Throw in the valley’s rich history of computer science breakthroughs, and you’ve set the stage for the geeky-hippie hybrid ideology that has long def… - Kai-Fu Lee

Algorithms tuned by an average engineer can outperform those built by the world’s leading experts

Each of the three recognized categories — care, service, and education — would encompass a wide range of activities, with different levels of compensation for full- and part-time participation. Care work could include parenting of young children, attending to an aging parent, assisting a friend or family member dealing with illness, or helping someone with mental or physical disabilities live life to the fullest. This category would create a veritable army of people — loved ones, friends, or even strangers — who could assist those in need, offering them what my entrepreneur friend’s touchscreen device for the elderly never could: human warmth. Service work would be similarly broadly defined, encompassing much of the current work of nonprofit groups as well as the kinds of volunteers I saw in Taiwan. Tasks could include performing environmental remediation, leading afterschool programs, guiding tours at national parks, or collecting oral histories from elders in our communities. Participants in these programs would register with an established group and commit to a certain number of hours of service work to meet the requirements of the stipend. Finally, education could range from professional training for the jobs of the AI age to taking classes that could transform a hobby into a career. Some recipients of the stipend will use that financial freedom to pursue a degree in machine learning and use it to find a high-paying job.

Algorithms tuned by an average engineer can outperform those built by the world’s leading experts if the average engineer has access to far more data.