Blogs / AI and the Redefinition of Merit: How Talent Evaluation Criteria Are Changing

AI and the Redefinition of Merit: How Talent Evaluation Criteria Are Changing

هوش مصنوعی و بازتعریف شایستگی: چگونه معیارهای ارزیابی استعداد تغییر می‌کنند؟

Introduction

A student who spends hours in the library trying to write a standard academic paper now faces a new reality: a classmate can produce a more coherent—and sometimes higher-quality—text in just a few minutes with the help of ChatGPT. An employee with years of experience in data analysis encounters a similar situation, as artificial intelligence tools perform the same analyses with greater accuracy and at a speed dozens of times faster. These scenes no longer belong to the future or to science fiction; they are part of our everyday world. Artificial intelligence has not only transformed tools and technologies, but has fundamentally called the notion of “competence” into question.
In a world where machines can write poetry, generate programming code, provide medical diagnoses, and even create music, we can no longer measure merit solely by traditional criteria such as memorization, calculation speed, or pattern repetition. This transformation is one of the deepest philosophical, social, and economic challenges of our era, requiring comprehensive understanding and rethinking at all levels.

Merit in the Pre-AI Era: A Look at the Past

To understand the current transformation, we must first look at the traditional definition of merit. Throughout history, merit was typically measured by criteria such as specialized knowledge, practical experience, technical skills, and problem-solving ability. A good engineer was someone who memorized formulas and could perform complex calculations quickly. A successful writer was someone who knew grammar perfectly and could sit for hours and write.
But these criteria were based on the implicit assumption that access to information is limited and humans must be the main tool for processing and production. In that world, a person's value was measured by what they had stored in their mind and the processing speed of their brain. Libraries were treasure troves of knowledge, and access to experts was limited and expensive.
Traditional Merit Criterion Description
Specialized Knowledge Memorization of information, formulas, and complex concepts
Practical Experience Years of work in a specific field
Technical Skills Ability to use specific tools and techniques
Speed and Accuracy Fast and accurate performance of repetitive tasks

The Advent of AI: The Moment of Transformation

With the emergence of Large Language Models like GPT, Claude, and Gemini, everything changed. Suddenly, many skills that had taken decades to acquire became available to everyone. All it took was writing a smart prompt to:
  • Generate professional text in any style and subject
  • Write complex programming code in seconds
  • Perform data analysis with high accuracy in short time
  • Create graphic design with tools like Midjourney and DALL-E
  • Produce professional videos with AI video creation tools
This transformation raised a fundamental question: If machines can do all these things, what is human merit?

Real Examples: Change in Practice

Programming: From Memorizing Syntax to Designing Architecture

A traditional programmer had to memorize syntax of different languages, implement complex algorithms, and spend hours debugging. But today, tools like GitHub Copilot and Claude Code can:
  • Automatically complete code
  • Identify and fix bugs
  • Optimize code
  • Write complete documentation
Now, a programmer's merit is no longer in memorizing syntax, but in understanding business needs, designing scalable architecture, and strategic decision-making. The ability to ask the right question of AI and intelligently integrate its outputs into a project has become a key skill.

Writing: From Grammar to Conceptual Creativity

ChatGPT and Claude can write articles, stories, poetry, and even novels. A modern writer can no longer stand out solely by mastering grammar. The merit of a modern writer lies in:
  • Unique voice and specific perspective
  • Deep understanding of human spirit and emotions
  • True storytelling, not just arranging words
  • Smart editing and guidance of AI to produce quality content

Medicine: From Memorizing Symptoms to Comprehensive Diagnosis

AI systems in medicine can diagnose diseases with very high accuracy, analyze medical images, and even discover new drugs. But today's competent physician is someone who:
  • Has empathy and human connection
  • Makes complex ethical decisions
  • Sees AI as a tool to strengthen diagnosis, not a replacement
  • Views the patient as a complete human, not a set of symptoms

New Criteria of Merit: What Matters Now?

