Leading technology intellectual, Tim O'Reilly, has now called for tech companies researching artificial intelligence (AI) to look beyond cost-cutting measures and consider its use as a way to augment human workers. More directly, O'Reilly believes that workers shouldn't be replaced by machine learning-driven solutions. Quoting T. S. Eliot, he goes on to say that the ideas surrounding one solution that has been offered to address robotic replacement of jobs, touted as "universal base income," is simply not the right answer. The concept effectively says that a base level of income should be parcelled out to ensure that everybody can afford to live with basic necessities in the wake of robots and AI taking too many jobs. O'Reilly actually likes the idea but says that it strikes him as an example of "the greatest treason" which is to do the right thing for the "wrong reasons." Regardless of whether technology replaces jobs traditionally held by humans, there is still a lot of work to be done that AI can assist with but not accomplish on its own.
O'Reilly's points may not be far off from the mark. AI and robotics are well placed to begin completely replacing jobs over the next decade, if not sooner. Moreover, they promise better road safety, better medications, earlier medical condition detection, and a plethora of other possibilities. However, the profit side of that has become a serious point of contention among many in the industry, as companies seek to continue yearly growth and industry dominance. Of course, some companies are arguably doing a better job than others of ensuring that human workers still have jobs. But it's not unreasonable to expect intense competition and discrepancies between businesses to drive more of the market the other direction over time.
Unfortunately, although O'Reilly does a good job of outlining issues that need to be worked on, he doesn't provide any clear ideas for how his proposal can be accomplished. His list includes issues surrounding climate change, rebuilding infrastructure, resource management, and disease prevention, among other things. AI may be able to crunch the data and design solutions but, in the short term, it's going to be on humans to see that the work gets done. It's going to be up to the companies behind the technology to lead the way in ensuring that's put to good use.