Companies that engage their workforce when they design and implement new technologies will be best-positioned to manage the coming AI revolution. By respecting the fact that today’s workers, like those before them, understand their jobs better than anyone and the many tasks they entail, they will be better able to “give wisdom to the machines.”
The future is both exciting and uncertain. Exciting because there are a huge amount of opportunities for AI to reduce risk for humans in jobs that are dangerous for humans or where humans’ imperfections create danger. Uncertain, however, because there is some risk that AI might just be able to crack that Turing Test across the board and leaving us totally jobless.
This is not a new phenomenon, new technologies have always displaced the need for human labor. In the past the change was gradual and people had time to learn new skills that the economy needed. But the pace at which it is happening this time may be too rapid for people to adapt.
While there has been a lot of talk about super-smart artificial intelligence lately, one of the leaders in the field thinks there are more pressing problems for humanity to solve.
Andrew Ng, the cofounder of Coursera and former chief scientist at Chinese technology powerhouse Baidu, told an audience at a Harvard Business Review event today that we should be far more concerned about the job losses that will come as a result of machine learning.
All the talk about the singularity and robot threats misses the real danger: the evisceration of the middle class and the creation of a restless, unemployed population. Instead of dreaming about robot wars, let’s be thoughtful about our own very human policy choices.
A Pew Research Foundation study examining the future of work and job training found a belief among some experts that artificial intelligence and automation threaten not just millions of jobs, but also the future of capitalism.
In the near future, every core business function will have been transformed by AI — hiring, sales, security, marketing, finance, manufacturing… everything. Purpose-built headless AI platforms will provide the new infrastructure that will drive every business.
In the future, there will be two kinds of jobs. Either we will manage the machines or the machines will manage us.
AI, as impressive and powerful as it is, won’t take over all human work any time soon. Instead of trying to prepare for a jobless future, we should instead be preparing for one that’s a turbocharged version of what we already have: a job creation engine that has shifted into a lower gear, and a large number of people tempted to sit on the sidelines rather than contributing their skills to the economy.
The future for analysts is much less dystopian than the headlines suggest. The advancements in AI look a lot like having efficient assistants rather than replacements.
The job of analysts will be to point the AI to the right questions to be analyzed and to decide how to apply that analysis to problems in the real world. As long as the ultimate consumer of analytics is a human, human analysts aren’t going anywhere.
AI’s flaw in a field as emotive and personal as language is simply that it isn’t human. So, while we’ll see machine translation taking on the more basic parts of translation work, it’ll be many years yet before it fully replaces skilled humans.
Experts from Yale and Oxford University recently released their research on how AI will transform modern life by reshaping transportation, finance, health, science, and the military. Key findings pointed toward a 50 percent chance that AI will outperform humans in every job in 45 years’ time.
How can we anticipate and manage trends in AI, and will creative and analytical skills really be the key to job success in an AI world?
For centuries, humans have been fretting over “technological unemployment” or the loss of jobs caused by technological change. Never has this sentiment been accentuated more than it is today, at the cusp of the next industrial revolution.
With developments in artificial intelligence continuing at a chaotic pace, fears of robots ultimately replacing humans are increasing.
The new smart will be about trying to overcome the two big inhibitors of critical thinking and team collaboration: our ego and our fears. Doing so will make it easier to perceive reality as it is, rather than as we wish it to be. In short, we will embrace humility. That is how we humans will add value in a world of smart technology.
Tools powered by artificial intelligence don’t care whether they replace you. So, here are three spaces they can’t fill — at least not for a while.
Thanks to advances in technology, many jobs that weren’t considered ripe for automation suddenly are
The technological race for human (consumer) attention won’t be won by human copywriters. This “People Based Marketing” everybody’s crowing about will very soon be executed best by nonhuman copywriters. Every day, brands and marketers are demanding more and more speed and more and more ideas from their “creative” agencies. And creative agencies are gape-mouthed clueless on how to meet these demands.
Unchanged for the past hundred years, the legal industry now faces its turn to be automatized.
The idea of legal tech is not new, however not until today have algorithms been ready to seriously transform the legal industry.
Artificial intelligence in fashion is stuck in the same catch-22 as technology like virtual and augmented reality. They’re all consistently on the cusp of disrupting the industry, but as a majority of cautious retailers wait in the wings to watch as others test it out, no real progress is being made. The edge AI has over VR is that it can actually make an impact on how companies operate internally.
The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. It’s exciting to consider all the ways our lives may improve, from managing our calendars to making medical diagnoses, but it’s scary to consider the social and personal implications — and particularly the implications for our careers. As machine learning continues to grow, we all need to develop new skills in order to differentiate ourselves. But which ones?