I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...
I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing
There was a recent report in The New York Times about the astronomical salaries being paid to people who have a Ph.D. in Artificial Intelligence (AI). People with barely a few years under their belt are getting paid anywhere between $300,000 and half-a-million. What is interesting is how this may be a peek into talent management in a digital world. It will force organisations to rethink the way they view talent.
Limited talent pool
When the entire talent pool consists of a few thousand people in the world, the demand and supply equation does get skewed in favour of the experts. In the case of AI, the talent pool is limited to less than 10,000 people across the world, according to Element AI, an independent lab in Montreal that has received funding from Microsoft's new venture fund.
These people are being tapped by everyone including Google, Facebook, Amazon, Apple, Microsoft as well as every other industry. The MD of Daimler Benz recently said its competitors are no longer other car companies such as Tesla,but Google, Apple, Amazon and such. The same holds true for talent. If AI is on its way to becoming like electricity, there are not enough electrical engineers being churned out.
Buy vs Build talent
When it comes to deciding whether to buy the talent rather than build it over time, the employers are seeking to outbid each other and mop up not only students but also the professors in this field. The talent pool can decide whether it wants to put its knowledge to use in driverless cars or diagnose life-threatening diseases. When each employer is paying the same salary, what makes one employer better than the other is the ability of the leader to articulate a compelling proposition.
Acqui-hiring is becoming a popular way to hire several experts at once. Google spent £400 million acquiring DeepMind, the London AI company. In January 2016, Apple purchased Emotient Inc, a startup that uses AI technology to read people's emotions by analysing facial expressions. No wonder the iPhoneX is offering face recognition. Expect Apple to build a database of your moods and then predict how to influence you.
When a company buys out these companies, the experts have to be made to feel like citizens of the new company. Else, there is a massive churn and the specialists leave en masse once their firm has been bought over.
The only beneficiary of the bidding war is the talent. They are spoilt for choice. Take the case of Andrew Ng. In 2014, the Chinese search giant Baidu poached him from Google's DeepMind project. Under his leadership Baidu's AI group grew to roughly 1,300 people, which includes the 300-strong Baidu Research. Then in March 2017, Andrew Ng left Baidu for his next big gig.
AI computing company Nvidia is also setting out to train developers in deep learning AI in a big way. Through its Nvidia Deep Learning Institute, the chip company is planning to increase its AI talent tenfold to prepare for a future where an organisation is totally powered by AI.
Hiring people from adjacent fields such as Astronomy and Physics and then training them is another strategy to build your own talent pool. I have seen people from Insurance and Finance being trained in compensation and becoming superstars in that field. Often it is easier (and cheaper) to invest in developing people because it is, after all, a great retention tool as well.
Companies such as Facebook run training programmes to build these next-gen skills among their employees.
Most employers groan at the quality of fresh hires and speak of their low employability. Yet, few employers think of hiring apprentices. In the digital age, new job roles are coming up that need new skills. AI and robotics are creating new jobs that are hard to fill because there is no ready-made talent.
Coders need to learn new programming languages that are not being taught formally. Companies such as Pinterest, LinkedIn, Visa, Airbnb and many more are using apprentice programmes to hire those who may not have a degree and yet are quick to learn the skills. It is a much better way to hire talent that can thrive in your company culture. The apprentices work on real projects and problems. This is a great way to identify people with learning agility. Educational qualifications are increasingly being separated from skills. Learning-agile people are motivated to keep learning continuously. Apprentice schemes can be a great solution to quickly build skills of the one million youth who join India's workforce every month.
As machines start understanding human voices, India needs to move beyond the target of 100 per cent literacy and focus on building 100 per cent employability. The apprenticeship programme in Germany is a successful programme that we can learn from. In the digital world, we cannot use the past to make predictions for the future. Being able to keep the mindset of an apprentice may be a terrific strategy even for experienced professionals.
Machines are certainly getting smarter. A team at Northwestern University has developed AI that can solve the Raven Progressive Matrices Test, an intelligence test of visual and analogical reasoning, better than the average American. It is time for humans to catch up. Buying talent works to plug skill gaps in the short run, but there is no getting away from building talent.