Assessment 2 Blog

7/28/2024

 

A Critical Evaluation  

Assessment 2  

1. This week I used critical thinking and paired it with digital literacy skills to investigate about a pressing problem within out technological community: Biased in Artificial Intelligence. 

2. I have been exploring this topic, which involves applying AI so that humans are removed from the equation, in hopes that there will not be mistakes or biased, and that the job can be done easier. 

3. This is when AI is used under the pretence that it will take human error or human biased out of the equation, when recruiting people or vetting job candidates, but in turn does the opposite and it learns racial or misogynistic biased, as it is programmed to do so. 

4. The misuse of AI specifically pertaining to the bias it can form is a huge issue, because it means that it is not only allowing companies and entities to make racists or misogynistic decisions, but by making the AI do this, it is also removing human accountability for these mistakes, so if not dealt with, could become a bigger systemic issue for the world. 

5. By explaining the significance of the issue, we can begin to push companies to re work their Artificial Intelligence algorithms, so that instead of having the world fear the uprise of AI we can become sure that it is something to welcome and something we can trust in 

6. To do this we must find who is being targeted by the biased algorithms, and allow them to have a voice in the re structure of its serviced, for example as the Harvard Business Review said, ‘ Invest more in diversifying the AI field itself. A more diverse AI community would be better equipped to… spot bias and engage communities effected’ James Manyika. (2019) In other words, you ca not fix the problem by only letting the people who created the problem into the spaces. 

7/8. The issues origins will vary from how the AI was conceived, but its most likely happening because the AI has been taught to make decisions based on decisions humans have made from the past, so it has learnt from out bad behaviour and in turn grown in into its intelligence. 

9. The AI gathering pre learnt ad intel, will affect minorities of all kind, and how they are chosen for the fields in which AI is being used. 

10. I have used an article from the Harvard Business Review to evaluate using the CRAAP method. AI and Machine Learning. What Do We Do About the Biases in AI? (2019) Retrieved 22 July 2024, from https://hbr.org/2019/10/what-do-we-do-about-the-biases-in-ai 

11. To see me evaluating the CRAAP method on my chosen article click here

12. I used the CRAAP method because I felt as though it was very clear and simple to follow, it allowed me to outweigh whether the article was a good source or not in a very simple manner.