Page 186 - Artificial Intellegence_v2.0_Class_9
P. 186
working, what exactly the algorithm is doing and what method it is using during the process. Since there is no
insight, it is called a Black Box problem. This happens because the data that the AI system is working on, goes
through a lot of neural nodes which mutates it, making it extremely difficult to determine the working and the
source of the problem.
Task
Take smartphone of your father after taking his permission and make a list of apps installed on it. Now,
surf the Internet and find out the ethical and privacy concerns related to these apps. Write YES if any
ethical or privacy concern related to the app, otherwise write NO.
Sr. No. App Name Ethical or Privacy Concern
AI Bias
Can we trust AI systems? Not yet. AI technology may inherit human biases due to biases in training data.
Consider the following examples:
Example 1: Why are most images that show up when you do an image search for “doctor” are white men?
Example 2: Why are most images that show up when you do an image search for “Shirts” are for men?
Example 3: Why do most search results show “Women’s Salon” when searched for salons nearby?
Example 4: Why do virtual assistants have female voices?
“AI bias is a phenomenon that occurs when an algorithm produces results that are systematically
prejudiced towards certain gender, language, race, wealth, etc., and therefore, produces skewed or
learned output. Algorithms can have built-in biases because they are created by individuals who
have conscious or unconscious preferences that may go undiscovered until the algorithms are used
publically.”
What are the Sources of AI Bias?
Some of the sources of AI Bias are:
• Data: AI systems are the result of the data that is fed into them. The data used to train the AI system is the first
step to check for biasness. The dataset for AI systems should be realistic and need to be of a sufficient size.
184 Touchpad Artificial Intelligence (Ver. 2.0)-IX

