As AI becomes the biggest disruptor in tech, the top firms are trying to corner the market on talent. In the last year or so, Google has assembled one of the industry's biggest teams of AI experts, including Fei-Fei Li, the head of Stanford's AI Lab. Uber also poached a team of 40 researchers from Carnegie Mellon University. Competition for talent among those companies plus Apple, Facebook, Amazon, Microsoft and Baidu is so intense that some recruits start out with seven-figure salaries.
To some, it looks like top-tier firms have hoarded all the talent. Google has admitted that it now houses "less than 50% but certainly more than 5%" of the world's leading experts in machine learning. If a handful of tech companies monopolize all the talent, the thinking goes, then they will control the future of AI and tech.
While this is a legitimate cause for concern - especially since the firms are raiding teachers from academia - the effect isn't likely to last. High salaries, global competition, open-sourced algorithms/platforms, and the lure of starting one's own company or joining an elite start-up will ensure that AI innovation will be democratized, even if it takes a few years.
The lure of a hot new career
AI talent is in such demand now that Microsoft research chief Peter Lee has likened the cost of acquiring an AI researcher to nabbing an NFL quarterback. As word of such salaries filter down, more undergraduates will inevitably consider AI as a career. Interestingly, a 2016 survey of the "hardest jobs to fill in tech," AI didn't make the list. I suspect it will in 2017 or 2018 based on what I see happening in tech. That ranking reflects the fact that so far, it's just the leading edge companies and schools schools that are throwing resources at AI. That will inevitably change as more firms realize that AI is essential to innovation and more students and software developers see the opportunities in AI. Seven-figure salaries may also convince tech workers in other fields to learn AI as well. Such workers have resources like Andrew Ng's course on Coursera and Kaggle, which teaches machine learning coding.
The lure of entrepreneurship
Another argument against a generational AI brain drain is the entrepreneurial drive. If someone who knows AI well can command a seven-figure salary, then she can probably also get funding for her startup or may prefer to join an elite team in a start-up working on an important problem.
While the possibility of becoming a billionaire is a strong draw for going this route, there are other motivations. Some want to change the world. Others want to work on difficult problems with small, elite teams. Still others want to do things their way. As Patagonia founder stated, "If you want to understand the entrepreneur, study the juvenile delinquent. The delinquent is saying with his actions, 'This sucks. I'm going to do my own thing.'" People with that mentality don't do well in a corporate environment.Yvon Chouinard has
For proof of this, look at Andrew Ng. A Google veteran, Ng recently left Baidu to pursue his own path. Though it's not clear where he's going, Ng's Medium post on the topic referred to "rich opportunities in entrepreneurship."
The global marketplace
While universities in the U.S. and Canada can rightly charge that Google and others have raided their staffs, let's not forget that we're living in a global economy. In 2020, the U.S. and the European Union will only account for 25% of the world's college-educated people.
China, meanwhile, opens a new university every week. In 2013, 40% of Chinese graduates completed STEM educations. That's double the U.S. rate. By 2030, China and India could account for 60% of STEM graduates in major economies versus 4% for the U.S.
Those are sobering figures. At the moment, the U.S. is still winning the competition for AI talent, but Chinese firms - especially Baidu - are aggressively pursuing AI talent. China's universities also began focusing a few years ago on AI so the fruits of that effort won't be seen for a few years.
The end of the brain drain
In addition to those factors, some tech companies have started making moves to ensure that there's more AI talent in the pipeline. As one AI professor told MIT Technology Review in 2014, tech companies have stepped up their grants since they realized they'll soon run out of recruits.
Elon Musk and other top tech leaders pledged to spend over $1 billion for OpenAI, a not-for-profit initiative that will share its work with the public. Initiatives like this could lead to open platforms that make it quite easy for even less advanced software developers to incorporate AI algorithms into their software products.
These are positive signs, showing the market won't allow a vacuum much longer. Assessing the scene from a global level, Google, Apple, Uber and others look like they're trying to plug leaks in a dam with their fingers. They can't hold off the torrent though.