News & Politics

Malala Apologized Publicly for Mistake in Autobiography ‘I am Malala’

Malala Yousafzai who currently is in Birmingham United Kingdom and she is a young education activist hailing from Pakistan has now publicly apologized to everyone for using incomplete name of the Holy Prophet (PBUH) in her autobiography ‘I am Malala’. She added that she was not worried at all about refusal of inauguration of her book in her homeland Pakistan. The girl from Swat (Pakistan) accepted that she has made a huge blunder that caused a clash with peoples’ religious sentiments and she want to apologize to the people all over Pakistan and all over the Muslim world.

An interview with a private television channel, she expressed her deep concerns about terrorism in Pakistan. Her view on this issue was that terrorism was not only spreading all over the country but now it has started to spill across Pakistani borders as well and due to terrorism making inroad into other countries and other nations, people of other nations are also reverting to the use of terrorism in order to achieve their agendas.

She expressed her regret that Pakistan and Afghanistan are currently the prime victims of terrorism and in order to curb the evil of terrorism, a unified struggle was required and war was not the solution to solve the problem of terrorism but peace could be achieved through sincere dialogue. She urged Taliban to apologize to the people and their families who were targeted by them intentionally or accidentally and conceded all sort of damages in the process. She also urged Taliban to adopt democracy in order to spread their message.

Finally Malala is quoted as saying

My only struggle is for the promotion of education, to which every citizen of Pakistan has a right

She also assured that she would visit Pakistan soon. Malala Yousafzai is nominated for Nobel Peace Prize once again.

Jennifer Mccarthy

Jennifer is Associate Professor (Ph.D) at Air University. Research Interests: Informatics; analysis of large-scale biological data sets (genomics, gene expression, proteolytic, networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bio-informatics.

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