In a recent interview, I heard motivational speaker Jon Acuff tell the interviewer that he sincerely hopes that nobody looks for their dream job as their first “real” job. Instead, he explained, that first job is there primarily to teach someone how to have a job.
How to deal with people. How to handle pressure. How to solve problems.
Those and other similar soft skills will be increasingly important as the workplace sees increasing automation through artificial intelligence and robotics.
Soft Skills Rising in Importance
In a recent study of school-age students, randrr found that students had high career aspirations at a young age, but they were tempered as they got older. However, one of the key recommendations in the report stood out to me (emphasis mine):
Educate based on the real needs of the work world. 40-60% of tomorrow’s jobs don’t exist yet so choosing majors based on job demand trends is improbable. Students will have exposure to a variety of careers throughout their lifetime, especially as technology changes and plays an increasingly predominant role in everyday lives. We may not know what jobs will be available 10-15 years down the road, but we can continue to educate and study trends to help students develop the skills, agility, knowledge, and self-awareness required to find jobs that they love and are a good fit for.
This is a similar approach I’m taking with my new book, Artificial Intelligence for HR. In the book, I look at the core soft skills that machines can’t easily replace, as those will be in higher demand in the coming years as we see more technological advancement and automation in the workplace. Some of the key components that make up the competency model I’m developing:
- Compassion: feeling empathy for others is a highly human skill. While we have algorithms that can detect cancer cells better than humans, who would you rather have deliver that diagnosis, a robot or a living, breathing human?
- Creativity: computers work within constraints and parameters. Build enough rules, and the computer can do anything within those rules without fail. But throw in a level of ambiguity or a new challenge and you see the system crash. People are uniquely designed to handle these types of issues.
- Credibility: predictive algorithms are great–when they are programmed appropriately, that is. if a computer is programmed by poor information, the output will be poor as well. Humans have the ability to see when outputs don’t reflect logical findings or reality and adjust course accordingly.
What skills do you think will be more important in the future, whether within the workforce or for us as HR and talent leaders?