With the recent release of GPT-4, discussions around the future of work have taken over the internet, igniting both long-standing concerns and hopes over the mainstream application of AI in the workplace.
And it makes sense—people are using GPT-4 to do a wide range of tasks, from building basic apps and designing app components to developing websites that work from napkin sketches.
Two different viewpoints are beginning to emerge at this time.
On the one hand, some people think that artificial intelligence (AI) will someday replace people in a large number of jobs, causing significant job displacement and unemployment.
However, some believe that AI will enhance human labor and create new career options that will allow us to fully express our creative potential.
Whatever the case, one thing is certain: AI models are becoming frighteningly sophisticated, and investing in complementary talents might pay off in terms of a career.
In light of this, we have investigated the essential supplementary abilities that white-collar workers will want in order to prosper at the outset of the artificial intelligence age.
- Interaction
AI benefits from effective communication for two reasons.
Writing efficient prompts that AI will produce outputs (such as text, photographs, drawings, or code) requires, first and foremost, communication.
It takes less time to achieve optimal results with effective prompting, and it also helps manage the cost of AI solutions, which may quickly spiral out of control with subpar prompting techniques.
Thus, creating clear, evocative instructions is beneficial for optimizing AI usage.
Second, in order to communicate AI concepts and outcomes to stakeholders who are not technical, effective communication skills are required.
To sum up, improving your communication abilities will enable you to engage with AI more effectively and will also enable you to convey these to others in an understandable and efficient way.
- Interpretation And Analysis Of Data
Even though it might seem fairly clear, it’s critical to understand the inputs you provide AI and to be able to evaluate the results it produces.
AI is here to dramatically speed up a lot of activities, but it is not here to unravel the riddles of the cosmos for us—at least not yet.
And knowing what we’re doing and why is still a prerequisite for this to occur.
Because data analysis entails comprehending and analyzing data to obtain insights and make defensible decisions, data analysis and AI go hand in hand.
Put another way, if you don’t know what kind of tasks you are performing or why, there’s no use in solving them faster.
- Verifying The Facts
Even though artificial intelligence (AI) has been automatically verifying facts for a while, human fact-checkers are still required to reach final conclusions regarding the accuracy of material.
This occurs because the information’s context and subtleties can be so complex that only a qualified individual with training and education can fully understand them.
It’s safe to predict that a large number of professionals, including journalists, lawyers, and bloggers, will be transitioning into fact-checking roles due to AI’s amazing ability to produce various kinds of written content. These professionals’ subject-matter expertise will be crucial in evaluating the outputs of AI.
AI will probably be a part of a feedback loop at the same time since it will be able to both create and check for mistakes in content that has been created by humans.
- Problem-Solving And Critical Thinking
Because it allows people to critically and nuancedly assess the results produced by AI models and algorithms, critical thinking is a complimentary AI ability.
Artificial intelligence (AI) is capable of processing enormous volumes of data, spotting patterns, and making highly accurate predictions, but it is not sentient, human-like AI, and as such, it is unable to generate autonomous thought or critical analysis.
People that possess critical thinking abilities are able to analyze and weigh the assumptions and constraints of AI models, take into account other theories or explanations, and weigh the advantages and disadvantages of the results that AI may produce.
- Mechanization
One of the most intriguing supplementary AI skills you can acquire is automation for two reasons.
First, there’s no need to wait; you may start training to become an automation specialist immediately.
Second, the simplest and most direct approach to harnessing AI’s capacity to reach entirely new heights is automation.
For instance, you might as well rely on GPT to expedite the creation of a blog article if you are an AI writer.
Rather than creating each blog post individually, you will now be able to produce hundreds of them more quickly when automation is added to the mix.
In Summary:
The concept of “skilling up” in the age of AI fits with a positive vision in which technology enhances human intelligence rather than completely replaces or threatens it.
The only thing we’ll be dealing with is intelligence augmentation as a whole when AI and humans develop a complementing relationship in which a human-and-AI team’s entire performance exceeds their individual capacity.
We must learn about AI and how to make the most of it if we are to get there, and developing our skills is the first step in that direction.