How to Deal with the AI Bias in Cloud Computing

Based on Gartner Research, 85 percent of AI projects will deliver erroneous outcomes due to bias in data, algorithms, or the teams responsible for managing them until 2022. As simple as this statement seems, it uncovers a huge flaw in the Artificial Intelligence system, commonly known as the AI system. This flaw can make or even break AI technology. Its further usage in different functions will be based on how well the experts are able to tackle the AI bias.

What is the AI Technology Bias?

Termed as an anomaly in machine learning algorithms, Artificial Intelligence is known to be biassed when it generates a preconception during the algorithm development procedure or develops unwanted influences in the training data.

When AI begins developing abnormally from its usual training and understanding, it poses a threat to the developers as well as users. The AI’s ability to emerge new data is also considered as the AI bias and will still be counted under challenges faced during the development of Artificial Intelligence.

To steer clear of such issues, it is upon companies and developers to use appropriate and unbiased data for training AI. And it is upon society and its people to use AI responsibly for a unified benefit.

AI Bias in Cloud Computing

AI has led to an effective revolution that significantly increases productivity and efficiency at capped costs thus making it a crucial addition to cloud computing. Although developing effective and unbiased Artificial Intelligence technology for cloud computing is the task of a well-trained and skillful individual.

Involving AI technology in the cloud computing arena has been a game-changer but only for those enterprises that hired exceptional talent and could afford the development. Although enterprises have been able to afford AI technology development increasingly, the lack of skills in the developers is causing the issues like AI bias and delaying the deployment of Artificial Intelligence in cloud computing.

Dealing with AI Technology Bias in Cloud Computing

To ensure a smooth, error-free AI technology run in cloud computing, it is essential to catch AI biases at an early stage and make necessary corrections. With the availability of relevant tools, finding and improving AI biases has become simpler.

Additionally, some steps and procedures have also been originated to safeguard cloud computing and avoid irresponsible use and development of AI technology. Azure AI services, for one, have some efficient solutions to tackle the situation.


Evaluation of the relevant AI technology, its benefits, and risks thoroughly will help minimise, if not completely eliminate the anomalies and biases.


Certain tools have been introduced to develop AI technology fairly and ethically. Microsoft’s Azure Machine Learning is worth the mention. Enterprises can design their AI technology using Azure AI services ethically, fairly, and responsibly. Azure Machine Learning also ensures security and privacy.

AI Dashboard:

Dashboard technology was developed to be able to assess AI technology’s accuracy and credibility and ensure that your AI technology is being developed for the intended purpose. It can be utilized by enterprises that wish to track even minimal progress and signs of biases effortlessly. Read more about responsible AI here.

Concluding Thoughts: AI Technology Bias

Microsoft has always been one to talk about and apply responsible practices with awareness of its overall consequences. Similarly, the development of AI in Microsoft cloud computing platforms or other areas has ascertained that AI is trained with the right material that is usable and unbiased. Their Machine Learning tactics are reliable as well. With the 365Solutions platform, deploy safe and secure Microsoft AI tools in your enterprise. For seamless support, protection, assistance, reach out to us on +44 20 3880 1220 or simply drop an email at

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