Elon Musk once stated, “With Artificial Intelligence , we are summoning the demons.
This quote highlights the surge impact of AI and machine learning in our everyday life that can be startling too. Though, there is no suspicion in the fact that AI and machine learning are the name of efficiency and sophistication but on the other hand, have some swindling effect too. The below stated pointers are some of the ethical implications of AI and Machine Learning in everyday life:

PRIVACY AND SECURITY:
AI Algorithms are used to process data and this data may also contain personal information of the individuals that can be used fraudulently. However , the user who has designed the algorithms should be responsible for the decision making of the AI.

BIAS ALGORITHM:
The places where AI is implemented like libraries, stores or the places where recruitment is taken place , have become a source of bias algorithm. Partisanship takes place based on the personal information of the individuals that may include discrimination on the basis of color, caste , creed ,gender among them .This leads to the selection in a total unfair means.

INCREASING UNEMPLOYMENT RATE:
AI generated tools are playing a vital role in the displacement of jobs of people. The human based tasks like content writing , making presentations and research on any topic and many more , are indubitably completed by AI algorithms and machine learning.

THREATENING TO HUMAN EXISTENCE:
One of the most alarming implications of AI and machine learning is that they could easily be used to harm human existence. As these machines possess human intelligence, they can easily be programmed to be self aware and to contemplate humans as a threat to them. In this way, these machines can be used for the purpose of wars or terrorism .

CONCLUSION:
The user who implements and processes the algorithms should be responsible for the safety of the consequences and should make sure that the system is working for the betterment of the society. In this way, the flustering upshots of AI and machine learning implementation can be eradicated.