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Could the FTC Order to Delete Biased Algorithms in the Near Future?

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Continuing with my endeavor to further understand algorithmic bias, as well as learning about what is being done about it, I recently stumbled upon a fascinating article in Protocol that talked about how the Federal Trade Commission (FTC) had instructed the company WW International to delete all the illegally obtained private data and delete all algorithms derived from this data. The subject was intriguing, “a new standard for penalizing tech companies that violate privacy and use deceptive data practices: algorithmic destruction” (Kaye, 2022). Started looking further into the details by reading the FTC’s press release on the settlement resulting from a complaint filed by the Department of Justice (DOJ) on behalf of the FTC on WW International (formerly Weight Watchers). The FTC press release indicated that WW International collected personal information from children as young as eight without parental permission. The settlement instructed not only for the illegally collected data to b...
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An Insightful and Inspiring Tech Talk by Cathy O'Neil on Algorithmic Bias

As a Computer Science Major, I spend most of my days learning and perfecting the skill required to communicate with zeros and ones with fascinating non-sentient systems and embed logic into their memories, so they follow my commands. This sorcery is usually referred to as coding! Just like with magic, we can also program these systems to consume large quantities of data and spit back countless secrets hidden in it; or perhaps answer complex questions that would take us (humans) sometimes up to several lifetimes to compile. This magic is the result of algorithms defined in code. Well-designed code-embedded data-based decision-making logics had been the attainable holy grail for many organizations in recent times and some of us,  data sorcerers,  had been happily non-stop coding as many decisions in our lives as caffeine allows.   We often debate on the quality of the code and the algorithms, but rarely talk about the source data. Even more rarely do we discuss the quality...
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Concerns About Bias in Machine Learning and Artificial Intelligence

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    As science and technology advancements continue pushing the boundaries of what computational power can do, digital data keeps growing in popularity as the preferred method to store and search for human knowledge. Recently, Machine Learning approaches to processing this vast and growing universe of datasets have started to be used to improve efficiency and to be able to keep up with the speed at which our digital universe is growing, not to mention the growing digital cloud empowered by high-speed data transmission. Machine Learning has opened the door to autonomous algorithm-based decision-making. These technologies are the building blocks of Artificial Intelligence.      Basic Artificial Intelligence technology is currently being used to support or even completely overtake decision-making in multiple industry sectors and human ingenuity may likely one day bring into reality more autonomous versions of Artificial Intelligence. Worrall in a 2015 National...
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