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Future-proof careers: Focus on capabilities AI can’t replicate

Fast-track emotional quotient skills over cognitive skills to prepare for a future of work where we will be competing with AI.
Avsharn Bachoo
By Avsharn Bachoo, Group technology director, Afrocentric Group.
Johannesburg, 05 Jun 2023

Generative artificial intelligence (AI) like ChatGPT and Bard are at an inflection point to revolutionise countless industries, ranging from healthcare, financial services and manufacturing. 

The explosion of AI, like most exponential technologies, is both exciting and daunting. It’s exciting to witness the ways AI is improving society, ranging from radical scientific and medical breakthroughs, to simply managing our diaries − and daunting when we consider the social and personal implications, such as the impact on our careers.

The ability to “think” has always been the differentiator of humans over machines, but today’s AI brings that digital divide closer to reality. As AI continues to disrupt, we must develop new skills to differentiate ourselves. But which ones?

How does AI think?

AI uses algorithms and models to find patterns and relationships in large amounts of data, and then reuses those patterns in new data to make predictions or automate repetitive tasks.

ChatGPT, for example, uses Neural Network Large Language Models to look for patterns of words within large chunks of internet data, and then reuses those patterns in new data to predict subsequent words; for instance: “happy birthday… to you”, or to perform logical calculations like “two plus two is equal to… four”.

Operational vs thinking jobs

Using this technique, AI is transforming industries and the operational workforce at a faster pace. Autonomous self-driving trucks have already forced over 2 000 truck drivers to seek alternative forms of employment in Europe, whereas AI-enabled vehicle production lines shed half a million jobs last year at just one car manufacturer.

But this is just the beginning of the disruption. As AI rapidly disrupts these ‘operational’-type jobs, more ‘thinking’-type jobs − like doctors, investment consultants and scientists − will be further affected.

Broadly speaking, most thinking-type jobs follow a generic three-step workflow of ‘gathering data’, ‘analysing that data’ and finally ‘implementing a course of action’.

As AI continues to disrupt, we must develop new skills to differentiate ourselves.

For instance, doctors perform tests, analyse and interpret the results and finally prescribe a course of treatment to a patient. Similarly, investment consultants gather and analyse client data to understand their risk tolerance, then implement a course of action with an investment strategy.

These thinking-type jobs command higher salaries because of this generic workflow capability. However, AI is now quickly surpassing this capability.

Human limitations

Thinking-type jobs are often plagued with human biases and limitations. For instance, doctors can never keep fully updated on every new publication in their areas of expertise due to the vast volume of new research. Instead, they rely on a small number of personal experiences rather than the complete knowledge of their field. Likewise, management consultants can only experience so many business restructures over their careers, limiting their insights.

ChatGPT’s ability to process massive amounts of data, its immense computing power and advanced algorithms are already solving medical cases that doctors have been unable to unravel for decades, while the general public of investors are discarding expensive consultant-managed funds for superior-performing AI-managed funds.

The value of traditional ‘thinking’ jobs is being eroded.

Beyond the hype

However, it’s easy to get caught in the hype by overestimating AI capabilities and forgetting the emotional quotient (EQ) required to pragmatically succeed in many of these industries.

EQ is the ability to blend a human lens of emotions, feelings, experiences with some curiosity into our thinking. Those that want to stay relevant in their professions will need to focus on these EQ skills and capabilities that AI has difficulty replicating.

AI can diagnose terminal illnesses and recommend treatments better than a doctor. However, it takes a doctor to sit and connect with a patient, appreciate their life situation, while providing empathy and comfort to their diagnosis.

Likewise, AI can analyse complex business problems and make recommendations to improve business performance. However, a CEO is still best suited to motivating a leadership team, steering through heated political conditions, and identifying smart individuals to lead change.

Finally, AI can produce a thesis using explanatory or descriptive research techniques, but it takes a student to wander the world and seek new knowledge with a lens of curiosity from what they see, hear and feel to generate novel ideas.

EQ is often the spark igniting unique discoveries and theories from humanity’s earliest days of inventing the wheel, understanding the laws of gravity, to the development of modern medicine.

EQ eats AI for breakfast

It’s these EQ capabilities like empathy, social understanding and curiosity that are going to become differentiators, as AI provides faster and more accurate decision-making, takes over operational duties and repetitive tasks in the workplace.

Now, more than ever before, it is crucial for us to focus on refining humanity’s defining traits. We can stay ahead of the curve by fast-tracking our EQ skills over cognitive skills to prepare for a future of work where we will be competing with AI.

EQ remains an irreplaceable catalyst in scientific exploration and discovery. For better or worse, these EQ skills will become essential to anyone who wants to stay relevant in their field as AI proliferates.

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