1. Meta-Cognitive Skills: Thinking About Thinking

In the age of AI, the ability to learn, adapt, and think critically is more important than any specific knowledge. Those who can:
  • Learn how to learn (Meta-Learning)
  • Adapt to rapid changes
  • Critically analyze information
  • Recognize AI biases and limitations
These individuals will be more successful in the new world.

2. Prompt Engineering: The Art of Conversing with Machines

The ability to write effective prompts has become one of the key skills. This means:
  • Precise formulation of questions
  • Step-by-step guidance of AI
  • Extracting the best output from language models
  • Continuous iteration and improvement until reaching the desired result
Someone who can write an excellent prompt is more competent than someone with years of experience who doesn't know how to use AI.

3. Conceptual Creativity: Ideation Not Execution

When AI can execute, the main value is in ideation. Those who can:
  • Pose novel questions
  • See problems from new angles
  • Combine different ideas
  • Envision fundamental innovations
These people will always be valuable, because AI can imitate but can hardly invent.

4. Interpersonal Skills: Empathy, Communication, and Leadership

One of the biggest differences between humans and machines is the ability for deep emotional connection. In the world of AI, skills such as:
  • True empathy and understanding others' emotions
  • Human-centered leadership
  • Teamwork and collaboration
  • Negotiation and persuasion
These are skills that AI can hardly replace.

5. Systems Thinking: Seeing the Big Picture

Artificial Intelligence is excellent at specific tasks, but understanding complex relationships, long-term consequences, and systemic impacts still requires the human mind. Those who can:
  • See systems holistically
  • Predict indirect consequences
  • Understand complex interactions
  • Make strategic decisions
These individuals will play a key role in organizations and society.
Traditional Skill New Skill (AI Era)
Memorization Critical thinking and analysis
Precise execution Creative ideation
Deep expertise in one field Interdisciplinary knowledge
Individual work Human-AI collaboration
Pattern repetition Adaptability and continuous learning

Challenges and Risks: A Realistic View

1. Identity Crisis and Personal Value

Many people derive their identity from their profession and expertise. When AI can do many things better, a crisis of meaning emerges. People who have spent years learning a skill may feel their value has been lost.

2. Digital Divide and Inequality

Those who have access to AI tools and can use them will have a huge advantage over others. This can intensify economic inequality and deepen the gap between social classes.

3. Cognitive Dependency on AI

Excessive use of AI can lead to cognitive dependency. When we resort to AI for every question, decision, or problem, we may lose our cognitive abilities. This is the same phenomenon that happened with GPS and our spatial memory.

4. Decline in Social Skills

With increased interaction with AI and decreased human interaction, social skills may weaken. This is particularly concerning for Generation Alpha who are growing up with AI.

5. Loss of the Value of Effort

In a world where AI can do anything instantly, the value of effort and the learning process may fade. This can lead to a culture of "instant results" and impatience with real challenges.

Solutions: How to Remain Competent in the AI Era?

1. Continuous Learning and Adaptability

The most important merit in the AI era is the ability for continuous learning. We must:
  • Be flexible and ready to learn
  • Maintain intellectual curiosity
  • Step out of our comfort zone
  • Make peace with changes
Continuous education and accepting the reality that no skill is sufficient forever is the key to success.

2. Combining Human and Artificial Intelligence

Instead of seeing AI as a competitor, we should see it as a partner. Optimal use of AI tools alongside human judgment yields the best results. For example:
  • Design by human, execution by AI
  • Strategy by human, tactics by AI
  • Decision-making by human, data analysis by AI

3. Focus on Uniquely Human Skills

We must invest in skills that AI cannot replace:
  • True creativity and innovation
  • Empathy and emotional intelligence
  • Ethical thinking and value judgment
  • Leadership and inspiration
  • Aesthetic sense and taste

4. Developing Digital and AI Literacy

We must understand AI's language and logic. This includes:

