Law firms should do more to share the benefits of artificial intelligence technology with their clients, according to a new report revealing what GCs really think about AI. The report, AI: The new wave of legal services, produced by Legal Week Intelligence and Bird & Bird, is based on 15 interviews with senior in-house lawyers, covering subjects including their current and potential use of technology, the opportunities and challenges presented by AI, and how it will shape their expectations of the law firms they instruct. The report reveals that many GCs would like a more proactive stance from law firms in sharing the potential benefits of AI – through testing to implementation and cost savings. KPMG general counsel Jeremy Barton argues that AI should be a catalyst for law firms and GCs to work more closely together: "What is going to change is the nature of collaboration with law firms. We pay law firms too much for doing basic research. "You could easily envisage getting to a stage where the only law firms you really want to deal with, as in-house counsel or general counsel, are those who share a platform with you, or are prepared to use your platform so that your collaboration is supported by technology that is common between you and the law firm." Claire Debney, director of legal strategy at FTSE 100 pharma company Shire, agrees. "Law firms should be more collaborative in their use of technology," she says. "When they look at the client relationship, you have your relationship partner and your regular review.

Mozilla has long been one of the strongest champions for openness in technology -- from the software it produces to the web standards it adopts. As new technologies emerge, the battle over closed versus open systems continues to be one of the most important factors for a range of concerns that are critical to a healthy information ecosystem -- innovation, competition, privacy, security, consumer protection -- and even civil rights. With new advances in artificial intelligence -- particularly in the fields of machine learning and sensor technology -- questions of "open" versus "closed" have arisen again. However, what is becoming quickly clear is that the traditional open strategies, such as permissive licensing and code/documentation publication, may not work as well or even at all. Consider deep learning, one of the key AI techniques driving advances such as automated speech recognition.

Over the summer, a software engineer was sentenced to 40 months in prison for his role in helping Volkswagen evade pollution control rules. Earlier this month, the Pew Foundation reported that 85% of the public would support regulation to restrict the use of AI by businesses and organizations. These stories suggest powerful reasons for tech companies to do the right thing. But, beyond the fear of legal action or adverse public opinion, companies are also fully aware of the ethical implications of the AI-algorithms they create. Tech companies are actively seeking principles to guide them through these ethical challenges.

From June 7–9, an important conference on artificial intelligence took place in Geneva. Called AI for Good Global Summit, many parties with an interest in the AI boom discussed how to ensure the technology is used for many different purposes, not only profit. Everyone from Amnesty International and the World Health Organization to IBM, Google and Microsoft, examined the ethical, technical, societal and policy issues related to AI. The goal was to "offer recommendations and guidance, and promote international dialogue and cooperation in support of AI innovation." The conference was broadcast live worldwide so anyone with an interest in AI could e-attend.

AI is applicable to your industry as well. Even if you don't use it in your every day business, having an AI-based platform to automate tedious activities is both time-saving and cost-effective. AI has no bias and can also be used to take human error out of the equation. For example, most companies have a legal team, and they can use an AI-based archiving service to capture web and social content for a litigation.

Algorithmic decision making process now affects many aspects of our lives. Standard tools for machine learning, such as classification and regression, are subject to the bias in data, and thus direct application of such off-the-shelf tools could lead to a specific group being unfairly discriminated. Removing sensitive attributes of data does not solve this problem because a \textit{disparate impact} can arise when non-sensitive attributes and sensitive attributes are correlated. Here, we study a fair machine learning algorithm that avoids such a disparate impact when making a decision. Inspired by the two-stage least squares method that is widely used in the field of economics, we propose a two-stage algorithm that removes bias in the training data. The proposed algorithm is conceptually simple. Unlike most of existing fair algorithms that are designed for classification tasks, the proposed method is able to (i) deal with regression tasks, (ii) combine explanatory attributes to remove reverse discrimination, and (iii) deal with numerical sensitive attributes. The performance and fairness of the proposed algorithm are evaluated in simulations with synthetic and real-world datasets.

We are moving rapidly towards a world where robots and artificial intelligence (AI) systems are connected to and influenced by social media, the Internet of Things (IoT) and big data. Technological developments are moving fast, and AI has many governments concerned. Given the pace of technological advancement, how do rule-makers set legislation for AI while allowing the safe evolution of technology? Who thinks about and enforces these guidelines, and what work is being done, or should be done, with governments to craft AI policy? Moves by the European Parliament to consider granting some form of legal status to AI have revived questions of liability and responsibility.

Alphabet Inc's Waymo sought at least $1 billion in damages and a public apology from Uber Technologies Inc as conditions for settling its high-profile trade secret lawsuit against the ride-services company, sources familiar with the proposal told Reuters. The Waymo self-driving car unit also asked that an independent monitor be appointed to ensure Uber does not use Waymo technology in the future, the sources said. Uber rejected those terms as non-starters, said the sources, who were not authorized to publicly discuss settlement talks. Waymo sued Uber in February, claiming that former engineer Anthony Levandowski downloaded more than 14,000 confidential files before leaving to set up a self-driving truck company, called Otto, which Uber acquired soon after. The precise dollar amount requested by Waymo and the exact time the offer was made could not be learned.

A new trademark application filed by Nintendo has ignited rumours of an impending Game Boy launch. The company recently released new mini versions of the NES Classic and SNES Classic, so the Game Boy speculation isn't quite as farfetched as it might initially appear. The application, which was submitted on 15 September, was accompanied by an image of the Game Boy. It was spotted by a Japanese trademark bot, which tweeted it into the public consciousness. It isn't clear if Nintendo plans to re-release it, but with the 30th anniversary of the original Game Boy's release coming up in 2019, such a move certainly isn't out of the question.

If we imagine the future job market as an ecosystem, it will be one populated by both workers and robots. Jobs are evolving rapidly and almost half of them are susceptible to automation. Particularly at risk are not only occupations involving routine, and in manufacturing, which are easily replicable by computer algorithms, but also non-routine tasks. These include a wide range of jobs, from legal writing, and sales, to car driving, and medical diagnoses. This has been seen as a threat to employment in the future, and has stoked fears of a jobless growth economy. Whether these fears are justified or not, some questions are worth exploring: in this unpredictable scenario, who are the ones who are going to survive?