Technologists and economists have warned that China is poised to dominate in AI. If China has the strategy to compete, the US holds the resource advantage, says a report from Chinese tech giant Tencent. Per The Verge:
Canada has strong educational background (which has attracted many big companies to launch research labs there), while the UK is best on the “ethical and legal aspects” of AI, and Japan takes the lead in robotics. But it’s the US, says the report, that’s currently “far ahead” in terms of global talent, with more universities teaching machine learning and related subjects than any other nation, and more AI startups.
Tencent estimates that there are only 200,000 active AI researchers and practitioners worldwide, with another 100,000 studying. Competition for AI talent is fierce; as one university dean put it, job fairs now resemble “Thanksgiving Black Friday sales at Walmart.” The Economist offers a rundown on how the biggest AI companies – Google, Facebook, and Amazon – play:
The intense battle for talent may force secretive companies to become more open. “If you tell them, ‘come work with us but you can’t tell anyone what you’re working on’, then they won’t come because you’ll be killing their career,” explains Mr LeCun, who leads Facebook’s AI research lab. This trade-off between secrecy and the need to attract people also applies to the Chinese giants, which are trying to establish Western outposts and hire American researchers.
Look beyond the valuation frenzy. Bitcoin mining requires massive computing power; Digiconomist estimates that each bitcoin transaction requires as much as energy as needed to power eight US households for a day and that by 2019, bitcoin mining could use more electricity than the entire country. Though some entrepreneurs and investors call for an overhaul to the transaction process entirely, Ars Technica offers a less apocalyptic scenario:
If Bitcoin’s price doubles to $25,000, we can expect the Bitcoin network’s energy consumption to roughly double as well. If Bitcoin’s price falls significantly, on the other hand, miners will find their operations unprofitable and will start to switch off their least efficient equipment, causing energy use to decline.
At the inaugural meeting of G100’s BoardExcellence in Silicon Valley earlier this month, board directors explained why digital evangelists are critical to transformation and how to identify these individuals. John Hagel, head of Deloitte’s Center for the Edge, expands on how sponsorship shifts a cultural immune system resistant to change. From his blog:
To succeed in a transformation initiative, you’ll need one sponsor who is ideally the leader of the institution or at least someone who reports to the leader. … The key is to find someone who has both the conviction and the courage required to support and protect you. Don’t try to get support from the entire leadership team – I’ve never seen that happen and it tends to draw out the immune system.
How are boards addressing the legal, financial, and reputational damage of sexual harassment in their companies? Dismal metrics from The Wall Street Journal indicate most do not:
An October study by theBoardlist and Qualtrics found that 77% of boards hadn’t talked about sexual harassment, 88% hadn’t implemented a plan of action as a result of recent revelations and 83% hadn’t evaluated the company’s risks when it came to sexual harassment. Their most commonly cited reason for inaction? A perception that sexual harassment wasn’t a problem at the company.
As Vox reports, the US Equal Employment Opportunity Commission’s 2016 report on workplace harassment roundly refutes that assumption:
Anywhere from 25% to 85% of women report having experienced sexual harassment in the workplace. It’s a strikingly wide gap, but one that is very substantial even in its most conservative estimate – statistically predicting one in four people are affected by workplace sexual harassment.
Ready to start the new year with a burst of productivity? You probably won’t be all that successful, according to a new study from Priceonomics. They analyzed 1.8 million projects and 28 million tasks to figure out when people actually get their work done – and concluded that January is the least productive month in terms of tasks completed. From their findings:
