One of the most important things that the U.S. can do to improve economic growth is to invest in artificial intelligence, or A.I., said the White House, in a new report. A.I.-driven, intelligent systems have the potential to displace millions, such as truck drivers, from their jobs. But potential negative impacts can be offset by investments in education as well as by ensuring there is a safety net to help affected people, the White House argued, in what will likely be the Obama administration's final report on technology policy. Some of the report's recommendations, which include expanded unemployment help and access to healthcare, may be anathema to a Republican-controlled Congress with a focus on tax reductions and spending cuts. But this report -- "Artificial Intelligence, Automation, and the Economy" (PDF) -- which was in the works well before election day, also describes broader, technological-driven changes that will impact jobs and may pose issues for President-elect Donald Trump.

Welcome to California Inc., the weekly newsletter of the L.A. Times Business Section. Many of us are off this week and hitting the road. Happily, the average price of self-serve regular gas in the Los Angeles-Long Beach area is at the lowest level in eight years. Pump prices in the region are down nearly $2 a gallon from the all-time highs reached in October 2012, when refinery outages and heightened fears of lower supplies in California sent prices soaring. Changes at the top: At least eight companies will be getting new chief executives this coming weekend.

After three years of almost single-handedly juicing up the slow-growing economy, Janet L. Yellen and the Federal Reserve should be looking at easier days ahead. Yellen, in what will probably be her last full year as Fed chair, may finally get help from somewhere else in Washington. Tax cuts and infrastructure spending planned by President-elect Donald Trump, if backed by the Republican-controlled Congress, would lighten the load for a Fed whose easy-money policies have been the primary economic support for the nation. She is already breathing easier on the Fed's employment mandate; the jobless rate has fallen to a nine-year low of 4.6%. Inflation, too, is under control and, by all accounts, creeping toward the central bank's optimal level of 2%.

NASA is set to launch the robotic portion of its Asteroid Redirect Mission (ARM) in 2021. This will be the first mission to visit and collect a multi-ton sample from a large near-Earth asteroid. The collected sample will be used in a demonstration of enhanced gravity tractor asteroid deflection. Recently at the Robotic Operation's Center of NASA's Goddard Space Flight Center in Greenbelt, Maryland, a robotic capture module system prototype used a mock asteroid boulder to test its capabilities. NASA, along with students from West Virginia University, created the mock asteroid boulder from rock, styrofoam, plywood and an interior aluminum frame.

Google wants to apply its machine learning technology to NHS patient data within the next five years, TechCrunch reports. The search giant's London-based artificial intelligence research lab, DeepMind, announced a partnership with the Royal Free NHS Trust in London in February but the full extent of the arrangement is only just becoming clear. A Memorandum of Understanding (MoU) between DeepMind and the Royal Free shows that the pair envisage a "broad ranging, mutually beneficial partnership, engaging in high levels of collaborative activity and maximizing the potential to work on genuinely innovative and transformational projects." The MoU -- obtained via a Freedom of Information (FoI) request from New Scientist -- states that DeepMind hopes to gain access to "data for machine learning research under appropriate regulatory and ethical approvals" within the next five years. Machine learning -- a subfield of computer science that gives computers the ability to learn without being explicitly programmed -- has the potential to speed up patient diagnosis and optimise their treatments.

As financial companies have begun employing automated advisors aimed at helping customers manage their money, and oncologists have started using the artificial intelligence system known as Watson to identify new treatments, the prominent role that sophisticated computer programs have begun to occupy in our lives has become undeniable. Government agencies are also harnessing the powers of automation. The U.S. Environmental Protection Agency and the U.S. Food and Drug Administration, for example, are starting to use complex computer models that can predict environmental exposure to chemicals and drug interactions across patient groups. As agencies begin to enter this brave new world of automation, questions have begun to emerge about how government officials should delegate important tasks to machines. For one, will automation negatively affect the level and quality of human deliberation and dialogue that are integral to democratic governance? Furthermore, when adjudicating individual determinations, like the awarding of disability benefits, will machines prove incapable of providing much needed empathy to claimants?

We adopted an approach based on an LSTM neural network to monitor and detect faults in industrial multivariate time series data. To validate the approach we created a Modelica model of part of a real gasoil plant. By introducing hacks into the logic of the Modelica model, we were able to generate both the roots and causes of fault behavior in the plant. Having a self-consistent data set with labeled faults, we used an LSTM architecture with a forecasting error threshold to obtain precision and recall quality metrics. The dependency of the quality metric on the threshold level is considered. An appropriate mechanism such as "one handle" was introduced for filtering faults that are outside of the plant operator field of interest.

A shorter version was published in HBR Online on 21st December 2016. Also, the post does not review a new White House paper on AI and its impact released on 20th December 2016, that cites some posts on this blog.] On October 12, 2016, President Obama's Executive Office published two reports that received less media attention than they might have otherwise because the United States was gripped by the final weeks of a presidential campaign race. In these two reports, the administration laid out its plans for the future of artificial intelligence (AI). Depending on one's view of AI's potential impact, the actions resulting from these reports may be more influential on the long arc of history than the outcome of that election.

The 2012 publication Race against the Machine makes the case that the digitalization of work activities is proceeding so rapidly as to cause dislocations in the job market beyond anything previously experienced [1]. Unlike past mechanization/automation, which affected lower-skill blue-collar and white-collar work, today's information technology affects workers high in the education and skill distribution. Machines can substitute for brains as well as brawn. On one estimate, about 47% of total US employment is at risk of computerization [2]. If you doubt whether a robot or some other machine equipped with digital intelligence connected to the internet could outdo you or me in our work in the foreseeable future, consider news reports about an IBM program to "create" new food dishes (chefs beware), the battle between anesthesiologists and computer programs/robots that do their job much cheaper, and the coming version of Watson ("twice as powerful as the original") based on computers connected over the internet via IBM's Cloud [3]. On the darker side, you do not have to be paranoid to be paranoid about the potential technologies that the super-secret computers of the US National Security Agency (NSA) have on their digital drawing-boards.

The growing popularity of artificial intelligence technology probably will lead to millions of lost jobs, especially among less-educated workers, and could exacerbate the economic divide between socioeconomic classes in the United States, according to a newly released White House report. But that same technology is also essential to improving the country's productivity growth, a key measure of how efficiently the economy produces goods. That could ultimately lead to higher average wages and fewer work hours. For that reason, the report concludes, our economy actually needs more artificial intelligence, not less. To reconcile the benefits of the technology with its expected toll, the report states, the federal government should expand both access to education in technical fields and the scope of unemployment benefits.