5. Maintaining Cognitive Health

To prevent cognitive dependency, we must:
  • Have times without AI
  • Practice basic skills (mental math, handwriting, problem-solving)
  • Use our brain as a muscle
  • Perform brain recovery exercises

Educational System: Need for Fundamental Transformation

Our educational system is still designed based on 19th and 20th century models that focus on memorization and pattern repetition. In the AI era, we need a fundamental transformation:

What Must Change:

  1. From memorization to critical thinking: Instead of rote exams, we should teach students to analyze, evaluate, and create
  2. From cheating to collaborating with AI: Using AI should not be considered "cheating," but we should teach how to use it ethically and effectively
  3. From one path to multiple paths: Choosing a major in the AI era should be more flexible and diverse
  4. From pure theory to project-based: Learning should be accompanied by solving real problems

Teaching Children:

Teaching AI to children should be part of the curriculum, but not in a purely technical form. Rather:
  • Computational thinking and problem-solving
  • Digital ethics and responsible use of technology
  • Creativity and critical thinking alongside digital tools
  • Social skills and human connection

Job Market: Changing the Definition of Career Success

In the future job market, the traditional resume loses its value. University degrees and years of experience no longer guarantee competence. Instead:

New Hiring Criteria:

  1. Real portfolio: Showing real projects is more important than degrees
  2. Fast learning ability: Adaptability to new tools
  3. Problem-solving skill: Not memorizing solutions
  4. Collaboration with AI: Demonstrating mastery of AI tools
  5. Creative thinking: Ability to present new ideas

Professions in Transformation:

Many jobs have been affected by AI:
  • Accounting: From bookkeeping to strategic financial consulting
  • Law: From legal research to negotiation and strategy
  • Journalism: From reporting to deep analysis and specialized research
  • Design: From technical execution to conceptualization and branding

Philosophical Perspectives: Does Human Merit Have Meaning?

This transformation raises deep philosophical questions:

1. Is Human Value in What They Do?

If machines do all jobs better, do humans have intrinsic value? This question leads us to rethink the concept of work, purpose, and meaning of life.

2. Is Process More Important Than Result?

When AI can give results instantly, does the process of learning and effort still have value? Many believe the real value is in the journey, not the destination, but the AI era challenges this belief.

3. Difference Between Ability and Merit

Perhaps we should distinguish between technical ability (which AI can have) and human merit (which includes judgment, ethics, and meaning).

The Future: Probable Scenarios

Scenario 1: Successful Coexistence

In this scenario, humans and AI work together. AI agents become assistants that enhance human capabilities rather than replace them. Merit is defined as the ability to coordinate effectively with intelligent systems.

Scenario 2: Class Division

In this scenario, society divides into two groups: those who understand and use AI and those who cannot. Economic and social gaps deepen, and the concept of merit becomes completely polarized.

Scenario 3: Fundamental Transformation

In this scenario, society is completely redefined. Universal Basic Income is established, work is no longer the center of human identity, and merit depends on quality of life, personal growth, and social participation.

Scenario 4: The Emergence of Artificial Superintelligence (ASI)

In the most extreme scenario, AI reaches a point far beyond humans. In this case, the concept of human merit may become meaningless, and we need completely new frameworks to understand our place.

Conclusion: Continuous Redefinition

AI is not the end of human merit, but its continuous redefinition. We are at a historical moment where:
  • Traditional criteria are insufficient
  • New criteria are being formed
  • The future is in our hands to manage this transformation
Merit in the AI era means the ability to adapt, continuous learning, effective collaboration with machines, and maintaining humanity. We need to:
  1. Transform education
  2. Constantly upgrade ourselves
  3. Preserve human values
  4. Use technology as a tool, not a replacement
Ultimately, true merit may lie in our ability to remain human in the AI world—with all the creativity, empathy, ethics, and meaning that this word carries. The main challenge is not competing with machines, but finding our unique human place in coexistence with them.
Are we ready to redefine our merit? Can we not only survive but flourish in this transformation? The answer to this question will shape the future of generations to come.