you're working in the legal industry in general. There are now a thousand companies using the service. It currently costs around €129 per user per month.

"Man is still the most extraordinary computer of all" – so said John F. Kennedy in 1963. With recent developments in artificial intelligence (AI), some will question whether this statement still holds true. While computers have been used to assist with creative processes for some time, the creative input has largely been human. However, recent advances in machine learning software have changed all this. Using machine learning, computers now have the ability to'learn' without being explicitly programmed with any task-specific rules. As a result, AI is already writing new articles, poems and books, creating paintings and artistic works, producing video games, and composing music.