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Errors in Text and Speech

                  When a computer is trained with American or British accents, it may misinterpret a strong
                  accent saying "Turn on the light” as “Turn on the lice". It may also incorrectly mark a text as
                  misspelt or grammatically wrong based on regional language.


                  Use of Slang and Colloquial Words

                  The use of slang or colloquial language can sometimes be misinterpreted or may not elicit
                  a response. For instance, when a user says, “That game was fire", intending to convey that it
                  was amazing, NLP might misinterpret this as a reference to danger or damage, leading to a
                  negative connotation.



                  Privacy Concerns
                  NLP tools process large amounts of text and speech data to understand what people say. If this
                  data isn't protected properly, it can expose private conversations, personal details, or sensitive
                  information without the user's permission.


                  Misinformation                                 Bias                                   Use of Slang
                                                                 • Historical        Errors in Text    and Colloquial
                  If an NLP system is trained on incorrect       • Representation     and Speech           Words
                  or biased data, it might produce false
                  or misleading answers. This can lead

                  people to believe wrong facts, spread                        Privacy
                  rumours, or make poor decisions based                       Concerns       Misinformation
                  on misinformation.




                                Brainy Fact

                     Google’s BERT model, despite its success, has shown gender bias, associating professions
                     like "nurse" with females and "doctor" with males, highlighting the need for addressing bias

                     in NLP models.



                          Ethical Considerations in Using Statistical Data


                  Ethical consideration in using statistical data means respecting people’s rights, privacy, and
                  dignity. For example, while working on statistical data of healthcare industry, the privacy of

                  personal information like patients’ names and, contact details should not be shared unless
                  people agree.







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