Fiscal Intelligence

“But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should But, as Musk’s above-quoted statement suggests, the rise of AI has so far occurred in a regulatory vacuum. With the exception of a few states’ passage of legislation regarding autonomous vehicles and drones, very few laws or regulations exist that specifically address the unique challenges raised by artificial intelligence, and virtually no courts appear to have developed standards specifically addressing who should be held legally responsible if an AI causes harm.”

“While the non-oil private sector is relatively small in Saudi Arabia, it has potential to drive much of the growth. Already during the 2003–13 period, the non-oil private sector outperformed the economy as a whole, albeit starting from a low base. It grew at about 10 percent annually, much faster than the overall 6 percent GDP growth rate. Growth was broadly based, with consumption-based sectors such as transport, communications, retail and wholesale trade, and business services growing the fastest.”

In early 2015, 120.8 million adults were in middle-income households, compared with 121.3 million in lower- and upper-income households combined, a demographic shift that could signal a tipping point, according to a new Pew Research Center analysis of government data.¹

Another common pitfall we see is the treatment of blended learning as a standalone education program instead of integrated into the costs associated with day-to-day instruction. Assessing cost trade offs within the ongoing instructional budget will allow blended learning to be both scalable and sustainable.

The purpose of this article is to provide a quantitative analysis of privacy-compromising mechanisms on the top 1 million websites as determined by Alexa. It is demonstrated that nearly 9 in 10 websites leak user data to parties of which the user is likely unaware; more than 6 in 10 websites spawn third-party cookies; and more than 8 in 10 websites load Javascript code. Sites that leak user data contact an average of nine external domains. Most importantly, by tracing the flows of personal browsing histories on the Web, it is possible to discover the corporations that profit from tracking users. Although many companies track users online, the overall landscape is highly consolidated, with the top corporation, Google, tracking users on nearly 8 of 10 sites in the Alexa top 1 million. Finally, by consulting internal NSA documents leaked by Edward Snowden, it has been determined that roughly one in five websites are potentially vulnerable to known NSA spying techniques at the time of analysis.

In fact, 50% of students in America would have only the equivalent of dial-up speeds (up to 56 kbps per student) if their classrooms were to transition to a 1:1 digital learning environment.

Across the seven programs, we find no observable impacts of the cash transfer programs on either the propensity to work or the overall number of hours worked, for either men or women Pooling across the five comparably designed studies to maximize our statistical power to detect effects if they exist, we again find no observable impacts on either work outcome.

With these components in place, we present the Data Science Machine — an automated system for generating predictive models from raw data. It starts with a relational database and automatically generates features to be used for predictive modeling.