There is a clear, algorithmic formula for writing books about technology and society in 2018. Authors are generally required to be male, their documented personal journey must have been from that of techno-optimist to techno-sceptic to techno-panicker. There must be an urgent existential threat to either democracy or humanity lurking in the code base of Silicon Valley companies. The intractable crisis is not so profound, however, that it cannot be solved by a hail of partially thought-through remedies tacked on in the appendix. This recipe is producing a growing body of what might be termed "techlash" literature: the backlash against Silicon Valley and its seemingly unstoppable accretion of wealth, data and cultural and political capital.

An influential body of U.K. lawmakers said regulators should stop major tech companies from dominating the field of artificial intelligence, and also … British antitrust regulators should be mindful that large datasets on which artificial intelligence depends on are not monopolized by a handful of large …

The House of Lords Select Committee on Artificial Intelligence has asked the Law Commission to investigate whether UK law is "sufficient" when systems … comes as part of a report by the 13-member committee on the "economic, ethical and social implications of advances in artificial intelligence".

AI is becoming integrated in the digital systems that are part and parcel of our everyday lives. While the technology brings unprecedented opportunities, it is set to reconfigure power relationships within societies and among states; challenging human rights, deepening inequalities, and undermining international governance regimes. These disruptions are important for Global Affairs Canada as they affect Canada's ability to meet its international commitments and obligations related to human rights, inclusion, and democracy. Indeed, reports about biased AI systems fuelling discrimination and facilitating unequal access to services and information are ubiquitous. The role of AI technologies in undermining liberal democracy; eroding privacy; and interfering with human rights and freedoms, such as gender equality, freedom of expression and freedom of assembly, is also becoming troublingly apparent.

The Bridges and Tunnels Division of the New York Metropolitan Transportation Authority (MTA) is embarking on a chatbot pilot project called the Collision Accident Reporting System (CARS). The program is a partnership with Oracle, and will deploy a chatbot for agency employees allowing them to report and document accidents via their smartphones. It will also give managers the ability to examine accident hot spots and make decisions about rebuilding problem infrastructure. With 10 bridges and tunnels throughout Manhattan, connecting commuters to upstate New York, Connecticut and New Jersey, the agency's daily undertaking is daunting. While the MTA moves millions of people every day on buses and trains, the Bridges and Tunnels Division is responsible for all vehicles that drive into or out of the city.

Ethics should be at the centre of the development of artificial intelligence (AI), a parliamentary report has said. AI should "never" be given the "autonomous power to hurt, destroy or deceive" people, it adds. The Lords' report said the UK has the potential to be a leader in developing AI and called on the government to support businesses in the field. It also recommended that people be educated to work alongside AI in the jobs of the future. It said that such education would "mitigate the negative effects" on jobs which are possible as AI develops.

Britain needs to lead the way on artificial intelligence regulation, in order to prevent companies such as Cambridge Analytica setting precedents for dangerous and unethical use of the technology, the head of the House of Lords select committee on AI has warned. The Cambridge Analytica scandal, Lord Clement-Jones said, reinforced the committee's findings, released on Monday in the report "AI in the UK: ready, willing and able?" "These principles do come to life a little bit when you think about the Cambridge Analytica situation," he told the Guardian. "Whether or not the data analytics they carried out was actually using AI … It gives an example of where it's important that we do have strong intelligibility of what the hell is going on with our data." Clement-Jones added: "With the whole business in [the US] Congress and Cambridge Analytica, the political climate in the west now is much riper in terms of people agreeing to … a more public response to the ethics and so on involved. It isn't just going to be left to Silicon Valley to decide the principles."

Extracting temporal relations (before, after, overlapping, etc.) is a key aspect of understanding events described in natural language. We argue that this task would gain from the availability of a resource that provides prior knowledge in the form of the temporal order that events usually follow. This paper develops such a resource -- a probabilistic knowledge base acquired in the news domain -- by extracting temporal relations between events from the New York Times (NYT) articles over a 20-year span (1987--2007). We show that existing temporal extraction systems can be improved via this resource. As a byproduct, we also show that interesting statistics can be retrieved from this resource, which can potentially benefit other time-aware tasks. The proposed system and resource are both publicly available.

Efficient network management is one of the key challenges of the constantly growing and increasingly complex wide area networks (WAN). The paradigm shift towards virtualized (NFV) and software defined networks (SDN) in the next generation of mobile networks (5G), as well as the latest scientific insights in the field of Artificial Intelligence (AI) enable the transition from manually managed networks nowadays to fully autonomic and dynamic self-organized networks (SON). This helps to meet the KPIs and reduce at the same time operational costs (OPEX). In this paper, an AI driven concept is presented for the malfunction detection in NFV applications with the help of semi-supervised learning. For this purpose, a profile of the application under test is created. This profile then is used as a reference to detect abnormal behaviour. For example, if there is a bug in the updated version of the app, it is now possible to react autonomously and roll-back the NFV app to a previous version in order to avoid network outages.

Demand is growing for more accountability in the technological systems that increasingly occupy our world. However, the complexity of many of these systems - often systems of systems - poses accountability challenges. This is because the details and nature of the data flows that interconnect and drive systems, which often occur across technical and organisational boundaries, tend to be opaque. This paper argues that data provenance methods show much promise as a technical means for increasing the transparency of these interconnected systems. Given concerns with the ever-increasing levels of automated and algorithmic decision-making, we make the case for decision provenance. This involves exposing the 'decision pipeline' by tracking the chain of inputs to, and flow-on effects from, the decisions and actions taken within these systems. This paper proposes decision provenance as a means to assist in raising levels of accountability, discusses relevant legal conceptions, and indicates some practical considerations for moving forward.