How Will AI Affect Your Job?

If you believe the hype, artificial intelligence is coming after every job in every sector at every skill level, and jobs are at risk of going away at an unprecedented pace and scale.

Such dramatic pronouncements are unfounded.

The concern about AI affecting jobs is real, but it is hardly a new type of crisis for humanity.  This march toward automation, higher efficiency, more productivity and a higher standard of living has existed since the dawn of industry. This has been true of many productivity-enhancing technologies over the centuries: disruption occurred and jobs were impacted, especially in the case of lower level, more repetitive jobs that could be automated.

With AI, the disruption will be different. AI doesn’t automate repetitive or formulaic tasks as was previously done. Instead, it automates human decision making – not based on a prescribed formula, but by “learning” how to make the “right” decision from the data.  For example, computer automation could use a formula to rank flights based on cost, time and class of service.  But AI could rank the flights based on learning who preferred which flight at what time and under what circumstances for which cost from a dataset of all existing flights. In this case, AI learns who you are and what you need.

PREMIUM CONTENT: Preparing your firm for a world of AI – Webinar Replay

A machine’s ability to make human decisions without a prescribed formula is very powerful and therefore this capability will disrupt jobs.  And the impact on jobs will be faster and very different from what we’ve seen in the past.  With AI, the level of job doesn’t predict the impact. Instead, jobs across a wide spectrum, including many high-level jobs, will be impacted.

Analyzing this disruption and more accurately predicting the impact, requires a framework for understanding how AI affects jobs and under what circumstances. My company uses AI to connect employers to the best specialty recruiters. Our technology analyzes thousands of job descriptions and rates recruiters’ effectiveness. This gives us a unique vantage point to see how jobs are changing in real time. In particular, we have observed AI’s impact on jobs in three categories: assist, commoditize and eliminate.

AI assists people and enables them to do their jobs better. In many cases AI can provide sophisticated analysis to assist us so we can be better at our jobs, but humans are still very much needed. For example, AI can highlight cell structures that might be cancerous, but biopsies, sophisticated testing and the judgement of an oncologist are still required to ensure an accurate diagnosis.

In recruiting, AI is used to narrow potential candidates to a short list through technologies such as chat bots, candidate scoring and other techniques.  Even so, the recruiter is still needed to interpret the information, determine who the best person to hire is and, in many cases, convince that person to change jobs.

AI commoditizes jobs and enables more people to do them. When we say a job has been “commoditized,” it means the position can be done by a large number of people with little specific education or experience.

A great example of commoditization can be seen in the taxi business.  Previously, drivers needed to know when, where and how to get good fares. They also needed extensive geographic knowledge to be successful.  Now, rideshare services and GPS have transformed the industry in a way that most humans can do what is needed – accept a requested ride and follow the GPS from one location to another – with little or no training.   As a result, many more people are now available to do the job, thus devaluing, or “commoditizing” it.  This isn’t great for old-school taxi drivers, but the news is very good for rideshare customers who enjoy widely available, low cost, on demand transportation.

AI eliminates jobs, displacing the people who do them. Clearly, AI is most disruptive when it performs the entire job function, thereby eliminating the job. Not all that long ago, travel agents had exclusive access to flight and hotel information, and the agent’s main role was to figure out which option fit a requested itinerary. But, finding the best itinerary based on a set of options is no longer as complex a task.  Once the information became available and the algorithms reached a reasonable level of sophistication, AI was quickly able to match and then beat what a travel agent could do for a majority trips, putting many travel agents out of work.

It can sometimes be hard to see this type of disruption coming. In my next post, I will discuss a model that helps to analyze which jobs will be affected, how quickly and with what type of disruption.

Ken Lazarus

Ken Lazarus
Ken Lazarus is CEO of Scout Exchange

Ken Lazarus

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