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Key Takeaways Corrupted training data is a costly threat that undermines AI’s effectiveness and can lead to poor decisions, wasted resources, loss of trust and erosion of competitive advantage.
Corruption stems from issues like code reuse errors, incorrect data labelling and even intentional sabotage.
For effective and safe AI systems, leaders must ensure that they are trained properly and constantly monitored for accuracy.
These days, many business leaders will punt artificial intelligence as a main source of gaining an advantage over competitors. They are willing to splurge money on investing in AI and bringing in so-called high-quality teams to develop it.
Beneath all of this is often something unaddressed — widespread data corruption in training datasets. This can compromise your entire operation from the start. It is the destruction of data integrity from the start. It is something that will typically not be featured on a financial statement. However, it can be catastrophic as it impacts ROI, the strategy of a business and the trust of investors.
What causes the corruption?
Data corruption in AI is not just due to mistyped data. It tends to start in the learning process and happens as a result of a few factors. It can happen when a code used to identify a product is used again for an item that may be unrelated. This can cause an AI system to get confused. For example, it may suggest car oil to a customer looking for toys for a baby.
In incorrect data labelling, misleading instructions or tired workers may have misleading information in the form of pictures and writing. The AI model, which is learning, will thus learn from incorrect labels, and its ability to be accurate when it comes to giving advice and instructions will be compromised.
In the competitive business environment that we are in, it’s also possible for others to put misleading information into your systems in order to sabotage your business. They can do this through corrupted information, making changes to the attributes of your images or changes to your text. This can cause confusion to the AI that will be studying your business.
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