The Illusion of AI Performance: No Comparison, No Truth

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Key Takeaways

1The evaluation of AI is often biased by the lack of comparison with traditional methods.

2Concrete examples show that enthusiasm for AI can mask the absence of real gains.

3A rigorous AI testing method includes clear and documented comparisons to assess its usefulness.

💡Why it matters — Only a critical and comparative evaluation of AI will allow us to fully harness its potential without being misled by illusions of performance.

The Illusion of AI Performance: Without Comparison, There Is No Truth

In our quest for technological innovation, we are often captivated by the apparent prowess of artificial intelligence (AI). However, this fascination can lead us to overestimate its actual capabilities. In the absence of rigorous comparative testing, we risk drawing erroneous conclusions about the added value of these technologies.

When an AI produces a result that impresses us, we tend to accept this success without questioning it. This confirmation bias leads us to believe that the AI was indispensable, without ever confronting this result with what we could have achieved ourselves or through other means. This approach undermines the reliability of our evaluations and needs to be corrected.

To properly assess an AI, it is essential to systematically compare its performance with that obtained without it. Only by doing so can we truly appreciate the impact and effectiveness of these technological tools.

The Pitfalls of Rigorous AI Evaluation

Enthusiasm for new technologies can play tricks on us. When an AI offers us a seemingly brilliant solution, our confirmation bias comes into play. We want to believe that the tool works perfectly, without taking the time to verify whether a similar result could have been achieved by other means.

Concrete Examples

Automatic Email Correction: An employee uses ChatGPT to improve a professional email. The final message is flawless, and the user concludes that the AI was a valuable aid. However, without comparing it to a manually proofread version or one reviewed by a colleague, this conclusion remains speculative.
Meeting Summary: After a meeting, an AI generates a report. The manager is pleased with the time saved. But has he compared this document with what an experienced assistant could have produced? Perhaps the latter would have provided a more detailed and better-structured summary.
Creative Ideation: During a brainstorming session, an AI suggests marketing campaign ideas. The team is enthusiastic, thinking that these ideas would never have emerged without the AI. Yet, if the team had taken more time or consulted an expert, the results could have been just as innovative.

Conditions for Effective Comparison

To seriously evaluate the contribution of an AI, it is crucial to ask several questions:

Is the result obtained through the AI truly superior to that obtained without it?
At equal cost and time, does the AI offer a measurable advantage, whether in terms of quality or quantity?
What biases does the AI introduce, such as excessive simplification or standardization of ideas?

Without this in-depth questioning, any conclusion about the effectiveness of an AI remains subjective and potentially misleading.

Methodology for Reliable AI Testing

To properly evaluate an AI, here is a simple method to follow:

Define a specific objective: What is the purpose of using the AI? To produce text, generate ideas, sort data?
First, create a version without AI: Generate the desired result using only your own resources.
Then, produce the version with AI: Use the tool to achieve the same objective, trying not to be influenced by the first test.
Compare according to defined criteria: Evaluate the quality, speed, cost, originality, clarity, and accuracy of both versions.
Document and assess: Keep a written record of the comparison and explain why the AI provides (or does not provide) real added value.

This approach transforms a subjective impression into an informed judgment based on concrete evidence.

The Importance of Strengthened Critical Thinking

In a world where AI tools are multiplying, our professional future will depend on our ability to evaluate these technologies critically and comparatively. Those who can truly measure the value of artificial assistance, rather than assume it, will be the true pioneers of the digital age.

As Francis Bacon wrote in 1620: "Man prefers to believe what he would prefer to be true." Now more than ever, we must fight against this natural tendency to make the most of machines.

And you, how do you evaluate today what AI truly brings you?