A £10 million innovation fund has been unveiled to'lay the groundwork' for a future of flying cars and ethical robot lawyers. Business secretary Greg Clark has today (5 October) announced the 15 winning bidders for the government's Regulators' Pioneer Fund. The cash will be given to UK regulators to help drive forward innovation in the public sector and help it seize long-term opportunities like the growth of AI and the future of mobility. A £700,000 grant has been given to the Solicitors Regulation Authority to help the development of AI legal services for small businesses – dubbed'robolawyers'. The SRA's chief executive, Paul Philip, said AI services could widen access to legal services.

The sportswear giant Nike, which has a contract reported to be worth $1bn (£768m) with Cristiano Ronaldo, says it is "deeply concerned" by rape allegations against the footballer. It adds that it will "closely monitor" the situation. Ronaldo, who plays for Juventus and Portugal, denies assaulting former teacher Kathryn Mayorga at a Las Vegas hotel in 2009. Ms Mayorga has said she was inspired to speak out by the #MeToo movement. Meanwhile, another Ronaldo sponsor, the games company EA Sports, called the report detailing allegations against him "concerning".

An NBER conference on Economics of Artificial Intelligence took place in Toronto on September 13-14, 2018. Research Associates Ajay K. Agrawal, Joshua S. Gans and Avi Goldfarb of University of Toronto and Catherine Tucker of MIT organized the meeting, sponsored by the Alfred P. Sloan Foundation, CIFAR, and the Creative Destruction Lab. These researchers' papers were presented and discussed: Emilio Calvano, Vencenzo Denicolò, and Sergio Pastorello, University of Bologna, and Giacomo Calzolari, European University Institute Q-Learning to Cooperate AI algorithms are increasingly replacing human decision making in real marketplaces. To inform the debate on potential consequences, Calvano, Calzolari, Denicolò, and Pastorello run experiments with AI agents powered by reinforcement learning in controlled environments (computer simulations). In particular, the researchers study multi-agent interaction in the context of a workhorse oligopoly model: price competition with Logit demand and constant marginal costs.

The Library of Congress, along with basically everyone else, is interested in exploring what artificial intelligence and similar technologies can do for its mission. The library devotes an entire section of its new Digital Strategy document to its intention to "invest in our future," through ongoing IT modernization and, more nebulously, "innovation." "In addition to the Library's ongoing investments in IT modernization, we will encourage a culture of continuous learning and capacity for innovation," the strategy states. "We will engage with new technologies and communities." Specifically, the library imagines, emerging technologies like computer vision, natural language processing and machine learning have the capacity to "streamline" the work of staff and increase impact.

Something is materially broken with web application security and, as a result, critical attacks are being missed. According to a new report from Kaspersky Lab, 73 percent of corporate network breaches in 2017 were achieved via vulnerable web applications. There are a variety of factors contributing to the problem: resource constraints, concerns over false positives and the sheer volume of the attack surface. The good news is that machine learning can be applied to help overcome these issues and strengthen application security. Most companies are failing to harness the full power of machine learning.

Trained machine learning models are increasingly used to perform high-impact tasks in areas such as law enforcement, medicine, education, and employment. In order to clarify the intended use cases of machine learning models and minimize their usage in contexts for which they are not well suited, we recommend that released models be accompanied by documentation detailing their performance characteristics. In this paper, we propose a framework that we call model cards, to encourage such transparent model reporting. Model cards are short documents accompanying trained machine learning models that provide benchmarked evaluation in a variety of conditions, such as across different cultural, demographic, or phenotypic groups (e.g., race, geographic location, sex, Fitzpatrick skin type) and intersectional groups (e.g., age and race, or sex and Fitzpatrick skin type) that are relevant to the intended application domains. Model cards also disclose the context in which models are intended to be used, details of the performance evaluation procedures, and other relevant information. While we focus primarily on human-centered machine learning models in the application fields of computer vision and natural language processing, this framework can be used to document any trained machine learning model. To solidify the concept, we provide cards for two supervised models: One trained to detect smiling faces in images, and one trained to detect toxic comments in text. We propose model cards as a step towards the responsible democratization of machine learning and related AI technology, increasing transparency into how well AI technology works. We hope this work encourages those releasing trained machine learning models to accompany model releases with similar detailed evaluation numbers and other relevant documentation.

Data analytics, cloud and cyber security are the key technologies for CIOs today – but a fair proportion are looking at artificial intelligence (AI) and machine learning. That is the primary finding from a study by Trace3, a provider of, well, cloud, cybersecurity, and machine learning software. Never mind that however – the statistics from the study, which featured more than 200 responses from the C-suite, as well as vice presidents and directors, are still of interest. Two thirds (67%) of CIOs polled said technology was a'business enabler', with data analytics the most important category for business transformation, cited by 74% of respondents. Cloud (64%), cybersecurity (63%), and AI (44%) were also frequently cited.

The Department of Transportation is getting a little more creative about how it defines "driver," Secretary Elaine Chao announced Thursday. In the third version of the department's official stance on self-driving, the department said it would "adapt the definitions of'driver' and'operator' to recognize that such terms to not refer exclusively to a human, but may in fact include an automated system." The computers have a ticket to drive now--at least where federal regulations are concerned. And while this is good news for everyone working on building, and eventually deploying, self-driving vehicles, it's especially welcome for the automated trucking crowd. Waymo, Daimler, Volvo, Embark Trucks, Kache.ai,

Federal officials overseeing billions in benefit payments to millions of Canadians are hoping artificial intelligence can resolve ongoing snags in the system. The government is looking to "push the boundaries" of what artificial intelligence can do to improve a variety of services, including the pace of benefit decisions to Canadians applying for disability pensions, say documents obtained by The Canadian Press under the access to information law. Employment and Social Development Canada is currently facing processes that are "slow, inefficient, inconsistent, and prone to error," reads a presentation about the AI efforts. Instead of being able to proactively change the way federal services are delivered to Canadians, the documents say, officials are bogged down with millions of "low value" issues that need to be taken care of, crowding out more critical work. Among the "low value" work are about 50,000 tasks required to issue tax forms to Canada Pension Plan and old age security recipients.

This is the last article in a three part series on AI law. Previously in parts one and two, I discussed the AI as tortfeasor and how traditional tort theories may apply to semi-autonomous AI, and I discussed how state and foreign regulators are taking AI bias and the protection of consumers seriously. Federal regulators are beginning to grapple with these issues also. Our discussion of AI Law turns now to the topic of robo-advisors, AI speech and AI legislations before Congress. Chat bots and voice bots are AIs that interact with people using spoken and the written word.