On Jan. 15, FBI agents arrested Jerry Chun Shing Lee, a former CIA case officer, and charged him with unlawful retention of classified information. Lee is the sixth person charged by the Justice Department in the past two years for espionage-related offenses suspected to have been conducted on behalf of the People's Republic of China. By comparison, prior to 2015, only one or two people on average per year were arrested for such offenses. The increased frequency of arrests--coinciding with a public March 2016 announcement by the Chinese government that intelligence efforts would be more heavily resourced--may indicate that China is scaling up traditional human intelligence efforts against the United States government. Lee's arrest seemingly stemmed from FBI agents' discovery of classified information in his notebooks in 2012.
Data has become the most valuable currency in business. But without the right tools or intelligence, its true value will not be realised. According to a MiQ survey, 43 per cent of US and UK brand marketers think that the lack of measurement of business impact, such as sales or growth, is the main hurdle to investing more in data analytics. But if marketing metrics are not the same as business goals, why are campaigns measured against them? Marketing should align with the same goals as the rest of the company, in order to measure tangible business results.
The IQ test is an exam most of us are familiar with, regardless of whether we have taken it or not. The test was originally designed by the French psychologist Alfred Binet in the early 1900s. But in the new millennium, is the IQ test still an effective means of measuring general intelligence? According to the general consensus, the answer is "no."
When it comes to artificial intelligence (AI), the dominant media narratives often end up taking one of two opposing stances: AI is the saviour or the villain. Whether it is presented as the technology responsible for killer robots and mass job displacement or the one curing all disease and halting the climate crisis, it seems clear that AI will be a defining feature of our future society. However, these visions leave little room for nuance and informed public debate. They also help propel the typical trajectory followed by emerging technologies; with inevitable regularity we observe the ascent of new technologies to the peak of inflated expectations they will not be able to fulfil, before dooming them to a period languishing in the trough of disillusionment. There is an alternative vision for the future of AI development.