How I drew out an Ai System to Fail !

 

"Drawing out an AI system to fail" refers to intentionally designing, prompting, or testing an AI in ways that expose its weaknesses, limitations, or failure modes. - Mr. Perplexity Ai

With the advent of my excitement state, especially after visiting the Ai Symposium held in Delhi (India), I decided to push the Claude Ai to a stress Test and "bingo!" - it failed.

My learnings from the experiment are as follows :

1. Firstly give a "simple looking" yet a very complex task for the Ai to perform
2. Ensure that you gradually load with additional tasks based on its responses
3. Let the Ai assume the additional inputs that it need to consider
4. Respond only to the questions for which the Ai is seeking responses
5. If the Ai makes improper assumptions, just point out the same
6. Never preempt the Ai not to make any wrong assumptions
7. Let the Ai feel that you are very comfortable in answering the questions
8. Observe whether the Ai is going in circles - Fixing one issue leading to another etc
9. After completing your desired iterations, then point out to the AI about the frustrating results
10. At this stage, the Ai will accept failure

Ai Systems need to be Smart, that is the very purpose for which they are being built.

Whilst minor bugs in the Ai will not cost much, but failures in the Ai system to arrive at a solution can be very expensive and catastrophic in certain cases. Startups and Enterprises should be sensitive to this before they release their products.

Startups and Enterprises need to Test their Ai Solutions rigorously before they launch the same to internal/external stakeholders. In early 2000s, software companies used to launch software products with bugs, which customers used to unearth and report back during the implementation phase. In this Ai age, companies do not have that luxury. If the customers find the Ai to be prone to failure, they will lose faith in the company and will switch to competitions/substitutes. Ai Solution Testing Roadmap should be as critical and prioritised as any Feature Roadmap. Whilst it is not possible to have 100% Test Cases for an Ai Solution, any Startup or SME who do not deploy adequate "Stress Testing" of their Ai Solutions, will find it extremely difficult to survive/scale in the long run.

Smart Ai Systems tend to acquire customers at a disruptive speed.