When Artificial Intelligence produces biased, inaccurate, and unfair outcomes, it reflects the conditions in which its data was created which could be social, historical or political. This is so because AI learns based on the data it's given.
As artificial intelligence continues to advance, it is importnant to monitor/check/police its outcomes of that specific piece in order to fully understand its behavior and make sure that it's not violating our (human) moral compass
As Automation and narrow artificial intelligence systems continue to change the nature of employment and work, what are the downstream implications
AI Algorithms affect our lives and society in many ways. In this discussion, we will detail techniques one can use to take AI algorithms apart, investigate how they were built, critique them, question their design and development, question their performance – the input and see if the output is the desired one.
This can involve looking for errors in the AI algorithm by investigating the input to see if there were errors which has affected the output.
Also known as Back Engineering. This is when an AI algorithm is deconstructed to reveal its designs, architecture, or to extract knowledge from it.
In this method, a researcher can enjoin the public or a group of people to send in information on how a particular process backed by a software algorithm has affected their lives.
This is the openness about the purpose, structure, and underlying actions of the artificial intelligence algorithms used to search for, process, and deliver information.
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