{"id":30474,"date":"2021-03-27T22:36:39","date_gmt":"2021-03-28T02:36:39","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=30474"},"modified":"2021-04-04T22:43:55","modified_gmt":"2021-04-05T02:43:55","slug":"ai-unemployment","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/ai-unemployment\/","title":{"rendered":"AI-Induced Unemployment: The Threat Is Real"},"content":{"rendered":"\n

Will AI cause mass unemployment? Are smart assisstants and self-driving cars going to make people lose their jobs?<\/p>\n\n\n\n

AI-based systems are taking every industry by storm. The concern of AI causing unemployment on a massive scale is becoming increasingly urgent as AI capabilities progress.<\/p>\n\n\n\n

Keep reading to learn about AI-induced unemployment, and some possible routes the government could take to adapt to the AI-automated economy.<\/p>\n\n\n\n\n\n\n\n

The Impact of AI on Unemployment <\/h2>\n\n\n\n

Technological innovation is enabling AI to perform an increasing number of jobs, which will cause unemployment on a massive scale.<\/p>\n\n\n\n

Throughout history, each new machine and labor-saving technology created at least as many jobs as it eliminated\u2014for example, a piece of equipment that replaced a human laborer also required someone to operate the equipment and another person to do maintenance on it. Past innovations substituted human workers\u2019 physical<\/em> capabilities, but not their cognitive<\/em> abilities. No matter how quickly a machine could sew a shirt compared to a seamstress, the machine couldn\u2019t take customers\u2019 measurements. <\/p>\n\n\n\n

However, the dual rise of infotech and biotech is creating technologies that could truly replace the need for human workers. <\/strong>New discoveries in neuroscience have revealed that human skills<\/a> such as analyzing, decision-making<\/a>, communicating, and interpreting other people\u2019s emotions are the results of specific brain algorithms\u2014not the elusive forces of free will. For example, when a lawyer enters negotiations, she\u2019s not being guided by her intuition, but rather by algorithms that pick up on the other party\u2019s biochemical patterns, including their gestures, tones of voice, and facial expressions. <\/p>\n\n\n\n

Now that scientists understand how the human brain uses these algorithms, technologists can replicate those processes with AI. As a result, not only can machines do a human\u2019s job, but they can do it better than humans, because they\u2019re immune to human error and biases.<\/strong> Additionally, machines can be connected on a network and updated all at once. Imagine the implications in the medical field: When new research comes out, it\u2019s nearly impossible to alert every doctor in the world\u2014but a global network of AI doctors could receive that update in an instant. Similarly, a network of self-driving taxis could all be updated whenever traffic laws are updated. <\/p>\n\n\n\n

The indirect effects of automating high-skilled jobs would be substantial and far-reaching.<\/strong> For example, if computers can do the job of doctors, the massive savings in payroll could make healthcare more affordable for everyone. Furthermore, patients in rural Uganda could receive the same quality of care as patients on the Upper East Side of Manhattan, because their robot doctors would have access to the same information and resources. <\/p>\n\n\n\n

However, even with the improved capabilities of AI, unemployment won’t become the destiny for all of us because not all professions lend themselves to automation. For example, AI doctors are more likely than AI nurses because doctors\u2019 job duties involve collecting data on patients\u2019 symptoms and analyzing the information in order to give diagnoses\u2014and data collection and analysis are two of computers\u2019 strongest abilities. On the other hand, nurses need a broader range of physical and emotional skills to work with patients.<\/p>\n\n\n\n

Automating Creativity<\/h3>\n\n\n\n

While it\u2019s tempting to assume that creative professionals like artists and musicians would be similar to nurses in being immune to automation, even the arts aren\u2019t safe from AI. Just as decision-making and interpersonal interactions trace back to neurological processes, so do emotions, which are at the core of creating and consuming art. When you listen to music, your emotional response is reflected in physical reactions, such as a change in heart rate and hormone levels. Machines measuring your biometric data could learn your preferences and create art designed to elicit a specific emotional response. <\/strong><\/p>\n\n\n\n

For example, if you go through a breakup, an AI sound system that has learned which genres, bands, and songs you like could detect your emotions and play the perfect sad and angry songs to fit your mood. If you prefer that your sound system plays music that lifts your mood, you could make one of two adjustments: <\/p>\n\n\n\n

  1. Program your sound system to play happier music.<\/li>
  2. Program the system to choose songs based on your preferred psychological philosophy\u2014for example, you could program it to follow the teachings of psychologist Elisabeth K\u00fcbler-Ross and her five stages of grief, playing songs that reflect and elicit denial, anger, bargaining, depression, and acceptance. <\/li><\/ol>\n\n\n\n

    Additionally, your AI sound system could: <\/p>\n\n\n\n