How A.I. will Affect Our Future
Updated: Mar 27
Bashing Silicon Valley has become one of the few things both political parties agree on this election cycle. And they have good reason—the artificial intelligence (AI) and automation technology developed by the Valley’s best and brightest minds is projected to displace the jobs of between one-quarter and one-third of American workers by 2030. The Brookings Institute estimates that 36 million Americans could have 70% of their work tasks replaced by automation.These alarming figures are attracting the attention of policymakers and politicians alike. Some are calling for a tax on robots. Others believe massive open online courses (MOOCs) are the answer to retraining millions of displaced workers. One former presidential candidate based his campaign on a universal basic income (UBI) to offset wage loss expected to result from mass automation.It’s only a matter of time before public opinion, like political sentiments, turns against the technology sector. It’s easy to imagine how someone at the front desk of a hotel who is replaced by an artificial assistant will feel, or to understand the reaction of a truck driver whose job is eliminated when self-driving trucks become commonplace.Silicon Valley innovated this problem into existence, and now it must innovate to find a solution. AI will impact a number of jobs, so it’s time to put AI to work to teach employees new skills. Doing so represents both a financial opportunity and a moral obligation for the tech community.A logical solution begins with giving workers access to apprenticeships in the roles that will thrive in the next iteration of our economy. People learn best by doing things and being coached, not by sitting through hours of online courses. Indeed, trying something and then getting feedback is likely how you learned how to do your job. We can’t reasonably expect someone who’s been working in a factory for 20 years to magically transform into a software engineer simply because they accessed a Web-based learning system. They need to watch and then do, assisted by a real-time coach.However, geographic dispersion makes apprenticeships challenging. Those teaching the skills that will remain valuable in a post-automation world often live far from those who most need new jobs—and neither is likely to move. Indeed, geographic mobility in the U.S. is at historic lows. In 1990, 6.1% of Americans moved between counties or states; in 2017, only 3.6% did so.
Jake SaperCommunication technologies can help bridge geographic distance, but they’re not enough to help displaced, dispersed workers learn new skills. For that, we need to build digital apprenticeships. This starts by connecting a novice worker into a distributed network of people performing the same role. AI is then used to learn which approaches to the task work best in a given context and provide real-time guidance to the novice worker as they get started. As these novice workers grow and develop, their own best practices will automatically contribute to the network, improving the recommendations for everyone else working in it.For example, consider someone who is training to be a customer support representative, a position that anyone can hold regardless of their geographic location but which requires skills and knowledge learned from others. AI learns how all support reps in a network respond to a specific customer question, considering all the relevant context (customer demographics, product type, the support rep’s experience, etc.). It then measures how well each response performs, in terms of customer satisfaction, time to resolve the issue and the like. Lastly, it identifies the best-performing responses, or “brilliant outliers,” and makes recommendations based on those responses to workers learning how to deal with similar situations.This network-based apprenticeship model offers massive knowledge distribution to help even a novice who is learning a new task from afar. When deployed at scale, not only does it represent a way for Silicon Valley to mitigate some of the job losses it is driving, but also it is a massive business opportunity that gives companies access to talent outside its traditional hiring centers. At Emergence, we call this opportunity Coaching Networks and believe it represents not just the next big wave of software innovation but also a critical tool in helping our country bridge the growing geographic and economic divide.
Artist: Fred Friedrich
Name: Schlepper 5
Collection: Sleeeper 8
Technique: Photography / QR Code
Measures: 80 x 80 cm
W.V. 2020/02/03 ©
Provenance: Museo Fred Friedrich