Insider trading is illegal in the United States, but what that actually means is often up to interpretation.
The term has never had an official statuary definition, causing prosecutors a lot of headaches as they attempt to argue cases based on court precedent instead of on a set of established standards.
On Thursday, Congress attempted to amend that by officially banning—and defining—the practice.
“There is currently no bright line statutory prohibition against insider trading, forcing the SEC and [Department of Justice] to rely on more general anti-fraud statutes and decades of case law, subject to interpretation by individual judges,” said Jim Himes on the floor of the House. “It is past time for Congress to provide direction in this area, as there exists a clear and fundamental disadvantage in prosecuting a crime that has never been properly defined.”
The Securities and Exchange Commission currently has its own definition of insider trading and chooses to file lawsuits against individuals who violate those stipulations. It’s then up to the courts to evaluate the SEC’s standards and determine if they’re fair on a case-by-case basis.
The Insider Trading Prohibition Act, which passed the House by an overwhelming majority of 410 to 13, defines insider trading as any trade made on information that has been “obtained wrongfully.” It also prevents people from passing along “material, nonpublic information” to someone “if it’s reasonably foreseeable that the recipient of the information will trade on that information or pass it along to others who will.”
In a statement after the passage of the rule, Himes noted, “The bipartisan passage of this bill represents years of work incorporating ideas and input from regulatory agencies, legal experts, and my colleagues on both sides of the aisle.” He emphasized, “it’s a testament to the fact that Congress can craft meaningful policy that both Democrats and Republicans can support if we fully commit to working across the aisle in good faith.”
But 13 Republican Congressmen voted against the ban. They claim there would be more nay votes if their fellow representatives had taken the time to fully understand the nuances of the bill and were less worried about political capital.
“I think it’s fair to say that people were nervous about voting against something saying it’s going to end insider trading,” said Rep. Bill Huizenga (R-Mich.), who
Bye bye blockchain developer, hello artificial intelligence specialist.
That role, A.I. specialist, is the fastest growing U.S. job in terms of number of hires, at least according to LinkedIn, which published its annual emerging jobs report on Tuesday.
Hirings for A.I. specialists on the career networking service have grown 74% annually over the past four years, LinkedIn said. But it didn’t reveal how many jobs that represents, only that demand for that job role is growing faster than other emerging jobs.
What’s noteworthy about this year’s survey is that last year’s top job role, blockchain developer, is absent from the latest list. It highlights how the recent craze over cryptocurrencies and blockchain created a brief demand for blockchain-related jobs, but as the hype died down, so too did demand for people with blockchain skills.
“It was spectacular, but vanished very quickly,” LinkedIn’s principal economist Guy Berger said. The fact that blockchain developers did not make this year’s emerging job list caused Berger to say that it validates his company’s data by showing it accurately reflects “a failed trend or a flash in the pan.”
No. 2 on the list was “robotics engineer,” an umbrella term for both physical robotics and so-called robotic process automation, a trendier technology that involves software automating basic tasks like entering data into a table. The third fastest growing job in terms of hiring was “data scientist.”
A.I. specialist is an evolution of other machine-learning and data-crunching job titles that have topped the list before. Although A.I. specialists may share some traits with data scientists, the work of data scientists involves a wider set of statistical or data visualizations tools versus just machine learning software, Berger said.
The top metropolitan areas where A.I. specialists are in demand include the San Francisco Bay Area, New York, Boston, Seattle, and Los Angeles. Computer software, Internet, information technology, higher education, and consumer electronics are the industries with the biggest appetite.
The most common jobs that A.I. specialists held prior to labeling themselves with the title include “software engineer,” “data scientist,” “research assistant,” and “data engineer,” a LinkedIn spokesperson said. This suggests that people may be updating their job titles to include artificial intelligence, to put themselves in a better