75% of workers ask AI questions instead of colleagues - with potentially serious consequences

Introduction

In today's workplace, artificial intelligence is becoming an increasingly common tool for employees to seek answers and solve problems. However, a recent study shows that 75% of workers are turning to AI instead of asking their colleagues for help. While AI can be incredibly helpful, relying too heavily on it without human interaction can lead to serious consequences. In this tutorial, you'll learn how to create a simple AI assistant that can help you understand when it's better to ask a human versus using AI.

This tutorial will teach you how to build a basic decision-making tool that helps determine the best approach for getting help with work tasks. You'll use Python to create this tool and understand how to balance AI and human collaboration in your workplace.

Prerequisites

To follow along with this tutorial, you'll need:

• A computer with internet access
• Python 3.6 or higher installed on your system
• A text editor (like VS Code, Sublime Text, or even Notepad)
• Basic understanding of how to open and run Python files

No prior AI experience is required - this tutorial will guide you through everything you need to know.

Step-by-Step Instructions

Step 1: Set Up Your Python Environment

First, we need to make sure your computer is ready to run Python code. Open your command prompt or terminal and type:

python --version

If you see a version number (like 3.8 or higher), you're good to go. If not, you'll need to download and install Python from python.org.

Step 2: Create a New Python File

Create a new file called ai_vs_human_helper.py using your text editor. This file will contain our decision-making tool.

Step 3: Import Required Libraries

At the top of your Python file, add the following code:

import random

# This imports the random library that we'll use to make decisions

Why we're doing this: The random library helps us simulate decision-making by randomly choosing between AI and human approaches, which is perfect for our learning exercise.

Step 4: Define Your Decision Criteria

Now, let's create a function that helps us determine when to use AI versus human help. Add this code to your file:

def get_help_advice(task_type, complexity):
    """Determine whether to use AI or human help based on task characteristics"""
    
    # Simple rules to guide our decision
    if task_type == "technical" and complexity == "high":
        return "Ask a human colleague - this is a complex technical problem"
    elif task_type == "routine" and complexity == "low":
        return "Use AI - this is a simple, repetitive task"
    elif task_type == "creative" and complexity == "medium":
        return "Consider both AI and human help - this requires creativity"
    else:
        # Default decision using random choice
        choices = ["Use AI", "Ask a human colleague"]
        return random.choice(choices)

Why we're doing this: This function creates a simple decision-making framework that helps determine the best approach based on what kind of task you're working on and how complex it is. This simulates how organizations might make decisions about when to use AI versus human expertise.

Step 5: Create the Main Program Loop

Next, we'll create a loop that allows users to input different tasks and get advice:

def main():
    print("AI vs Human Help Decision Assistant")
    print("====================================")
    
    while True:
        print("\nWhat type of task are you working on?")
        print("1. Technical")
        print("2. Routine")
        print("3. Creative")
        
        task_choice = input("Enter your choice (1-3) or 'quit' to exit: ")
        
        if task_choice.lower() == 'quit':
            print("Thanks for using the help decision assistant!")
            break
        
        # Get complexity level
        print("\nWhat is the complexity level?")
        print("1. Low")
        print("2. Medium")
        print("3. High")
        
        complexity_choice = input("Enter your choice (1-3): ")
        
        # Convert choices to actual values
        task_types = {"1": "technical", "2": "routine", "3": "creative"}
        complexity_levels = {"1": "low", "2": "medium", "3": "high"}
        
        if task_choice in task_types and complexity_choice in complexity_levels:
            task = task_types[task_choice]
            complexity = complexity_levels[complexity_choice]
            
            advice = get_help_advice(task, complexity)
            print(f"\nAdvice: {advice}")
        else:
            print("Invalid input. Please try again.")

# Run the program
if __name__ == "__main__":
    main()

Why we're doing this: This creates an interactive program where you can test different scenarios. It simulates how employees might think about when to use AI versus human help in real workplace situations.

Step 6: Test Your Decision Assistant

Save your Python file and run it by typing:

python ai_vs_human_helper.py

Try different combinations of task types and complexity levels to see how the decision assistant responds. For example:

• Choose '1' for technical and '3' for high complexity - you should get advice to ask a human
• Choose '2' for routine and '1' for low complexity - you should get advice to use AI

Why we're doing this: Testing helps you understand how the decision-making logic works and how different inputs affect the output. This is crucial for understanding when AI might be better than human help and vice versa.

Step 7: Expand Your Understanding

Now that you have a working decision assistant, think about how you might improve it:

• What other factors might influence whether to use AI or human help?
• How could you make the decision process more sophisticated?
• What are the potential risks of relying too heavily on AI?

Why we're doing this: This reflection helps you understand the broader implications of AI usage in the workplace, which is the core message of the news article about 75% of workers asking AI instead of colleagues.

Summary

In this tutorial, you've created a simple decision-making tool that helps determine when to use AI versus human help in the workplace. You learned how to:

1. Set up a Python environment
2. Create functions to make decisions based on task characteristics
3. Build an interactive program that accepts user input
4. Understand the balance between AI and human collaboration

This tool demonstrates the key insight from the news article: while AI can be helpful for routine tasks, complex problems often require human expertise. By creating this assistant, you've gained practical experience in thinking about how to balance these different approaches in your own work environment.

Remember, the goal isn't to eliminate human interaction, but to make better decisions about when to use AI and when to collaborate with colleagues. This balance is crucial for maintaining both efficiency and the human connections that make workplaces successful.