The Artificial Intelligence provided many benefits to the IT industry but it also comes with multiple challenges that need to be addressed. In this Blog Post, we learn about different types of challenges of AI and ML in IT industry.
Bias
AI systems run on programs which are written by humans. The Data contained in programs are responsible for all decisions that AI make. The Biased Data in AI programs can make decisions which can create discrimination among certain group of people or organization. AI can be very manipulative if it is biased and further make decisions that can be used to manipulate and mislead peoples.
Security Issues
AI run on large amounts of training data which contains sensitive information. In case of any cyber attack or breaches, it can expose very sensitive or personal informations which can cause serious disadvantages. Another challenging security issue with AI is cyberattacks. Attackers can hack and manipulate AI algorithm to causing them to make incorrect decisions and predictions.
Lack of Transparency
Lack of Transparency is one of the major challenges of AI in ML in IT industry. In Artificial Intelligence, Lack of Transparency means you don’t have enough knowledge about how AI algorithms work and make decisions and predictions. The AI algorithms are not easily interpretable. This can create mistrust among the users to use AI in their daily lives because some AI algorithm may be biased and can be used to manipulate you.
Lack of Data Quality
AI algorithms run on large amount of Data with the help of which AI can make its decisions and predictions. Good data quality is one of the most important thing which is considered during the process of developing an AI. Lack of Good Data Quality can cause biasness, incorrect decisions and predictions by AI. If the data contains any incorrect information, AI can make wrong decisions and cause misinformation. This can lead to a serious issue in particular fields like healthcare and finance.