Lawyers, be forewarned: In what could be a foreshadowing of things to come, a judge has penalized two lawyers for failing to use artificial intelligence. The case comes to us by way of Ontario. It arose after a woman named Kristen Cass slipped and fell in a tavern in Port Dalhousie, a waterfront community on Lake Ontario, 30 minutes by car from Niagara Falls. The tavern owner defaulted, so her lawsuit proceeded solely against the building's owner, the Port Dalhousie Vitalization Corporation (PDVC). PDVC won summary judgment dismissing the action against it.

A cadre of senators is looking to prompt the federal government to be a bit more proactive in utilizing artificial intelligence technologies. To this end, the bipartisan group including Sens. Brian Schatz, D-Hawaii, Cory Gardner, R-Colo., Rob Portman, R-Ohio, and Kamala Harris, D-Calif., introduced the Artificial Intelligence in Government Act on Wednesday. Per a news release, the bill would seek to "improve the use of AI across the federal government by providing resources and directing federal agencies to include AI in data-related planning." The bill aims to do a number of things, including establishing an AI in government advisory board, directing the White House Office of Management and Budget to look into AI as part of the federal data strategy, getting the Office of Personnel Management to look at what kinds of employee skills are necessary for AI competence in government and expanding "an office" at the General Services Administration that will provide expertise, do research and "promote U.S. competitiveness." "Artificial intelligence has the potential to benefit society in ways we cannot imagine today," Harris said in a statement.

U.S. District Judge Haywood Gilliam in Oakland granted a request by 14 Democratic attorneys general for a preliminary injunction. The rules, which are set to go into effect Jan. 14, allow businesses or nonprofits to obtain exemptions to an Obamacare requirement for contraceptive coverage on moral or religious grounds.

The goal of this article is to inspire data scientists to participate in the debate on the impact that their professional work has on society, and to become active in public debates on the digital world as data science professionals. How do ethical principles (e.g., fairness, justice, beneficence, and non-maleficence) relate to our professional lives? What lies in our responsibility as professionals by our expertise in the field? More specifically this article makes an appeal to statisticians to join that debate, and to be part of the community that establishes data science as a proper profession in the sense of Airaksinen, a philosopher working on professional ethics. As we will argue, data science has one of its roots in statistics and extends beyond it. To shape the future of statistics, and to take responsibility for the statistical contributions to data science, statisticians should actively engage in the discussions. First the term data science is defined, and the technical changes that have led to a strong influence of data science on society are outlined. Next the systematic approach from CNIL is introduced. Prominent examples are given for ethical issues arising from the work of data scientists. Further we provide reasons why data scientists should engage in shaping morality around and to formulate codes of conduct and codes of practice for data science. Next we present established ethical guidelines for the related fields of statistics and computing machinery. Thereafter necessary steps in the community to develop professional ethics for data science are described. Finally we give our starting statement for the debate: Data science is in the focal point of current societal development. Without becoming a profession with professional ethics, data science will fail in building trust in its interaction with and its much needed contributions to society!

Machine-learning models have demonstrated great success in learning complex patterns that enable them to make predictions about unobserved data. In addition to using models for prediction, the ability to interpret what a model has learned is receiving an increasing amount of attention. However, this increased focus has led to considerable confusion about the notion of interpretability. In particular, it is unclear how the wide array of proposed interpretation methods are related, and what common concepts can be used to evaluate them. We aim to address these concerns by defining interpretability in the context of machine learning and introducing the Predictive, Descriptive, Relevant (PDR) framework for discussing interpretations. The PDR framework provides three overarching desiderata for evaluation: predictive accuracy, descriptive accuracy and relevancy, with relevancy judged relative to a human audience. Moreover, to help manage the deluge of interpretation methods, we introduce a categorization of existing techniques into model-based and post-hoc categories, with sub-groups including sparsity, modularity and simulatability. To demonstrate how practitioners can use the PDR framework to evaluate and understand interpretations, we provide numerous real-world examples. These examples highlight the often under-appreciated role played by human audiences in discussions of interpretability. Finally, based on our framework, we discuss limitations of existing methods and directions for future work. We hope that this work will provide a common vocabulary that will make it easier for both practitioners and researchers to discuss and choose from the full range of interpretation methods.

Johnathan Fair, 19, allegedly beat his girlfriend's 4-year-old daughter to death in December after she spilled juice on an Xbox video game console. Prosecutors in Illinois plan to seek a life sentence for a man who allegedly killed his girlfriend's daughter after she spilled juice on an Xbox video game console. Johnathan Fair, 19, of Waukegan, roughly 40 miles northwest of Chicago, was babysitting 4-year-old Skylar Mendez on Dec. 13 when the incident occurred, the Lake County News-Sun reported, citing the State Attorney's Office. Fair took the child to a hospital and claimed she fell and hit her head, prosecutors said. He later reportedly admitted that he shook Mendez "really hard" and beat her because she spilled juice on the console.

The right to privacy has become a pressing human rights issue. Big data -- combined with artificial intelligence and facial recognition software -- has the capacity to intrude on people's lives in unprecedented ways, in some cases on a massive scale. While much of the discussion has focused on how social media and tech companies use the data they collect about their users, more attention needs to be paid to the wider relationship between violations of privacy and other types of human rights abuses. Mass invasions of privacy can undermine the rights of millions, if not billions, of people around the world as governments gain a greater capacity to discriminate -- or worse -- across gender and sexuality lines, and stifle dissent, including through violence. So what can be done to limit the human rights fallout?

The publication of Federico Pistono's book, Robots Will Steal Your Job, But That's OK, back in 2012 spawned a thousand think pieces, news headlines, and debates over what the future of robotics means for humans and the workplace. At a recent Future of Ageing Conference held by the think tank International Longevity Centre (ILC) in London, the topic was once again up for debate. Whilst the consensus is that the robots are coming, in fact many argue they're already here, Caroline Waters, vice chair of the Equality and Human Rights Commission and vice president of Carers UK, made an interesting point in regards to the robotic effect on the labour market. "We're conflating robots and AI with industry," said Waters. "Actually we're more likely to use domestic robots."

Every year the technology industry gathers in Las Vegas for the Consumer Electronics Show (CES), an event that often sets the agenda for the coming 12 months. This is what CES 2019 taught us. The first 5G networks are expected to begin rolling out this year, and so the next-generation connectivity technology was being mentioned everywhere at CES. Intel, Qualcomm and Samsung all spoke about harnessing the technology to not just offer faster mobile internet speeds, but also to connect more devices and appliances to each other and be able to handle more data in the process. Experts at the show also commented on the higher capacity of 5G networks being able to support the software needed to power networks of driverless cars and robots. The halls of this year's CES hinted at a world where homes, cars and even entire cities are connected to one another, with people able to use these connections to complete tasks every day.

Faced with seesawing commodity prices and the pressure to be more efficient and environmentally friendly, farmer Jamie Butler is trying out a new worker on his 450-acre farm in England's Hampshire countryside. Methodically inspecting Butler's winter wheat crop for weeds and pests, the laborer doesn't complain or even break a sweat. That's because it's a four-wheel robot dubbed "Tom" that uses GPS, artificial intelligence and smartphone technology to digitally map the field. Tom's creator, the Small Robot Company, is part of a wave of "agri-tech" startups working to transform production in a sector that is under economic strain due to market pressures to keep food cheap, a rising global population and the uncertainties of climate change. Most robots are still only being tested, but they offer a glimpse of how automation will spread from manufacturing plants into rural areas.