Artificial intelligence is no longer a test in the United Arab Emirates. It is now a standard procedure in business. Businesses employ AI for data analysis, risk assessment, customer service automation, and even document drafting. The nation is making significant investments in its digital future, and companies are following suit. However, responsibility grows along with opportunities.
The idea that a system should be held accountable for its decisions is one of the most prevalent misunderstandings. This isn’t the situation in reality. An algorithm is not a human being. It is not responsible. The organization that implements and depends on the system is always accountable.
Regulators will ask direct questions if AI suggests a loan, rejects an insurance claim, or affects a hiring decision: What safeguards were in place? Who examined the system? Were oversight procedures put in place? How “intelligent” the software was is irrelevant to the courts. They are worried about the company’s level of responsibility. Automation does not equate to intelligence.
Terminology presents another difficulty. Many businesses refer to any digital technology as artificial intelligence. However, there is a distinct distinction between machine learning and basic automation. A system that adheres to predetermined guidelines is predictable. A system that adjusts its outputs after learning from data is not.
This is when explainability and transparency issues come up. The business must be prepared to provide an explanation if a customer is refused a service. That explanation might be more challenging when a learning model makes the choice. Regulatory risk also rises as a result. It could seem insignificant to misclassify technology. Contracts, insurance coverage, risk assessments, and connections with regulators are all affected.
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