If the casting director of the TV show "Silicon Valley" were asked to produce a canonical example of an applicant to Y Combinator's incubator program, she may well have come up with the guy strolling to the front of in a basement auditorium at Stanford on a mid-April day this year. He's a goateed bro in his mid-twenties, rocking a grey pullover hoodie, a brown stocking cap, and an eagerness to share his killer idea--Airbnb for parking! He's come to the Gates Computer Science Building to pitch it to the two interlocutors holding "Office Hours," where savvy veterans of the startup process dispense wisdom to aspiring Mark Zuckerbergs. The bro is clearly happy when both of them--Sam Altman, the head of Y Combinator, and Yuri Sagalov, a startup CEO who completed YC's startup boot camp in 2010 and now is a part-time partner there--express excitement at the concept. But Altman, a wiry 32-year-old who himself is wearing a zip-up hoodie, hits the brakes on the lovefest. "When is this going to launch?" he asks. The founder says the app is six months out. Steven Levy is Backchannel's Editor in Chief. Sign up to get Backchannel's weekly newsletter. "How about six days?" asks Altman.

Artificial intelligence (AI) can transform the productivity and GDP potential of the UK landscape. But, we need to invest in the different types of AI technology to make that happen. Our research shows that the main contributor to the UK's economic gains between 2017 and 2030 will come from consumer product enhancements stimulating consumer demand (8.4%). This is because AI will drive a greater choice of products, with increased personalisation and make those products more affordable over time. Labour productivity improvements will also drive GDP gains as firms seek to "augment" the productivity of their labour force with AI technologies and to automate some tasks and roles.

Research from PwC has shown that the majority of the UK's economic gains over the period to 2030 will come from increasing consumer demand. AI will drive this, with a greater choice of products, increased personalisation of those products and making them more affordable over time. Labour productivity improvements will also drive GDP gains, but to a lesser extent. Jonathan Gillham, economist at PwC, said "Much of the focus on AI to date has been on the impact that increased automation of tasks will have on jobs. While we expect that the nature of jobs will change and that some will be susceptible to automation, our research shows that the boost to UK GDP that AI-driven products and services will bring will also generate significant offsetting job gains, as well as boosting average real wage levels." See also: How AI can transform I.T. and keep businesses at the summit "AI will make everyday products better, more personalised and cheaper over the longer term, which we predict will fuel increased demand.

HM Revenue & Customs is planning a series of trials on the use of artificial intelligence (AI) in some of its processes, with an emphasis on customer contact and casework. Interim chief digital and transformation officer Mike Potter (pictured) referred to the plans in a presentation to the Public Sector Show in London yesterday. He said the department plans to launch the trials in the near future as part of a move towards robotic automation and "taking the graft out of people's jobs to focus on higher value work". Potter declined to provide details of the trials, saying there is a need to talk with staff before making more information public. But he said the department is exploring areas it thinks is more viable, and his presentation included a slide dividing early use cases into three groups: contact handling, to direct people to the right places without human intervention; casework, with AI being used to augment decision-making; and helping customers through effective self-service. These are part of a broader effort for HMRC to use its data more intelligently and to supplement its processes with machine learning.

It's widely accepted that artificial intelligence (AI) will have a huge impact on our lives in the coming decades -- but what's its value to the global economy? According to a new report, global GDP will be 14% higher in 2030 as a result of AI -- the equivalent of $15.7 trillion, more than the current output of China and India combined. The report, Sizing the Prize, was launched by PwC in a session at the World Economic Forum's Annual Meeting of the New Champions 2017 in Dalian, China. Improvements to labour productivity will account for over half of all economic gains from AI between now and 2030, while increased consumer demand resulting from product enhancements will account for the rest. Regional gains will be most strongly felt in China, which will receive a 26% boost to GDP in 2030, followed by North America (14.5%).

This list isn't just about what is new and innovative. It is about what will be adopted at scale. The beginning of a new year is usually the time to predict key trends for the year to come, and so it goes with the insurtech sector as well. Most lists focus on the latest sexy technologies and applications. But, after a year, we find these have hardly gained any traction and so cannot really be considered "trends" in our view.

As we learned during the general election, political campaigns now routinely involve paid social advertising utilising a variety of data to identify likely supporters or swing voters. Such'social scoring', whether done manually or by an algorithm, is concerning to some. Professor John Rust of Cambridge University's Psychometric Centre told the Guardian: "The danger of not having regulation around the sort of data you can get from Facebook and elsewhere is clear. With this, a computer can actually do psychology; it can predict and potentially control human behaviour." He finds it "incredibly dangerous" that people's "attitudes are being changed behind their backs".

Recitations from Tel-Aviv University introductory course to computer science, assembled as IPython notebooks by Yoav Ram. Exploratory Computing with Python, a set of 15 Notebooks that cover exploratory computing, data analysis, and visualization. No prior programming knowledge required. Each Notebook includes a number of exercises (with answers) that should take less than 4 hours to complete. Developed by Mark Bakker for undergraduate engineering students at the Delft University of Technology.

The latest scare story around the rise of robots is that within 120 years all human jobs will be automated. If that study from Oxford University is to be believed, we're just 3 to 4 generations away from perpetual holiday. The report goes on to predict when AI will outperform humans and -- more interestingly -- how. Some aspects will be of genuine concern to certain industries: AI will be a better driver than human heavy goods vehicles drivers by 2027, AI will write better novels than we can by 2049, and, closest to today, AI will be better at translation by 2024. AI has the potential to significantly reshape the translation sector, as it's doing to many other industries already. However, given that the last time human translators were pitted against machine translation (in February) that 90 percent of the automated translation was judged "grammatically awkward," that is a bold prediction.

Some foundations of statistical science have been questioned recently, especially the use and abuse of p-values. See also this article published in FiveThirtyEight.com. Statistical tests of hypotheses rely on p-values and other mysterious parameters and concepts that only the initiated can understand: power, type I error, type II error, or UMP tests, just to name a few. Pretty much all of us have had to learn this old stuff (pre-dating the existence of computers) in some college classes. Sometimes results from a statistical test will be published in a mainstream journal - for instance about whether or not global warming is accelerating - using the same jargon that few understand, and accompanied by misinterpretations and flaws in the use of the test itself.