Myth Buster: As you age, you don’t want to and can’t learn about AI

Myth Buster: As you age, you don’t want to and can’t learn about AI

By Sharon Lewis

The availability of intelligent technology is here. On a daily basis, we read articles that embrace the changes that such technology represents, as well as articles that breed fear and gloom in the advent of this new world.

It’s no surprise that we see a discrepancy between the employer perceptions around employee willingness to work with AI.

·      Over 2/3 of the executives interviewed for a recent Accenture survey see AI positively reshaping their industry, yet only 3% of the interviewed employers plan to significantly invest in re-skilling the workforce for this AI-driven future.

·      Nearly 1/4 of them point to worker resistance in using the intelligent technologies as one of the top three challenges that employers have in implementing these new intelligent technologies. 

Misperception #1: Workers DO want to learn and use new skills.

Additional Accenture research with the worker audience, found that:

·      62% believe that AI will have a positive impact on their work

·      67% of workers believe it will be important to learn the new skills to work with AI in the next three to five years

·      31% believe that they themselves are primarily responsible for keeping up their own skills

Misperception #2: Outdated Stereotypes are Stubborn to Change

This recent HBR article highlights the outdated stereotypes surrounding the worker who has “decades of experience". Perhaps the funniest irony with the article is its name: When No One Retires.

·      In the United States, about 10,000 people turn 65 each day, and one in five Americans will be 65 or older by 2030.

·      Typical 60-something workers today are healthy, experienced, and motivated to make meaningful contributions.

·      The five generational workplace is here. As the article suggests, leaders must bravely say, “We reject the assumption that people become less tech-savvy as they get older” and “We will fight the impulse to put only our youngest employees on new initiatives.” 

Biases are real and often unfounded. How can we help today’s leaders to accelerate the preparation of the workforce for tomorrow’s technology? Moreover, how can we do such with inclusion across all worker profiles?

Please share your thoughts on these relevant topics:

  • As a manager, have you hired someone for your team that is older than you are? What was the best part of the experience? What was the most deliberate part of the experience? For example:
  1. Did you find yourself assigning this new employee to a technical skills class?
  2. Did you consider assigning this new staff member two internal mentors in their department: One mentor being a peer and the other mentor being a recent graduate?
  • According to the McKinsey Global Institute, up to 375 million workers, globally, may need to switch occupational categories by 2030. Do you see this as an opportunity to adjust your expertise or an opportunity to rewire your expertise into a new line of work?
  1. Conceptually, can you imagine the difference between a category switch that takes you from nurse type A to nurse type B?
  2. Now, conceptually imagine a second type of category switch takes place when you go from working in trucking to a job in healthcare doing something completely different.
  3. How are you thinking about this adjustment vs re-invention for yourself?

Myth Buster: As you age you don’t want to and can’t learn about AI

This article was also published for amazing.community on Medium

#disruptaging #reskill #adaptability



Susan L. Harper, Esq.

Advocacy, Law, Strategy, Communications; Treasurer, New York State Bar Association

5y

Those who prevail are always learning.

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